CHARACTERIZATION AND MODIFICATION OF BIOMASS PYROLYSIS CHARS FOR ENVIRONMENTAL APPLICATIONS MATTHEW WILLIAM SMITH

Transcription

1 CHARACTERIZATION AND MODIFICATION OF BIOMASS PYROLYSIS CHARS FOR ENVIRONMENTAL APPLICATIONS By MATTHEW WILLIAM SMITH A dissertation submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY WASHINGTON STATE UNIVERSITY The Gene and Linda Voiland School of Chemical Engineering and Bioengineering JULY 2016 Copyright by MATTHEW WILLIAM SMITH, 2016 All Rights Reserved

2 Copyright by MATTHEW WILLIAM SMITH, 2016 All Rights Reserved

3 To the Faculty of Washington State University: The members of the Committee appointed to examine the thesis of MATTHEW WILLIAM SMITH find it satisfactory and recommend that it be accepted. Manuel Garcia-Perez, Ph.D., Chair Su Ha, Ph.D. James Amonette, Ph.D. Jean-Sabin McEwen, Ph.D. Louis Scudiero, Ph.D. ii

4 Acknowledgement I would like to thank my major advisor, Dr. Manuel Garcia-Perez, for his uncompromising support during my studies. His dedication towards science has been a consistent source of motivation throughout these years. I would also like to thank my committee members; Dr. Jean-Sabin McEwen, Dr. Louis Scudiero, Dr. James Amonette, and Dr. Su Ha for their continued guidance and assistance during my PhD. Without their knowledge and assistances this work would not have been possible. I would also like to Dr. Greg Helms, Dr. Armondo McDonald, Dr. Craig Frear, Dr. Tim Johnson, Dr. Carolyn Brauer, and Dr. Juan-Espinal for their assistance and contributions in various aspects of this project. To the staff of both Biological Systems Engineering and the Gene and Linda Voiland School of Chemical Engineering and Bioengineering, thank you for all of your help in navigating the administrative and technical complexities of research and of the degree process. I also thank my colleagues who have provided consistent support, both academic and personal, through my studies, including; Brennan Pecha, Filip Stankovic, Rishi Ghogare, Iva Tews, Yinglei Han, Jason Selwitz, Alex Dunsmoor, Jonathon Lomber, Kelly Welsch, Tyler Enslow, Kristen Ford, Dr. Waled Suliman, Dr. Jesus, Garcia-Nunez, Dr. Raul Pelaez-Samaniego, Dr. Shuai Zhou, Dr. Zhouhong Wang, and Dr. Jieni Lian. iii

5 To all of my friends in Pullman, past and present and too numerous to list here, thank you for making these years so memorable and enjoyable. I would like to thank my family, who, despite uncertainty that I would ever actually finish, have been an unwavering source of support. Finally, and most heartfelt, I would like to thank my wonderful wife, Rocio Jackelyn Carrion Rabanal, who has been my greatest joy and inspiration throughout the last 2 years of this work. Your constant support and encouragement has pushed me to work harder and be more than I ever thought possible. iv

6 CHARACTERIZATION AND MODIFICATION OF BIOMASS PYROLYSIS CHARS FOR ENVIRONMENTAL APPLICATIONS Abstract by Matthew William Smith, Ph.D. Washington State University July 2016 Chair: Manuel Garcia Perez In this project the deconvolution of Raman, X-ray Photoelectron, and Nuclear Magnetic Resonance spectra of chars are examined. To support this work, spectra calculated for a wide variety of polyaromatic structures have been examined using density functional theory. Based on these results a new fitting and interpretation procedure for Raman spectra of chars has been proposed. This method identifies out of plane deformation, 5 membered ring systems, 7+ membered ring systems and heteroatom inclusions, in addition to monitoring the cluster size of aromatic domains. A modified deconvolution procedure has also been proposed for XPS spectra. This method utilizes sequential deconvolution of the O 1s and C 1s spectra. In this method the C 1s deconvolution is constrained by the results of the O 1s spectrum, using the maximum and minimum bonds of for carbon-oxygen bonds based on theoretical groupings. A new quantitative 13 C multiple cross-polarization NMR technique was successfully applied to pyrolysis chars. Coupled with a REDOR type dephasing series this method was used to estimate the cluster size and number of atoms at each distance in a series of cellulose chars. This method provided results consistent with far more time intensive direct polarization studies. The methods developed have v

7 been applied to three thermoseries of chars from primary biomass constituents; cellulose; hemicellulose (xylan); and lignin (milled wood lignin). The results of these studies, in combination with bulk chemical and morphological tests identified fundamental differences, and basic similarities, in the pyrolysis behavior of each compound. Each sample was found to move on a generally ordering trajectory with temperature until 600 o C when out of plane deformations became significant for each material between 600 and 700 o C. Ring cluster size was found to increase slowly until 600 o C and then increased significantly. Finally the effects of ozone on two dissimilar chars, from Douglas fir wood and bark, was examined. These results show dramatically more intense reactions with bark char, though the content of acid groups increased for both materials. Our studies also identified a strong correlation between reactor temperature and lactone group formation. vi

8 Table of Contents Acknowledgement... iii Abstract... v Table of Contents... vii List of Tables... x List of Figures... xiii Chapter 1: Introduction... 1 Page 1.1 Biomass Composition Biomass Structure Thermochemical reactions responsible for biochar formation Strategies for the activation and functionalization of carbonaceous materials Characterization of Carbonaceous Materials Spectroscopic analyses for the study of carbonaceous materials Density Functional Theory Calculations Model of Carbonaceous Materials Dissertation Objectives Methodology Scientific Contributions References: Chapter 2: Structural Analysis of Char by Raman Spectroscopy: Improving Band Assignments through Computational Calculations from First Principles Introduction Materials and Methods Results and Discussions Conclusions References Appendix A Supplemental Material for Chapter A.1 Defect structures in circumpyrene and circumcoronene vii

9 Chapter 3: Improving the Deconvolution and Interpretation of XPS Spectra from Chars by ab Initio Calculations Introduction Materials and Methods Results Conclusions References Appendix B Supplemental Material for Chapter B.1. XPS Deconvolution Figures B.2 Asymmetric line shape for primary C-C peak B.3 Oxygen bracketing equations B.4 Detailed binding energy distributions for assorted compounds presented in the text B.5 Additional C1s peak tables for cellulose deconvolution B.6 References Chapter 4: Effect of Pyrolysis Temperature on Cellulose Char Aromatic Cluster Size by Quantitative Multi Cross-Polarization 13 C NMR with Long Range Dipolar Dephasing Introduction Materials and Methods Conclusions References Appendix C Supplemental Material for Chapter C.1. Detailed pulse sequence description C.2. NMR Shielding for PTCDA Cluster Chapter 5: Chemical and Morphological Evaluation of Chars Produced from Primary Biomass Constituents: Cellulose, Xylan, and Lignin Introduction Materials and Methods Results Discussion Conclusions References Appendix D Supplemental Material for Chapter viii

10 D.2. Bubble Wall Texture of Lignin Pyrolysis Chars Chapter 6: Enhancing Cation Exchange Capacity of Chars through Ozonation Introduction Experiments and Methods Results and Discussion Conclusions References Chapter 7: Conclusions Future work References ix

11 List of Tables Chapter 1 Page Table 1. Standard test methods for coal that can be used for char Table 2. Test Category A: Basic Biochar Utility Properties Required for All Biochars (summarized from IBI requirements Table 1) Table 3. Test Category B: Biochar Toxicant Reporting-Required for All Feedstocks (Summarized from IBI requirements Table 2) Table 4. Test Category C: Biochar Advanced Analysis and Soil Enhancement Properties- Optional for All Biochars (Summarized from IBI requirements, Table 3) Chapter 2 Table 1. Comparison of peak positions and intensities for experimental and unscaled simulated spectra of Naphthalene Table 2. Relative uncorrected maximum intensity of each calculated and experimental Raman spectrum as compared to the uncorrected maximum intensity peak of Naphthalene Table 3. Primary experimental and simulated peak positions and position errors for each major peak (normalized intensity greater than 0.1) of the PAH tested Table 4. Summary of peak assignments Table 5. Peak widths at half maximum for thermoseries (cm -1 ) Table 6. Peak intensities compared to the total area of the G band (GT) Chapter 3 Table 1. Summary of binding energies used for the deconvolution of C1s and O1s spectra (ev) Table 2. Bulk properties associated with cellulose and cellulose chars Table 3. Fine Scan C1s and O1s peak parameters with O1s deconvolution Table 4. Application of symmetric deconvolution methods utilized within the literature and comparison of C:O ratios to totals determined from the total C1s and O1s spectra. Negative values for the deviation from the C1s:O1s ratio indicates an overestimation of oxygen x

12 Table 5. Asymmetric Deconvolutions Table 6. Fitting parameters used for the analysis of model compounds with a GLsum line shape Table 7. Calculated binding energies for various oxygenated functional groups positioned on assorted carbons. Lactone and carboxylic group (1) refers to the carbon connected to both oxygens. Lactone (2) refers to the ether bonded carbon, while carboxyl (2) refers to the carbon adjacent to the carboxyl group Table 8. Peak assignments and parameters for the interpretation of O1s and C1s spectra of chars Table 9. Peak distribution and C:O ratios determined using proposed deconvolution scheme Appendix B Table B1. Peak positions for all peaks used in the deconvolution of cellulose chars Table B2. Full Width at Half Maximum values used for all peaks in the deconvolution of cellulose chars Chapter 4 Table 1. Integrated intensities for PTCDA peaks, see figure 6A for corresponding assignments, and quantification of C associated with each peak compared to the theoretical values Table 2. Peak assignment table Table 3. Assorted Polyaromatic structures with number of carbons C-(-X)-H bond distances specified Table 4. Composition of material based on NMR Specta (%) Table 5. Estimated contribution of various C-H bond distances for chars produced at o C based on dephasing results (%) Chapter 5 Table 1. Heating protocol for proximate analysis Table 2. Peak assignments and parameters for the interpretation of O1s and C1s spectra of chars [56] Table 3. Summary of peak assignments [55] Table 4. Peak assignment table xi

13 Table 5. Elemental composition and FC/VC ratio for all chars (wt. %) (Dry material) Table 6. Surface Area and average pore diameter of chars from each biomass component Table 7. Approximate elemental composition from wide scan spectra of Xylan (atomic %) Table 8. Peak distribution and C:O ratios determined using proposed deconvolution scheme (reproduced from Smith et al. [56] Table 9. C 1s and O 1s group distribution in atomic %. Also included is the C 1s: O 1s Ratio (C:O) and the distribution coefficients denoting how the C-O and COO region are distributed between hydroxyl and ether like group and carboxyl and lactone like groups respectively Table 10. Peak position (and FWHM) for deconvolution peaks used to interpret the Raman spectra of primary component chars produced at o C. Cellulose peak parameters previously presented by Smith et al. [55] Table 11. NMR results estimated functional group contributions (atomic %). Error is approximately 2%. Cellulose data previously presented by Smith et al. [57] Table 12. NMR results estimated bonding distances for groups based on dephasing results and approximate polyaromatic equivalent size. Cellulose data previously presented by Smith et al. [57] Chapter 6 Table 1. XPS Binding Energies and sensitivity factors for elements and chemical structures identified [24] Table 2. Chemical composition of initial chars Table 3. Surface area and pore structure of initial carbons Table 4. Proximate and Elemental Analysis of Treated Samples Table 5. Effect of ozone treatment on surface morphology Table 6. Elemental composition and carbon structures as determined by XPS Table 7. Effect of ozonation time (0-60 min) on the phpzc and quantity of carboxyl, lactonic, and phenolic groups as identified by Boehm titration xii

14 List of Figures Chapter 1 Page Figure 1. Scheme of an anaerobic digestion bio-refinery in which AD fibers is used for engineered bio-chars production Figure 2. Cellulose Chain [26]... 7 Figure 3. Hemicellulose Monomer Units. Left to Right, Top to Bottom: D-glucose, D- mannose, D-galactose, D-xylose, L-arabinose, 4-O-Methylglucuronic acid... 8 Figure 4. Lignin Monomer Units. (A) p-coumaryl Alcohol (B) Coniferyl Alcohol (C) Sinapyl Alcohol... 9 Figure 5. Bonding Types Present in Lignin Oligomers. From left to right β-o-4, α-o-4, β- 5, 5-5, 4-O-5, β-1, β-β [48] Figure 6. Cellulose primary thermo-chemical degradation reactions, modified from reaction mechanism proposed by Wang et al. [67] Figure 7. Multistep lumped mechanism for the pyrolysis of lignin that will be evaluated in this proposal. Adapted from Zhou [87] Figure 8. Representations of amorphous carbon using graphene sheets (A) nanocrystalline model of amorphous carbon proposed by Franklin [195], reproduced by permission of the Royal Society, and (B) falling card model proposed by Dahn et al. [195], reprinted with permission from Elsevier Figure 9. Non-graphitic representation of amorphous carbon structures (B) Illustration of the curved carbon fragments containing cyclopentane-, cycloheptane- and cyclohexane-ring systems as identified by Harris et al. [199] IOP Publishing. Reproduced with permission. All rights reserved. (C) 2D chemical representation of coal structure, as proposed by Shinn [203], reprinted with permission from Elsevier Figure 10. Flow diagram highlighting work conducted during this program Chapter 2 Figure 1. Several models exist that attempt to describe the underlying structure of coals and activated carbon, these include: (A) Representation of non-graphitizing carbon as randomly oriented nano-graphitic regions, as hypothesized by Franklin [19], reproduced by permission of the Royal Society. (B) Illustration of the curved nature of carbon fragments containing cyclopentane-, cycloheptane- and cyclohexane-ring systems as identified by Harris et al. [28] IOP Publishing. Reproduced with xiii

15 permission. All rights reserved. (C) A 2D chemical representation of coal structure, as proposed by Shinn [32], reprinted with permission from Elsevier Figure 2. Application of different deconvolution methods to the Raman spectra of a cellulose pyrolysis char produced at 400 C Fitting methods adapted from (A) Ferrari et al. [40, 42] (B) Hu et al. [43] and (C) Li et al. [17] Figure 3. Effect of basis sets on the simulated Raman spectra for naphthalene. The experimental spectrum has been wavelength- and intensity-corrected for instrument response Figure 4. (A) Comparison of experimental and predicted Raman spectra for various PAHs with their position correct simulation counterparts. Solid black lines represent simulated results, while dashed red lines represent experimental results. (B) Representation of the A1g symmetric breathing mode for a benzene ring (C) Kekulé type vibration for a benzene ring (D) E2g asymmetric stretch in alkene and aromatic carbons. Position lines denoting the change in location of the A1g, Kekulé and E2g vibrations are provided as black lines spanning the spectra of Naphthalene Coronene. The symmetry labels used in 4B-D are derived from the D6h structure of the benzene Figure 5. Effect of alkyl chains on the predicted Raman spectra of a coronene-based molecule Figure 6. (A) Effect of cyclopentane center on position of symmetric breathing mode of the parent coronene molecule in the modeled Raman spectrum (B) Predicted Raman spectra of heptane ring system at the 6-31G level, detailing a symmetric ring breathing mode near 1175 cm Figure 7. Effect of various single point defects on the calculated Raman spectra of a coronene based molecule (upper spectra contains a single nitrogen atom substitution denoted in blue). The spectrum of coronene is provided at the bottom of the figure for comparison Figure 8. Effect of various DPDs on the calculated Raman spectra of a coronene based molecule (The spectrum of coronene is provided at the bottom of the figure for comparison) Figure 9. Effects on the calculated Raman spectra of oxygenated single and double point defects of a coronen-based molecule. The spectrum of coronene is provided at the bottom of the figure for comparison Figure 10. Effect of oxygenated edge sites on the predicted Raman spectra of a coronenebased molecule. The bottom spectra are of anhydrous tetracarboxylic perylene. Solid lines represent simulated data while the dashed red line represents experimental data xiv

16 Figure 11. Experimental Raman spectra of chars produced from cellulose at different temperatures. All data were collected using a 532-nm incident light Figure 12. (A) Deconvolution of Raman spectrum of a cellulose char produced at 400 C using the newly proposed method. The red line (online version only) represents the summation of curves while the solid black line is the original experimental data. The dotted black lines are individual Gaussians based on the curve fitting parameters given in Figures 13B-D and Table 5. The effect of temperature on the deconvolution curve parameters for (B) Peak position (C) Peak intensity of breathing modes and (D) peak intensity of asymmetric stretch modes are also given Appendix A Figure A1. Assorted defects within a circumcoronene (CC) parent system. Single Point Defects (SPD) and Double Point Defects (DPD) correlate to the same defects utilized in the coronene parent throughout the paper Figure A2. Assorted defects within a circumpyrene parent system. SPDs and DPDs correlate to the same defects utilized in the coronene parent throughout the paper Figure A3. Parent (A) circumcoronene and (B) circumpyrene compounds used to assess defects in larger ring systems. Numbers 1 and 2 denote carbon atoms removed to create defects. For SPDs only atom 1 is removed, for DPDs both atoms are removed or replaced Chapter 3 Figure 1. FT-IR transmittance for a thermoseries of cellulose chars produced at temperatures from 300 o C to 700 o C. Dash lines indicate important regions of the various spectra Figure 2. (A) Comparison of the wide-scan XPS results for Avicel cellulose and the resultant chars. (B) Parity plot of the atomic bulk C:O ratio from elemental analysis with the C: O ratios obtained by XPS using by high resolution C1s and O1s scans Figure 3. Development of (A) C1s and (B) O1s XPS spectra with increasing pyrolysis temperature Figure 4. Experimental (red) and theoretical (black) binding energy overlays for (A) Pyrene C1s (B) Cellobiose C1s (C) PTCDA C1s (D) cellobiose O1s. The experimental lines are computed using the corrected bindings determined via DFT, and expanded based on the individual broadening parameters given in Table 6. The intensity of both the experimental and theoretical lines are normalized against the point with greatest intensity. Individual binding energies for each C and O atom are given in Appendix B section B4, Figure B xv

17 Figure 5. Reference spectra for Coronene (green), circumpyrene (black), and circumcoronene (red) Figure 6. Reference sp 3 containing carbon structures (A) single pentane chain linked to coronene (B) two pentane chains linked to coronene (C) single buta-di-ene chain linked to coronene (D) two buta-di-ene chains linked to coronene. The black line in each Figure denotes the modified coronene structure, while the red dashed line gives the parent coronene. Individual binding energies for each C atom are given in Appendix B section B4, Figure B Figure 7. Effect of (A) cyclopentane defect and (B) cycloheptane defect on core binding energies. Values A-C give the respective shift of the calculated binding energies for each unique position relative to the average binding energy calculated for coronene ( ev). The black line denotes the calculated spectrum for the cyclopentane centered ring system shown, while the red dashed line is that of coronene Figure 8. (A) Effect of Stone Wales defect on core binding energies in circumpyrene parent system, values A-J give respective calculated binding energy shifts relative to the average shift of coronene, ev, bold denotes significant shifts, values in red are negative shifts (B) Simulated C1s plots for defects in (black lines) and unmodified (dashed red lines) coronene, circumpyrene and circumcoronene parent systems with FWHM of 1.56 and G:L = 0.55 for each atom (C) Spectra from B with FWHM reduced to 0.5. Individual binding energies for coronene and circumcoronene are given in Appendix B section B Figure 9. Binding energy shifts in adjacent, as well as second nearest neighbors associated with (A) hydroxyl (B) carbonyl (C) carboxylic and (D) lactone groups. Group A represents the average reference shift for C-H atoms, while B is the average shift of C-C in each compound. All shifts are relative to the original binding energy of atoms at the same relative position in the parent coronene Figure 10. Basic algorithm for the combined O1s/C1s deconvolution of XPS spectra of chars and amorphous carbons Figure 11. Deconvolution of (A) C1s and (B) O1s spectra from C Appendix B Figure B1. Various deconvolution schemes utilized for chars and activated carbons in the literature using the C400 C1s spectrum as a reference. (A) Basic Deconvolution (B) inclusion of Defect/sp 3 carbon peak (C) implements both C-C peaks from B and adds an additional defect peak shifted -0.4 ev from the primary C-C peak (D) use of an asymmetric primary C-C peak (E) use of both a defect/sp 3 peak and asymmetric primary C-C peak (F) uses the same peaks as described in D with the addition of a low energy defect C-C peak xvi

18 Figure B2. Comparison of empirical asymmetry equation to DS line shape for (A) uncorrected and (B) Shirley background corrected DS line shape. Black line is DS line, dotted black line empirical line-shape with TL = 200, red dots empirical line shape with TL = 600. Asymmetry parameters alpha=ts = Figure B3. Calculated C1s core binding energies relative to the average calculated binding energy of coronene ( ev) are given for each lettered assignment for (A) Pyrene (B) cellobiose and (C) PTCDA. (D) Calculated O1s binding energies for each oxygen in cellobiose. These values are used to calculate the respective spectra given in figure 4 of the main text. Bold values denote shifts from the coronene reference greater than 0.4 ev. Red values indicate negative shifts Figure B4. Calculated C1s binding energies for (A) alkane and (B) alkene chain modified coronene structures as discussed in Figure 6 of the main text. Only coronene modified with 2 chains are shown here, however the effects for a single chain are highly similar. All shift values are given relative to the average calculated binding energy of coronene at ev. Bold values indicate shifts greater than 0.4 ev while red values indicate negative shifts Figure B5. Calculated C1s binding energies for stone-wales defect inclusions in (A) coronene and (B) circumcoronene, as discussed in Figure 8 of the main text. All shift values are given relative to the average calculated binding energy of coronene at ev. Bold values indicate shifts greater than 0.4 ev while red values indicate negative shifts Chapter 4 Figure 1. Pulse sequences used for this study, all signal acquisitions were taken on a Han Echo with TPPM decoupling on the 1 H channel. (A) MultiCP with standard acquisition (B) DP with standard acquisition (C) MultiCP with dipolar dephasing and continuous wave decoupling around the dephasing period (D) DP with dipolar dephasing and continuous wave decoupling around the dephasing period (E) drop in long range dephasing sequence used with both MultiCP and DP experiments. A detailed expiation of each sequence is given in Appendix C section C1 with the related code for each method Figure 2. Van Krevlen plot of atomic H:C and O:C ratios from combustion analysis. Solid lines represent theoretical vectors for the loss of CO and CH4 and various initial compositions. The central black line represents the theoretical change associated with dehydration reactions Figure 3. XRD spectra for cellulose and cellulose derived chars, the FWHM of the 002 peak for each material is listed adjacent to each spectra with the estimated crystallite size calculated by the Scherrer equation, assuming a shape factor of Figure 4. Effect of contact time and passed on the spectra obtained for DFW300. (A) A series of multicp scans using a ramped contanct of 1.0 ms per pulse and (B) 0.5 ms per pulse. Blue line gives a reference CP spectrum obtained with a 1.0 ms pi pulse, xvii

19 green line is a single ramped CP period, the red line is 7 passes and black line is 11 passed. Figure C shows a comparison of the spectrum collected after 7 passes using a 1.0 ms ramped CP period (red line) with the background corrected spectrum obtained by DP (black line) (D) compares the spectrum obtained by 11 passes using a 0.5 ms ramped CP period (red line) Figure 5. C700 with dephasing. Black lines represent MultiCP signals from 2048 scan scaled by exactly 1/11. Red lines represent DP signal collected after 256 scans. Total acquisition time for MultiCP experiments was 6.5 hrs while DP experiments required 9.6 hrs Figure 6. (A) MultiCP spectrum for PTCDA collected form 2048 scans, relative integration areas are provided above each distinct peak within the main spectra and the side bands. (B) DP spectra for PTCDA using 1.5 (red), 3 (black) and 7 (blue) minute recycle delays, spectra for 1.5 and 7 minutes are a composite of 32 scans while the spectrum for 3 minute delays is a composite of 512 with the background normalized to the other spectra. (C) Comparison of MultiCP spectrum (black line) to calculated spectrum for isolated PTCDA (red line) (D) comparison of MultiCP spectrum to calculated spectrum for the central molecule of a 6 molecule PTCDA cluster Figure 7. Dephasing plots for Tetracarboxylic perylene Figure 8. Dephasing results individual carbons in PTCDA (A) dephasing over time for carbons A-E with the theoretical rate for A and C+D given as dashed line (B) comparison of experimental dephasing rate with F value, black line denotes empirical equation proposed by Mao and Shmidt-Rohr [44] Figure 9. Theoretical spectra for 9 compounds (A) pentacene (B) coronene (C) circumpyrene (D) cyclopentane centered ring system (E) cycloheptane centered ring system (F) coronene with Stone-Wales defect (G) conenene with added carboxyl group (H) coronene containing lactone group (I) coronene with single point defect closed by ether group and carbonyl group. All compounds containing carbon at shifts less than 120 ppm and greater than 140 ppm have been assigned alphabetic labels that correspond to each respective figure. New labels are used for peaks separated by more than 3 ppm Figure 10. (A) Theoretical dephasing for various carbons within circumpyrene at different apparent distances from hydrogen (1.9 A < rc-h < 3.8 A) (B) Composite dephasing for various polyaromatic structures of increasing size (squares rylene, diamonds = coronene, triangles = circumpyrene, and circles = circumcoronene). The red line denotes an S/So value of 0.05 as an approximate minimum quantification level Figure 11. Changes in Char spectra with temperature, Deconvolution scheme shown for C Figure 12. Plot of NMR spectrum and dipolar dephasing spectra for C500. All spectra have been collected using 2048 scans xviii

20 Figure 13. S/So plots for C400 (squares) C500 (diamonds) C600 (triangles) and C700 (circles) the solid red line represent the theoretical dephasing for coronene based on first order kinetics and the black line for circumpyrene. The insert shows an expanded view of the dephasing plot between 0.3 and 1.1 ms for clarity Figure 14. Example char structures based on composition shown in Table 4 and C-H distance and quantity from table 5 for C300-C Appendix C Figure C1. Shift in NMR shielding for carbon F (see figure 6A in chapter 4 for primary labels) when comparing molecules within the cluster (labeled as sites A here only) to those at the edge (labeled as sites B-D here only). Similar patterns are also observed for carbon G (again see figure 6A), however those shifts do not result in contamination of a second peak Chapter 5 Figure 1. Examples of reactant loads and product yields obtained during pyrolysis of pure components (A) example load of 1.0 grams Avicel cellulose (B) char produced from 1.0g cellulose at 700 o C (C) char produced from 1.0 g Xylan at 700 o C (D) Char produced from 0.5 g of MWL at 700 o C Figure 2. T vs time plots obtained for center of samples in spoon reactor trials respectively for (A) Cellulose (B) Xylan and (C) MWL Figure 3. Char yields for each of the components studied Figure 4. Pyrolysis progress from Raw material, to 500 o C and 700 o C for (A-C) Cellulose and (D-F) xylan. All images are taken at 100X magnification except (D) which was taken at 50X due to charging at 100X magnification Figure 5. Melt and boil progression of lignin at different pyrolysis temperatures (A) untreated (B) 300 o C (C) 400 o C (D) 500 o C (E) 600 o C (F) 700 o C Figure 6. Surface morphology of chars from Cellulose (A) 500 o C (B) 700 o C, Xylan (C) 500 o C (D) 700 o C, and Lignin (E) 600 o C (F) 700 o C. All images are taken at 10000X magnification Figure 7. X-ray diffraction patterns for (A) Cellulose, (B) Xylan and (C) Lignin Chars. FWHM and apparent crystal size from the Scherrer equation are given for cellulose, reproduced from Smith et al [57] Figure 8. Survey scan progression for the thermoseries for (A) Cellulose (B) Xylan and (C) MWL char series. Cellulose series reproduced from material presented by Smith et al. [56] xix

21 Figure 9. High resolution scans for the (A) Na 2s (B) C 1s (C) O 1s regions of the Xylan spectra Figure 10. Deconvolution of Xylan 600 o C 1s and C1s regions Figure 11. Raman Spectra progression for (A) Cellulose (B) Xylan and (C) MWL. The progression of the S, D, and G bands are highlighted by arrows for each series. The spectral series for cellulose is reproduced from Smith et al. [55] Figure 12. Intensity fractions for major peaks associated with A1g type modes for chars from (A) cellulose (B) Xylan and (C) MWL and from E2g type modes for chars from (D) Cellulose (E) Xylan and (F) MWL. Associated peak labs are listed beside the 400 o C point. Lines are provided for visual reference only. Figures A and B are reproduced from Smith et al. [55] Figure 13. NMR spectra progression for (A) cellulose (B) Xylan and (C)MWL with dephasing plots for (D) cellulose (E) Xylan and (F) MWL for D, E and F, open circles are chars produced at 300 o C, squares are 400 o C, diamonds are 500 o C, triangles are 600 o C and circles are 700 o C. Results for cellulose are reproduced from Smith et al. [57] Figure 14. D band peak position vs cluster size Appendix D Figure D1. Example effect of Ash on morphology of Xylan. Both samples have been pyrolyzed using a vacuum flash pyrolysis reactor at WSU, images taken at 2000x magnification (A) Xylan as received (B) acid washed using dilute HCl. Images kindly provided by Brennan Pecha, to be submitted to the Journal of Analytical and Applied Pyrolysis [1] Figure D2. (A) Medium and (B) high magnification of the ruptured portion of a bubble in char from MWL. The sub-micron smooth sheets are a result of a complete melt of the initial MWL and suggest a higher degree of molecular organization than is possible in materials that do not form a complete melt Chapter 6 Figure 1. (A) Temperature variation of the packed bed reactor, (B) mass fraction remaining after oxidation, and (C) ozone consumed during reaction. Filled triangles DFWC, open circles DFBC, filled circles AC Figure 2. (A) N2 and (B) CO2 isotherms for selected carbons. CO2 isotherms for activated carbon have been shifted by 20 cm 3 /m 2 to avoid convolution with DFBC curves. Solid lines untreated, dashed lines 60 minute treatment Figure 3. Effect of ozone treatment on pore size distribution of activated carbon, nearest plot AC-60, furthest AC-0. Treatment results in continuous decrease of pores of 1- xx

22 1.5nm while an initial increase, followed by gradual reduction is observed for those of ~ 0.5nm Figure 4. XPS wide scan results for DFBC Oxidation time increases from 0-60 minutes moving up the graph. Bold series at the top is acid washed DFBC-60. Treatment results in sharp increase in oxygen peak, with simultaneous reduction and broadening of the carbon peak. A strong increase in calcium is noted on the surface after prolonged exposure to ozone, mild acid washing successfully remove this material Figure 5. of untreated and 60 minute ozone treated samples; normalized to C-C/C-H peak and corrected for background. Solid line- untreated, dashed line-treated, dotted lines-best fit curves from deconvolution of untreated samples (A) AC (B) DFWC (C) DFBC. (D) Comparison of DFBC-60 before and after acid washing; normalized to the C-C/C-H peak and corrected for background. Bold dashed line unwashed DFBC-60, solid line acid washed DFBC-60, gray line residual from subtraction of acid washed spectra from unwashed spectra. dotted lines Gaussian fit of residual peak: 1 st residual at FWHM of 4, 2 nd residual at FWHM of Figure 6. Correlation between content of Lactone groups and oxidation temperature (r 2 = 0.89) Figure 7. (A) Effect of ozonation on the CEC of each material (B) regression analysis of CEC compared with changes in carboxyl groups (r 2 =0.93 and slope = 0.99 with the origin forced) xxi

23 Chapter 1: Introduction Utilization of biomass for products, fuels and chemicals is among the oldest technologies in human history [1], and until only recently comprised our primary source fuel and basic chemicals [2, 3]. During the industrial revolution, with increasing demands for fuel, coal became the dominate source of energy in the industrialized world. This transition continued as society developed, and the growth of the petroleum refinery during the late 19 th and 20 th century displaced older techniques, including wood distillation for basic chemicals such as acetic acid [2, 3]. The development of gasoline and diesel from petroleum based sources, then by-products of kerosene refining, offset ethanol and vegetable based fuels as the dominant choice for the fledgling automotive industry [4-6]. Since then, sophistication of the petroleum industry has only increased, developing many of the chemicals and products modern life has become dependent upon. With this however, has come a range of challenges, including the finite supply of these fossil resources, their concentrated geographic location, and the detrimental effect that releasing this historically fixed carbon has had on atmospheric and oceanic patterns through increased green-house gas concentration and the related acidification of ocean waters [7, 8].The engineered oil shortage that occurred during the 1970s prompted renewed interest in the development of a more regionally stable fuel supply, including renewable sources [9, 10]. Since then, societal and scientific interest in the development of renewable products has increased steadily in the United States, and around the world. This increased interest has been driven by a range of considerations, including; national fuel security, rural development, and mitigation of greenhouse gas emissions from fossil resources. A variety of new biomass conversion technologies have been proposed and older technologies modified to meet the evolving challenges of the modern fuel and chemicals market [9-11]. 1

24 Biomass conversion processes generally fall into one of three categories: Chemical, biochemical, or thermochemical [12, 13]. Each of these methods have been used in some form for thousands of years, including fermentation for alcohol, combustion for heat, and slow pyrolysis for charcoal [1]. Regardless of the conversion technology chosen, the challenges of using a biomass based feedstock are consistent. In any processing scheme chosen, the ultimate goal is to produce consistent fuels and chemicals in a sustainable and efficient manner, avoiding impact on food supply, and maintain profitability despite variations in feedstock supply and quality. Among the most promising, and challenging, techniques for the rapid conversion of biomass is the process of pyrolysis [9, 10, 14]. Here, biomass is heated in an environment free of oxygen (or with very low content of oxygen in the case of auto-thermal processes), allowing a wide range of thermochemical reactions. This process results in the production of solid carbonaceous materials (also known as char), liquid products (known as tars or bio-oils) and gas (known as syngas or pyrolytic gases. These products have a significant potential for fuel and chemicals production [15]. By controlling the heating rate, the yields of solid and liquid products can be varied dramatically. With slow pyrolysis (heating rates of 10C/min or less) producing mostly charred solid residues [1] and fast pyrolysis (heating rates often in excess of 100C/s) generating far more liquids [10]. While pyrolysis generates numerous compounds of chemical interest, they are typically collected in low concentrations in a very complex matrix containing several hundred of compounds with a wide range of molecular weights and functionalities [9]. In addition to the mixed liquid phase, a significant fraction of the feed carbon, up to 50% when slow heating occurs, polycondenses to form a solid, amorphous carbon (char) which is the subject of this dissertation [1]. 2

25 Among the most heavily studied applications for biomass based chars is that of biochar. This material is defined as a biomass derived char specifically intended for agricultural application. Interest in these materials is based on evidence that chars have had long term positive effects on soil quality, substantially altering the physical and chemical properties in Terra Preta soils [16-18]. These changes have led to long lasting carbon storage and improved crop production. By returning chars to the field, mineral matter is recycled back into the original soil, reducing the rate of soil degradation and depletion [19, 20]. This process can also remove a considerable fraction of the associated carbon from the carbon cycle as the solid chars are stable within the environments for hundreds to thousands of years [21]. Carbonaceous materials formed by high temperature pyrolysis contain large fractions of highly stable aromatic compounds resistant to microbial attack [19]. The physical properties and surface chemistry of these chars can have a number of positive effects on the soil, including: lowering the overall packing density, improving aeration, and improving the cation-exchange capacity and the water holding capacity [19, 22, 23]. By returning chars to the fields, it may prove possible to increase the health of agricultural soils and improve the productivity of the land. While char has significant potential as a soil amendment, studies with freshly produced materials have not always been able to reproduce the effectiveness of the centuries-old Terra Preta soils of the Amazonian Basin [23]. One hypothesis is that when the char is left in the soil for long periods of time the surface is slowly oxidized [16], and these oxidized groups are responsible for the observed improvements in soil quality. Another possibility is that the chars are initially devoid of any adsorbed nutrients and addition causes an initial depletion of bio-available nutrients due to adsorption on the char surface. 3

26 A second application under consideration is the use of pyrolysis chars for adsorption processes in a way similar to activated carbons. While heavy activation appears to be a promising route, it is worth noting that the actual market size for activated carbon is rather small (~ 1.3 million tons/year in the US) and could be saturated by approximately 8 large pyrolysis facilities (5000 TPD, assuming a 90% uptime and 10% activated carbon yield) causing a crash in prices. Because char prices are relatively low, char prices of approximately $76 -$280/ton have been estimated recently to provide pyrolysis facilities with breakeven revenue for several pyrolysis plant concepts [24, 25], other applications may be viable. At these prices, a potential application is to target emerging markets, focused on high volume, lower value clean up, providing intermediate prices for these materials. These large scale applications include clean-up operations such are public works (e.g. storm water remediation), superfund sites, or large scale agricultural operations such as confined animal feeding operations (CAFOs) or dairies. Each project would likely require specific adsorption properties, and as a result, given the scale of the projects, highly specialized activated carbon can rapidly become cost prohibitive. Here, potential exists for slightly modified pyrolysis chars (engineered chars), provided the cost is sufficiently low to offset lower overall capacities and specificity when compared to activated carbon. An excellent evaluation case for these types of projects is that of anaerobic digesters located at dairy operations. Because of the high concentration of animals, nutrient production often far exceeds the land requirements directly surrounding the operation. This leads to over application challenges for phosphorous (P) and nitrogen (N), which can resulting in leaching to groundwater. High concentrations of N and P species in ground water results in contamination of rivers and streams eventually leading to eutrophication of lakes and river deltas [26-28]. Remediation of these 4

27 species has been examined in the literature. Investigation of the effectiveness of oxidized carbonaceous materials for the removal of ammonia from gas streams and ammonium from liquid streams has proved promising [29-33], with a strong correlation between the concentration of acid functional groups and total adsorption identified [30]. In contrast, the adsorption of phosphate by pyrolysis chars has been shown in recent studies [34, 35] to proceed primarily by sorption to the surfaces of bound metal oxide species, particularly magnesium oxide. Agricultural models provide an interesting prospective market as there is a potential for increased value of char after adsorption. This is in comparison to the disposal cost for spent adsorbents containing toxic material or disposal of adsorbents without a secondary application. Because, carbonaceous materials generated from pyrolysis processes have been found to have positive agricultural effect [20, 36, 37], land application of spent adsorbents (especially those used to remove nutrients from effluent streams) may be feasible, provided the adsorbed material does not contain elements or compounds deleterious to plant or animal health [38, 39]. A possible example of the interplay of pyrolysis and chars in an anaerobic digester facility is shown in Figure 1, where the oxidized char is used as an adsorbent for both nitrogen and phosphorous, allowing for a material that can be immediately beneficial in agricultural applications. In this process, nondigestible fiber is pre-loaded with minerals from the effluent stream by a ph elevation and then pyrolyzed to generate heat for facility operations and char. The high mineral char is then oxidized by exposure to air before being used to polish the effluent streams for ammonia/ammonium and phosphate. 5

28 Figure 1. Scheme of an anaerobic digestion bio-refinery in which AD fibers is used for engineered bio-chars production. To effectively design materials for these wide ranging applications a fundamental understanding of the char properties and formation mechanisms is required. A variety of processing parameters affect the final product, including feedstock composition, processing time, heating rate, and the final treatment temperature. Pre- and post-pyrolysis treatment also have a significant effect on the final char properties. 1.1 Biomass Composition Because the quantity, chemical composition, and physical properties of biomass pyrolysis products (biochar and bio-oil) are strongly dependent on the raw material, understanding of the feedstock 6

29 composition is essential. Biomass is composed primarily of cellulose, hemi-cellulose and lignin with a small fraction of light aliphatic and aromatic compounds (extractives) and mineral matter (ash). While these basic compounds are common to all biomasses the physical structure and composition of the material varies widely and affects the progression of pyrolysis reactions and the chemical composition and morphology of resulting chars Cellulose Cellulose is the most prevalent biological polymer on Earth, comprising approximately 50% of all biomass on the planet. It is a homogenous polymeric compound composed of anhydroglucose units linked by β 1-4 glycosidic bonds [40] with average chains containing hundreds to over ten thousand monomeric units. A representative portion of a cellulose chain is shown in Figure 2. Figure 2. Cellulose Chain [26] Cellulose chains form microfibrils through hydrogen bonding with adjacent chains, and can result in the formation of six known structures (I, II, IIII, IIIII, IVI, IVII), as detailed by O Sullivan [40]. Of these structures only two polymorphs of naturally occurring cellulose are known, both comprised of type I structures. These structures include the Iα (triclinic) and Iβ (monoclinic) phases, of which Iβ is predominantly found in higher plant species such as trees and herbaceous 7

30 biomass [40]. By comparison the amorphous chains, also found with the cell walls of plants have a degree of polymerization of a few hundred or less and show far less regularity in orientation and hydrogen bonding [40] Hemicellulose Hemi-cellulose is a complex amorphous polymer matrix comprising approximately wt. % of plant biomass. Sugar units commonly found in hemicellulose are shown in Figure 3 and include: D-xylose, D-mannose, D-glucose, D-galactose, and L-arabinose. The type and quantity of these units vary significantly between plant species [41]. While this polymer does contain a substantial degree of β 1-4 glycosidic bonds, the structure also contains significant branching at other sites that prevents the formation of large, linear changes [42, 43]. In addition the degree of polymerization is greatly reduced, containing only a few hundred units. Figure 3. Hemicellulose Monomer Units. Left to Right, Top to Bottom: D-glucose, D-mannose, D-galactose, D-xylose, L-arabinose, 4-O-Methylglucuronic acid 8

31 1.1.3 Lignin Lignin is a complex, amorphous polymer composed primarily of methoxylated phenylpropane monomers, and is described by Klein and Virk [44] and Hou et al. [45] as groups of single ring aromatics which vary by the type of propanoid side and the position of the methoxyl groups attached to the ring. Three primary monomeric units comprise the lignin matrix; p-coumaryl alcohol, coniferyl alcohol and sinapyl alcohol, these units are shown in Figure 4. The distribution of these monomeric units varies by species. P-coumaryl alcohol (Figure 4A) is found in small quantities in both hardwood and softwood. Sinapyl alcohol (Figure 4B) is the primary monomer in hardwoods, while coniferyl alcohol is the primary lignin unit in softwoods and also present in hardwoods [46, 47]. A B C Figure 4. Lignin Monomer Units. (A) p-coumaryl Alcohol (B) Coniferyl Alcohol (C) Sinapyl Alcohol The lignin matrix serves as a binding agent for the cellulose and hemicellulose within wood materials, providing increased structural stability to the cell wall [41-43]. To produce the necessary cross-linked structure, a variety of C-C and C-O-C bonds exist between monomer units The bonds 9

32 between the monomer units of lignin, shown in Figure 5, are: β-o-4, α-o-4, β-5, 5-5, 4-O-5, β-1, and β-β bonds [42, 43, 46]. C C C C C C C C C O C C C C C C O O O O Figure 5. Bonding Types Present in Lignin Oligomers. From left to right β-o-4, α-o-4, β-5, 5-5, 4-O-5, β-1, β-β [48] Extractives In addition to the primary components of cellulose, hemicellulose, and lignin biomass materials also contain a wide range of non-structural chemicals which are typically soluble in organic solvents such as ethanol, acetone, and water [47]. Extractive compounds include fats and waxes, terpenes and terpenoids, and phenols. These extractives typically comprise 4-10 wt. % of wood species, though higher contents are possible in tropical wood species and herbaceous biomass. The content of extractives also varies based between regions within the same plant; bark and leaf 10

33 fractions typically having a higher concentration than is found in the woody fraction of the plant [47] Ash Biomass contains an inorganic fraction comprised of necessary micronutrients needed as well as other mineral matter taken from the soils. The inorganic fraction usually represents wt. % of wood [49], with higher contents, sometimes in excess of 5 wt. % in grasses, leaves and barks. The primary elemental constituents are phosphorus (phosphates), sulfur (sulfates), silica, alkali and alkaline earth metals, and a small fraction of transition metals such as iron and copper [49]. The majority of these constituents are stable at pyrolysis temperatures and are concentrated in the char fraction. 1.2 Biomass Structure Biomass contains three distinct cell types, parenchyma cells, collenchyma cells, and sclerenchyma cells. Parenchyma cells are thin walled, semi flexible cells which provide the primary transport of nutrients and carry out metabolic function. Collenchyma cells are thick walled cells and provide structure in herbaceous biomass. Sclerenchyma cells are typically dead cells that have thick secondary walls and provide the primary structural support for woody biomass [47]. Stems and trunks represent to most common fraction of cellulosic biomass harvested. These materials are composed of long cells with rigid cell walls, providing both strength and nutrient transport [47]. Both stems and trunks are composed of a variety of cells which vary radially. 11

34 Central to both trunk and stems is the pith, a collection of parenchyma cells that store and transport nutrients. Surrounding the pith is the xylem which contains both parenchyma and fiber cells, and provides the primary structural support for the plant. This is the primary component of woody biomass and facilitates water and nutrient transport. The phloem, surrounding the xylem, is a thin layer of parenchyma cells that transports organic nutrients through the plant. The outer layer of stems consist of a ring of sclerenchyma cells the cortex and epidermis, which provides additional structural support, nutrient transport, storage of nutrients and other compounds, and protection from the environment. In woody plants the layer surrounding the phloem is periderm (bark) which contains a significantly higher fraction and variety of non-lignocellulosic compounds and is the primary boundary layer between the plant and the environment. 1.3 Thermochemical reactions responsible for biochar formation Carbonization of lignocellulosic material proceeds initially via primary cracking and cross-linking reactions [50-53]. Volatile compounds formed by the initial primary reactions undergo secondary heterogeneous reactions with char along the diffusion path out of the particle (Hastaoglu and Berruti 1989, Shen et al. 2009). The reactions and kinetics for each primary constituent of biomass vary considerably, resulting in a variety of reaction pathways Cellulose pyrolysis The reactions responsible for the formation of volatile products are in general better studied than the reactions responsible for char formation. A simplified scheme of cellulose pyrolysis and carbonization reactions is shown in Figure 6. In this scheme, carbonization of cellulose proceeds 12

35 via three major reactions: (1) formation of active cellulose (crystalline depolymerized cellulose) by the cleavage of weak glycosidic bonds every glucose units [54-60], (4 and 6) formation of a molten cellulose and cross-linking dehydration reactions to form cross-linked structures and water [54, 61], and (8) poly-condensation of cross-linked cellulose to form charcoal [58, 62-66]. Hydroxyacetaldehyde, Acetol Fragmentation 3 Cellotriosan, Cellobiosan, Levoglucossan Depolymerization Cellulose of High Degree of Polymerization 1 2 Cellulose of Low DP ( ) (Active Cellulose) H 2 O, 2-furaldehyde, 5-hydroxymethyl Furfural Dehydration 5 Reactions 4 Molten Cellulose 6 Crosslinked dimmers and Trimers, H 2 O 7 Crosslinked Cellulose Polycondensation 8 Char + CO 2 Figure 6. Cellulose primary thermo-chemical degradation reactions, modified from reaction mechanism proposed by Wang et al. [67] The carbonization pathway competes with the formation of volatile compounds via: (2) depolymerization of active cellulose to produce mono and oligo-sugars [57, 68-70], (3) fragmentation or open ring reactions leading to the formation of small molecules with little economic value [50, 51, 56, 57, 70-73]. This project will focus primarily on the products of Reactions 4, 6 and 8 (Figure 6) to describe the formation of char. An explanation of the crosslinking mechanism of cellulose is hypothesized by Pastorova et al. [74]. In this model randomized three dimensional growth of the condensed phase occurs through oxygen mediated reactions such as the aldol reaction, within the active cellulose or melt phase. In 13

36 addition to aldol condensation, at temperatures above 200 o C, ESR studies have identified the formation of radical sites from homolytic cleavages [75]. These highly reactive free radical sites can promote a variety of additional reaction including C-C crosslinking and condensation reactions. Previous analysis of cellulose chars by NMR and Py-GC-MS studies have demonstrated the formation of a numerous aromatic ring systems including furans, pyrans, and 5 and 6 membered aromatic rings [74, 76]. Still, work is required to further detail the reaction mechanisms that give rise to chars, and to determine the overall structuring of these products within the nascent char Hemicellulose pyrolysis The thermal decomposition of hemicellulose is the least studied of the primary biomass components [77].While degradation is often assumed to follow reaction pathways analogous to cellulose, its amorphous structure reduces the temperature at which pyrolysis reactions happen. Thermogravimetric studies show that primary decomposition of hemicellulose happens at temperatures as low as 250 o C and is nearly complete by 350 o C [78, 79]. These studies also show that only a mild mass loss is associated with further heating to 700 o C. While hemicellulose chars have not been well characterized, analysis of the vapor products from hemicellulose pyrolysis indicate that substantially higher amounts of furanic type compounds are formed compared with cellulose [77]. While the reactivity of the polymer is dramatically different, the same basic reactions that yield cellulose char are expected to contribute to char formation from hemicellulose. 14

37 1.3.3 Lignin pyrolysis Lignin bond cleavage is predicted to proceed via hemolytic cleavage, substitution, and hydrogen transfer induced bond-scission reactions [80, 81]. The various linkages are known to vary in reactivity; Kawamoto [82] listed the reactivity of each dimer as follows: β-1 (ph) > α-o-4 (ph) > α-o-4 (non-ph) > β-o-4 (ph) > β-1 (non-ph) > β-o-4 (non-ph) > biphenyl (ph) > biphenyl (nonph). Model compounds studies have shown that groups containing phenolic structures are considerably more reactive than groups without, showing increased yields of both char (from polycondensation) and guaiacol (from β-ether cleavage) [82]. A proposed decomposition pathway for lignin is presented in Figure 7. This mechanism supposes two primary pathways for carbonization. The first stems from lignin clusters of 6 or more rings linked by C-C bonds. These clusters are too heavy to evaporate so, they will remain as a soil or will form part of the liquid intermediate. They are presumed to cross-link in the liquid intermediate (increasing their molecular weight) [83-86], and polycondense via reaction steps 1 and 2 respectively. Smaller clusters form a melt phase upon heating (step 3), and the monomers are likely to be evaporated immediately. Heavier compounds cross link and poly condensation again gives rise to the char phase (6 and 7). This reaction pathway competes with depolymerization and thermal ejection (4) which gives rise to oligomers and decompose further (5) to give monomeric units. Reactions 2 and 7 are hypothesized to occur via reaction of the propanol chain and methoxy groups, leaving the aromatic ring intact [44]. 15

38 Lignin monomers Lignin 5 Lignin oligomers Clusters 1-5 aromatic rings O Cluster 6> aromatic rings Lignin liquid intermediate Lignin solid Residue (large 6 Cross-linked Char+ CH 3OH Lignin formaldehyde Char+ CH 3OH + formaldehyde clusters) Figure 7. Multistep lumped mechanism for the pyrolysis of lignin that will be evaluated in this proposal. Adapted from Zhou [87]. Pyrolysis of lignin in a fluidized bed converts approximately one quarter of the lignin into monomers and one quarter into oligomers with much of the balance carbonized [88]. In contrast, primary reaction studies conducted in vacuum mesh reactors show that almost 80 % of the lignin is converted into oligomers that form a liquid intermediate. These oligomers are thermally ejected by the bubbles formed in the liquid [89]. This indicates that despite the low vapor residence time in the fluidized bed reactor, significant secondary reactions occur. Char formation from lignin is hypothesized to proceed via cross linking and condensation reactions similar to those discussed for cellulose. These include a variety of oxygen mediated condensation reactions such as aldol condensation [80] and radical induced crosslinking [90]. These reactions are expected to occur primarily along the side groups, specifically the methoxy and propanol chains; however, detailed studies of the chars are not available to confirm the structures formed. 16

39 1.4 Strategies for the activation and functionalization of carbonaceous materials The adsorptive properties of char are highly dependent on the physical and chemical properties of the surface. The development of surface area is essential to increase the available binding surface for both physical and chemical adsorption processes. Alteration of the chemistry of the char is necessary when ionic adsorption capacity is desired, such as for the removal of small anions or cations that would not interact strongly with a neutral surface Surface area development (activation) Increasing the surface area of chars is a well understood process used in the production of activated carbon. Activation is typically achieved using either thermal treatments alone or chemical activation. Each method effectively generates porosity within the char system by increasing burnoff of the residual char. The nature of this porosity is strongly linked to the activation procedures employed [91]. Thermal (physical) activation: Thermal activation of carbon is a well understood industrial process, used to produce a range of mesoporous carbons for market. This process is typically employed as a two-step procedure, where biomass is first carbonized (pyrolyzed), and then subjected to activation. Here the carbonaceous material is heated in an environment containing weak oxidizing agents, typically carbon dioxide or steam to expand internal pore structures [91]. Because the activation process relies on carbon gasification to generate the pore structure a significant fraction of the original carbon material is lost. For industrial carbons, surface area and pore volume are typically maximized between 40 and 60% burn off [91]. 17

40 For both CO2 and steam the rate of reaction with chars is extremely low, even at the activation temperatures typically used, 800 o o C [91]. Because the reaction is heavily limited by the kinetics, gases can diffuse throughout the material prior to reaction. This allows the gasification to occur uniformly throughout the material and significantly improves the quantity and distribution of pores [91]. Chemical activation: Chemical activation typically requires lower temperatures than used for thermal activation processes. The process relies on the catalytic effect of a variety of acid and base salts, including alkalis ZnCl2 and H3PO4, during the initial carbonization process to facilitate primarily micropore development [91-93]. While this method does offer the advantage of being a single step procedure, and requires lower temperatures, a significant quantity of activating agent, up to 1:1 by weight, is needed. These materials must be washed from the final carbon, adding several more processing and purification steps to production [91] Surface functionalization by Oxidation The oxidation of char is known to have a dramatic effect on the application of these materials as adsorbents [29-33, 94]. The presence of oxygenated functional groups on the surface, which form slowly over time when exposed to atmospheric conditions [95], could strongly impact properties when used as a soil amendment [16], the primary effect being the development of acidic oxygen groups at low temperatures with aggressive oxidizing agents [29-31, ], and pore development when using weak oxidizing agents at high temperatures [91]. Understanding the various mechanisms of oxidation based on the temperature and oxidizing agent is important for 18

41 the development of post-pyrolysis treatment methods for the production of chars suitable for soil application and the removal of both non polar and cationic compounds for aqueous solutions. While numerous options, such as nitric acid, peroxide, and dissolved ozone due exist for liquid phase oxidation of solids, for simplicity only gas phase reactions are discussed here. The reactions of carbon with air/oxygen are the primary driver for both combustion and gasification reactions. When the temperature is maintained below the auto ignition point, typically near 370 o C for condensed carbons, a variety of oxygenated groups can be formed [97, 101]. These groups include carboxylic acids, lactone groups, and hydroxyls. Each group is temperature sensitive; carboxyl groups and hydroxyl groups begin to devolve at temperatures as low as low as 300 o C, whereas lactones are somewhat more stable, but typically begin to degrade by 500 o C. Degradation by air at elevated temperatures has been found to favor aliphatic and poorly condensed carbons, with degradation times being far shorter than for highly aromatic carbon [102]. Ozonation of activated carbons or chars is a relatively new concept for industrial application purpose, including development of acidic functional groups [29-31, 94]. The results in the literature indicate a strong formation of carboxyl groups on the surface as well as the formation of lactone and carbonyl groups [31, 95, 96]. However, the effect of the structure of carbonaceous materials on its oxidability is still poorly known [96]. Ozone preferentially oxidized carbons at alkene bond sites [ ]. 19

42 Other surface functionalization strategies Aside from oxidation, several additional strategies have been employed to functionalize chars. These methods have been employed to create acidic or basic functional groups. While only gas phase oxidation was discussed above, these same functionalities can be obtained in the liquid phase using oxidizing agents such as H2O2, KMnO4, and HNO3[ ]. Wet and gas phase oxidation typically results in the formation of weak acid sites such as lactone and carboxyl groups that can exchange ably bind anions. Other methods of adding surface acidity to chars, also exist, such as sulfonation. Here the char is exposed to fuming sulfuric acid to produce sulfonated groups on the surface [109], creating strong Brønsted acid sites. The creation of basic exchange sites is most commonly achieved by amine addition [ ]. Effective addition of amines often requires preliminary oxidation to generate sufficiently reactive sites for grafting [114]. Following this amine generation can be achieved by a variety of techniques, including contacting with ammonia gas, or reaction with amine containing precursors such as 3 chloroproylamine, tris(2-aminoethyl)amine, or polyethylenimine [ ]. The basic strength of the amine can be altered by the degree of hydrogenation, with primary amines being only weakly basic, and quaternary amines showing strong base properties [110] In addition to chemical modification of chars, properties can be tuned by the inclusion of nanoparticles [118], a concept equivalent to the use of activated carbon as a catalyst support. A modification of this approach involves pre-loading the biomass precursor with the desired mineral salts to produce chars functionalized with metal oxide nanoparticles [ ]. Studies examining 20

43 chars made from high magnesium feedstock have demonstrated that the mineral sites formed during pyrolysis acted as the primary site for phosphate adsorption [34, 35]. Addition of Mg salts prior to pyrolysis has also been found to generate similar functionality [122, 123]. Other groups have examined doping with FeCl3 prior to pyrolysis, creating iron particle bearing magnetic chars [118]. An excellent review of these methods can be found elsewhere [118] Characterization of Carbonaceous Materials A variety of standardized methods exist to evaluate the properties of carbon materials as they relate to the desired end use. Though these methods do not typically provide detailed chemical and microstructure information, they are exceptionally useful for classifying the material, which can vary widely depending on feedstock, processing conditions and any secondary treatments. The analytics required vary based on the desired end use, as do the desired properties. Testing for fuel use: For carbons selected for fuel use, analysis follows well established procedures for the analysis of coals. The primary concerns for this use include the higher and lower heating value of the char, the volatile matter fraction, the ash faction and composition and the friability. High heating values are desired to obtain the greatest quantity of thermal energy for a given mass of fuel. The volatile matter content strongly affects the firing behavior of the material and should fall within the design specifications. The ash fraction impacts both firing behavior and slagging, and can also influence down-stream heat exchange equipment. The friability of the material impacts both material handling procedures and grinding costs when a powdered fuel is required. Procedures for the analysis of coal and in some cases chars are well documented by ASTM with several methods regularly updated. Some of the most common methods are given in Table 1. 21

44 Table 1. Standard test methods for coal that can be used for char Property Method Description CHN Analysis ASTM D High temperature combustion with IR detection of H2O, CO2 and NOx Sulfur Analysis ASTM D High temperature combustion with IR detection of SO2. Sample analysis is independent of CHN analysis Ultimate ASTM D Reference of secondary methods for the determination Analysis Proximate Analysis ASTM D of CHNS(O) and moisture Thermogravimetric Analysis under defined heating conditions. 107±3 o C for moisture, 950±20 o C for Volatile carbon, 750±15 under air or oxygen for Ash. Fixed carbon by difference Ash Analysis ASTM D Mixed Acid Digestion (HCl, HNO3and HF) followed by solution analysis by Inductively Coupled Atomic Emission Spectroscopy. Heating Value ASTM D5865 Combustion in submerged bomb calorimeter Friability ASTM D Drop Shatter Test method Friability (2) ASTM D Tumbler test method Grindability ASTM D409/D409M-12 Hardgrove grinding test at 60 revolutions Agricultural use: Chars considered for use in agricultural applications require a more diversified range of characterization techniques. In addition to the methods discussed for fuel analysis several techniques and methods utilized for the evaluation of soils are required to obtain a proper understanding of the product. These tests include analysis of the organic carbon fraction, mineral nitrogen content, water holding capacity, ph in solution, electrical conductivity, hydrophobicity of the surface, surface area, and toxicological evaluation [18]. Because biochar is intended for soil application with the aim to increase soil fertility and crop yield, germination tests with various crops in amended and untreated trials are needed to evaluate performance [124]. The volatile and fixed carbon are important for estimating the stability of the char in soils and the ash fraction and analysis yields valuable information on any potentially toxic metals concentrated in the ash. Char typically contains a small quantity of oil condensed on the surface, it is important to analysis this fraction to determine if any potentially toxic compounds are present. Polycyclic aromatic 22

45 hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs), dioxins and furans are oxygenated ring compounds, often chlorinated, that are potentially highly toxic. Quantities of even a few parts per trillion (ng/kg) can cause negative environmental effects, so the accurate quantification of these compounds is critical for any potential soil application [125]. Standardization of these characterization methods is an ongoing process as the biochar industry continues to grow and develop. One of the most complete and well documented standards currently available is that of the International Biochar Initiative (IBI). For a material to be certified by IBI an array of tests must be performed and results reported for both test categories A and B, given in Table 2 and 3. These tests pertain to general physical characteristics of the char and the toxicological evolution respectively. Additional tests may be performed and reported, as given in table 3. The test given here pertain to more detailed properties related to soil quality, including mineral N and total P and K, surface area, and volatile matter. 23

46 Table 2. Test Category A: Basic Biochar Utility Properties Required for All Biochars (summarized from IBI requirements Table 1). Requirement Criteria Units Test Method Moisture Declaration %, total dry mass ASTM D (Specify measurement date with respect to time from production) Organic Carbon (Corg) Class 1: 60% Class 2: 30% Class 3: 10% H:Corg 0.7 (max) Molar ratio %, total dry mass Total C and H by dry combustion-ir detection Inorganic C analysis by determination of CO2-C content with 1N HCl, from ASTM D Organic carbon calculated by difference Total Ash Declaration %, total dry mass ASTM D Total Nitrogen Declaration %, total dry mass Dry combustion-ir detection (same as C & H) ph Declaration ph Procedure outlined in section 4.11 (ph) and 4.10 (EC) of Test Methods for the Electrical Conductivity Liming (if Above ph 7) Particle size Distribution Declaration ds/m Examination of Composting and Compost [126] Dilutions and sample equilibration methods from Rajkovich et al. [127] should be used Declaration % CaCO3 Association of Analytical Communities mehtod AOAC Titrate on as received samples, % CaCO3 reported on dry basis Declaration % <0.5mm, 0.5-1mm 1-2mm, 2-4mm, 4-8mm, 8-16mm, 16-25mm, 25-50mm & 50mm Progressive dry sieving with 50mm, 25mm, 16mm, 8mm, 4mm, 2mm 1mm and 0.5mm sieves. 24

47 Table 3. Test Category B: Biochar Toxicant Reporting-Required for All Feedstocks (Summarized from IBI requirements Table 2) Requirement Criteria Units Test Method Germination Screening using 3 species, OECD Inhibition Assay Terrestrial Plants Growth Test no. 208) Polycyclic Aromatic mg/kg dry US EPA method 8275A Hydrocarbons (PAHs) Dioxin/Furan (PCDD/Fs) ng/kg US EPA method 8290A Polychlorinated mg/kg dry US EPA method 8275A Biphenyls (PCBs) Arsenic mg/kg dry Procedures outline in section 4.5 of Test Cadmium mg/kg dry Methods for the Examination of Chromium mg/kg dry Composting and Compost [126] Cobalt mg/kg dry Copper mg/kg dry Mercury from US EPA method 7471B Lead mg/kg dry Mercury 1-17 mg/kg dry Molybdenum 5-20 mg/kg dry Nickel mg/kg dry Selenium 1-36 mg/kg dry Zinc mg/kg dry Boron Declaration mg/kg dry Sodium Declaration mg/kg dry Chlorine Declaration mg/kg dry Table 4 shows some of the optimal properties the IBI recommends that bio-char producers report on a voluntary basis. 25

48 Table 4. Test Category C: Biochar Advanced Analysis and Soil Enhancement Properties-Optional for All Biochars (Summarized from IBI requirements, Table 3) Requirement Criteria Unit Test Method Mineral Nitrogen (ammonium and nitrate) Total Phosphorous and Potassium Declaration mg/kg, dry wt Declaration % of total mass, dry wt 2M KCl extraction with spectrophotometry detection. [128] Modified dry ashing followed by ICP [129] Available P Declaration Mg/kg 2% formic acid extraction followed by spectrophotometry [130] Volatile matter Declaration % of total mass, dry wt ASTM D Total Surface Declaration m 2 /g ASTM D Stand test method for Area Carbon black by nitrogen adsorption. External Surface Declaration m 2 /g Area *Total K is sufficiently equivalent to available K for the purpose of this characterization Though not explicitly discussed in the IBI requirements the cation exchange capacity (CEC) is an important consideration for soil applications. This property is directly related to the char s capacity to hold and exchange positively charged mineral ions such as K and NH4 +. The two most common methods of measuring this property are based on the exchange of ammonium acetate and the exchange of barium chloride [131, 132]. The barium chloride method utilizes a forced exchange with magnesium by adding MgSO4 to the BaCl2 saturated material. This causes BaSO4 to precipitate allowing magnesium to exchange in its place. While this method is robust, and allows for measurement of the easily detectable magnesium ion, barium is a toxic compound requiring special disposal. This method also must carefully control ph, as this strongly affects results and the BaCl2 solution does not effectively buffer the solution. Both of these issues are resolved when using ammonium acetate, which buffers near ph 7, however this is a direct measurement technique 26

49 and measurement of the ammonium ion can be less precise than Mg and will not allow measurement of CEC at the native ph of the soil [133]. The CEC is directly related to the oxygenated group profile of the chars. One of the most common methods for quantifying these groups is the titration method of Boehm [97]. This method uses bases of varying strength to selectively react functional groups on the carbon surface, distinguishing the groups as phenolic like, lactone like, and carboxyl like based on relative pka values. As demonstrated by Fidel et al. [134] and Tsechansky and Graber [135] this method can suffer from interferences when applied to char, due to leaching of soluble organic matter. To overcome this contamination Fidel et al. [134] utilized a BaCl2 precipitation and filtration prior to measurement of the Boehm solution while Tsechansky and Graber utilized a successive acid and base wash to remove soluble mater prior to analysis [135]. Use as Adsorbents: Characterization of chars and activated carbon for adsorption processes utilize many of the methods already discussed. Particle size and other physical properties, as well as chemical composition and physicochemical properties, including proximate analysis, ash content, ignition points, ph in solution and potential toxic compounds are all important variables. In addition adsorption isotherms for standard compounds such as phenol, iodine and methylene blue are often determined [91, 136, 137]. Because the adsorption process relies on surface attraction and retention, surface area analysis is critical for these materials [91]. Analysis by nitrogen adsorption is a well-established method for activated carbon, relying on the physical adsorption of nitrogen gas to the walls of particles at liquid nitrogen temperature. Both the surface area and pore size distribution can be determined by incrementally increasing the partial pressure of nitrogen in 27

50 the system and measuring the quantity of gas adsorbed. These data are then translated to a surface area by BET analysis (Brunauer, Emmett and Teller) or a number of other isotherm interpretation methods, and to pore size distributions by BJH (Barrett-Joyner-Halenda) [138] or DFT based methods [139]. While this method provides excellent results for activated carbons due to their high mesopore volume (pore diameters of 2-50 nm) it often fails to provide accurate results for nonactivated carbons such as biochar, which is typically highly microporous (pore volume < 2 nm). Because of this, equilibration of nitrogen in these pores at an analysis temperature of C (77K) requires exceptionally long periods of time [91]. To more accurately analyze these materials CO2 is often used, with the analysis temperature controlled by a water/ice bath at 0 C ( K). This allows more rapid diffusion and equilibration within the micropore space, but is limited only to micropore analysis in most systems which operate with a maximum pressure of 760 torr. This is due high saturation pressure of CO2 at 0 o C (26141 torr) which allows only a low partial pressure of 0.03 to be achieved. 1.6 Spectroscopic analyses for the study of carbonaceous materials The end-use characterization techniques discussed previously are highly valuable in determining the applicability of chars for various tasks and processes, but do not provide the necessary detail for a comprehensive understanding of the underlying carbon structureto detail this chemistry a number of spectroscopic techniques are also available. These techniques include FT-IR, FT- Raman, X-ray Photoelectron Spectroscopy (XPS) and Nuclear Magnetic Resonance (NMR) spectroscopy. 28

51 1.6.1 XPS: XPS is a surface sensitive, quantitative analytical technique, capable of identifying elements and compounds within the first several nanometers of the surface. This technique has been applied a diverse array of carbons, ranging from amorphous and diamond like thin films [ ], to graphite [144, 145], graphene [146], carbon nanotubes [ ] and chars [102, 150, 151]. Analysis is performed by bombarding the surface with x-rays, causing electron emission from both the valence and core levels of excited atoms. The energy of the emitted electrons is that of the incident photon minus the binding energy of each emitted electron. The Handbook of X-ray Photoelectron Spectroscopy [152] is an excellent resource to begin evaluation of acquired spectra. In addition to the elemental composition of materials, XPS also informs on the chemical binding state of materials through shifts in the observed binding energy. These shifts are typically too weak to result in independent peak structures resulting in core level spectra for elements such as carbon that are heavily convoluted by multiple oxidation states and require deconvolution of the curve to interpret. A simple deconvolution for oxygen containing carbons uses Gaussian or 10% Lorentzian line shape with the primary carbon-carbon peak at ev, and with hydroxyl/ether, carbonyl and carboxylic groups shifted approximately 1.5, 3, and 4.5 ev higher, respectively [153, 154]. These methods commonly employ a full width at half maximum (FWHM) of 2 ev, resulting in substantial overlap of the deconvolution peaks. Analysis is confounded further due to non-ideal behavior that can occur for both poorly conducting samples [ ], where charge build up distorts the spectra, and highly conductive samples [144, 146] where asymmetric line shapes can develop. The difficulties of fitting these curves is apparent 29

52 where comparing the oxygen concentration determined from the C 1s spectra to that determined by the independent O 1s peak, which seldom match well Infrared Spectroscopy: Infrared (IR) spectroscopy uses infrared light to excite a range of molecular vibrations. Vibrational modes are measured by adsorption or emission at a given wavelength. Only certain vibrations are IR active, specifically those that result in a change in the dipole moment of the molecule. While IR spectra can be obtained over a wide range of wavelengths, the range most pertinent to carbon uses wavelengths between 2.5 and 25 um ( cm -1 ). Vibrational modes active within this region result in characteristic peaks for many important chemical groups, including: aromatic carbons, carbonyl groups, ether groups and hydroxyl groups [67, ], providing a powerful tool for the characterization of chars. These spectra can be recorded in minutes, and with the large volume of literature available regarding peak assignments, can often be readily assigned. The drawback is that the vibrational responses are not directly quantitative. While some estimates can be made with calibration, more accurate tools are available Raman Spectroscopy FT-Raman uses a monochromatic (single wavelength) emission source to measure inelastic scattering due to molecular interactions with the source wavelength. Scattering occurs when an incident photon strikes a molecule, causing an excitation to a virtual state [161]. The molecule relaxes back to the ground state and the scattered photon contains the same energy as the incident. Though the vast majority of light scattered is elastic (Rayleigh scattering) a small quantity excites 30

53 various vibrational modes causing a loss (Stokes scattering) or gain (Anti-Stokes scattering) in the energy of scattered light. This occurs when the molecule relaxes back from a higher vibrational state, or was excited to a higher vibrational state [161]. Potential interference can occur by fluorescence, which occurs when the molecule is excited sufficiently to reach a real electronic excited state, with relaxation back from this new excited state causing broad background intensity. By filtering the incident frequency from the detected light, a Raman signal can be obtained. As with IR spectroscopy, the energy shifts associated with the inelastic scattering are specific to chemical bonds and molecule symmetry. Raman spectroscopy is however complimentary to IR in that, Raman active modes are not always IR active and IR modes are not necessarily Raman active. Use of both methods provides additional details regarding sample composition. Though not specific to char, the work of Ferrari [ ] provides an excellent primer on current understanding of the analysis of various carbon forms by Raman spectrometry. Raman spectroscopy has been extensively used in the analysis of carbonaceous materials. These methods are often based on the original peak assignments derived for on graphitic structures by Tuinstra and Koenig [165] in These include the graphitic G-band, located at approximately 1575 cm -1, which is the primary Raman active mode for highly ordered graphite, and a second mode, near 1350 cm -1, the D-band, resolved when regions near grain boundaries were analyzed [165]. [166]. Unfortunately these bands alone are not sufficient to capture the full complexity of amorphous carbons [164, ]. Several additional peaks are need to improve the fit of shoulders not typically represented in spectra from graphitic materials, however the assignment of these additional bands remains largely tentative [168, 169]. 31

54 1.6.4 NMR: NMR allows for the analysis of various elements that have either or both an odd number electrons or atomic mass. When these nuclei are aligned in a magnetic field they can absorb energy and excite from a ground state to a higher energy state. When the nuclei relax, energy is emitted at a specific wavelength determined by the element and bonding characteristics associated with each nucleus in the sample. Measurement and evaluation of the emitted energy gives the NMR spectrum. Data acquisition and analysis of solid state samples by NMR is considerably more time consuming and difficult than for liquid samples. While a powerful tool for quantification, a fundamental limitation has been the need to direct polarize (DP) the carbon atoms to achieve equal polarization within the aromatic systems. The longitudinal relaxation (T1) of the polarized carbon back to original distribution requires substantial recycle delays between scans, on the order of one to several minutes per scan [171, 172]. Good signal intensity can be obtained more with substantially shorter delays using cross polarization, where polarization is achieved through coupling of carbons to adjacent hydrogens due to the more rapid relaxation of hydrogen, but tertiary and quaternary carbons do not achieve the same degree of polarization as primary or secondary carbons, resulting in only qualitative spectra [172]. This limitation was recently overcome by Johnson and Schmit-Rohr [173] through the use of multiple CP passes which successively build the polarization within the internal aromatic structure, resulting in 95% or better signal intensity from all carbons, even in low hydrogen samples. 32

55 In addition to quantification, NMR spectroscopy offers a unique method to analyze the distance between two dissimilar atoms within a compound through rotational-echo, double resonance (REDOR) type experiments [174]. This method was successfully used by Mao and Schmidt Rohr to assess the aromatic region of humic material and chars [172]. This same technique has also been used to estimate average aromatic structures of slow, fast and gasification chars [171]. A second method proposed to analyze cluster size, uses the shift of 13 C labeled benzene sorbed on the surface [175]. While not directly quantitative, when calibrated against the shifts for known compounds, the results for fast pyrolysis char are in good agreement with those reported by dephasing [176] Density Functional Theory Calculations Density functional theory (DFT) is an exact solution of the Schrodinger equation to identify of the electron configuration of a many body system, though the necessary use of various non exact exchange and correlation functionals and basis sets to solve many electron problems results in only an approximation of the exact solution. DFT calculations have become an important part of research, allowing scientists to probe the stability of ground states as well as well as transition states of molecules and reactions [177]. Combined with transition state theory, these calculations can provide information of the thermodynamics and kinetics of reaction systems, allowing proposed mechanism to be evaluated [177, 178]. A growing body of work has been performed on the reaction of various carbon structures at elevated temperatures with oxidants, including air and CO [ ]. Recent work by Gonzalez et al. [184] has investigated potential structures of calcium oxides along the surface of carbon structures. The application of DFT calculations to pyrolysis reactions is a new field; however, work by Mayes et al. [178]has shown the potential for 33

56 application of these calculations to probing reaction pathways of cellulose thermochemical reactions. DFT theory also has great promise for use in validating experimental techniques. Several important chemical properties can be calculated from the optimized electronic state of compounds including IR and Raman spectra, core binding energies and NMR shielding tensors. Each of these methods is subject to some deviation from experimental results, however these can be minimized by the proper selection of basis sets [185] and in the case of IR and Raman, empirical correction factors [ ]. Several studies have utilized DFT calculations to simulate the effects of structures that could otherwise not be isolated or to identify important, unknown vibrational modes [189, 190]. Similarly, the NMR shielding tensors can be calculated either for unknown compounds or to assign unknown peaks. XPS simulation from DFT is typically more involved and can be achieved by determination the core binding energies of each atom in a system. Because XPS results in the emission of an electron from the system, the electronic state of the molecule can be expected to change. Based on this, the core binding energies can be analyzed by making one of three assumptions: (1) the initial state is approximately representative of the final electron configuration (Koopman s theorem) [191] (2) final state approximations where the desired core-hole is isolated and the binding energy determined assuming full screening of the hole and (3) a transition state approximation utilizes partial orbital occupations to describe the excitation process [192]. While the final and transition state assumptions are considerably more accurate, they are also more expensive computationally, requiring a solution for the electronic configuration with the core-hole isolated at each individual 34

57 atom. By contrast use of the initial state approximation allows each atom to be assessed simultaneously, has been shown to provide a reasonable approximation for carbon systems when basis set appropriate correction factors are applied [193] Model of Carbonaceous Materials Attempts to model non-graphitizing carbons date back to the first attempts by Franklin in the 1950 s [194]. This original model visualized amorphous carbon as series of stacked nanocrystalline graphite regions connected by irregular carbon structures (see Figure 8A). Similar assumptions have been made to visualize the development of pore structure in activated carbon through a so called falling card model first proposed by Dahn et al. [195] where pores are constructed of randomly arranged graphene sheets. The use of planar, graphene sheet like, models have also been employed to explain dephasing results from NMR studies of chars and identify overall cluster sizes [171, 196]. Several simulations have also been carried out using a variety of computational packages to generate 3D representations of coal [197] and nano-porous carbons [198] using planar, hexagonal carbon regions as the basic sub-units. 35

58 Figure 8. Representations of amorphous carbon using graphene sheets (A) nanocrystalline model of amorphous carbon proposed by Franklin [195], reproduced by permission of the Royal Society, and (B) falling card model proposed by Dahn et al. [195], reprinted with permission of Elsevier. Despite the tendency to model biochars and activated carbons as simple planar structures, more complicated shapes have been observed. High resolution imaging techniques have highlighted the warped nature of carbon clusters in activated carbons, and the inclusion of non-hexagonal ring systems in the structure of these materials [199, 200]. Figure 9A shows a schematic representation of the curvature identified in activated carbon regions by Harris et al. [199]. In addition, several oxygenated groups are known to be stable at temperatures between 300 C and 700 C [201, 202] and add to the complexity of the structure. Figure 1C shows the collapsed 2D model of coal proposed by Shinn [203] which depicts the complexity of oxygenated groups and defects within the carbon matrix. These added complexities must be accounted for in models of the 3D structure to accurately determine morphology. 36

59 Figure 9. Non-graphitic representation of amorphous carbon structures (B) Illustration of the curved carbon fragments containing cyclopentane-, cycloheptane- and cyclohexane-ring systems as identified by Harris et al. [199] IOP Publishing. Reproduced with permission. All rights reserved. (C) 2D chemical representation of coal structure, as proposed by Shinn [203], reprinted with permission from Elsevier Dissertation Objectives The overall objective of this dissertation is to improve spectroscopic methods (Raman, XPS, NMR) for char characterization and to enhance our understanding on how feedstock composition and pyrolysis conditions affect the chemical structure of chars and their oxidability. To achieve this object three primary tasks have been investigated: (1) Improvement of spectroscopic characterization and interpretation of chars, specifically by Raman, XPS, and NMR spectroscopy. (2) Analysis of the effect of feedstock and pyrolysis temperature on the chemical structure of biochar 37

60 (3) Evaluate the effect of ozone oxidation on the surface chemistry of pyrolysis chars 1.10 Methodology To most clearly present this work, the dissertation has been broken into three sections as detailed in figure 10. These sections are presented in a flow chart detailing where the results fit within the material selection and design process. Section 1: Improvement of deconvolution and interpretation of XPS and Raman spectra for chars supported by DFT calculations and application of a rapid quantitative 13 C NMR technique for estimation of cluster size. Section 2: Characterization of chars produced from biomass components (cellulose, hemicellulose and lignin) and various feedstocks across a thermoseries from o C. The effect of feedstock and temperature will be evaluated via chemical and physical characterization means to determine the char properties. Section 3: The effects of ozone oxidation on the surface chemistry of chars produced from Douglas Fir wood and bark are examined. These oxidation behaviors are compared to those of a commercial activated carbon. 38

61 Figure 10. Flow diagram highlighting work conducted during this program 1.11 Scientific Contributions (1) A new series of band assignments has been proposed for the deconvolution of Raman spectra of amorphous carbon. These assignments are based of computational simulations and consider the effects of non-hexagonal ring systems, heteroatom defects and out of plan deformation of the primary carbon clusters. (2) A modified algorithm has been proposed for the sequential interpretation of the O1s and C1s spectrum from X-ray photoelectron spectroscopy. This method constrains the deconvolution of the C1s spectrum based on analysis of the O1s spectrum and the physical limits of associated C-O bonds. This method greatly improves estimated C:O ratios and allows for the estimation of functional group distributions, as well as improved assignments of defect regions. 39

62 (3) A rapid quantitative cross-polarization technique has been coupled with long range dipolar dephasing to provide accurate cluster size information for amorphous carbons by NMR that cannot be accurately evaluated by X-ray diffraction. (4) The new analytical methods developed were used to study the differences in chemical structure of chars from primary biomass constituents, cellulose, hemicellulose and lignin, produced at temperatures between 300 and 700 o C. (5) The effect of ozone oxidation on the surface chemistry of activated carbon and two biomass pyrolysis chars has been evaluated, revealing that lactone group formation is dependent on reaction temperature. Also found was that carboxylic acid groups readily formed on the surface and were the primary contributors to improved cation exchange capacity Publications 1. Smith MW, Dallmeyer I, Johnson TJ, Brauer CS, McEwen J-S, Espinal JF, Garcia-Perez M. Structural analysis of char by Raman spectroscopy: Improving band assignments through computational calculations from first principles. Carbon. 2016;100: Smith M, Ha S, Amonette JE, Dallmeyer I, Garcia-Perez M. Enhancing cation exchange capacity of chars through ozonation. Biomass and Bioenergy. 2015;81: Wei L, Liang S, Guho NM, Hanson AJ, Smith MW, Garcia-Perez M, et al. Production and characterization of bio-oil and biochar from the pyrolysis of residual bacterial biomass from a polyhydroxyalkanoate production process. Journal of Analytical and Applied Pyrolysis. 2015;115:

63 Submitted 4. Smith MW, Scudiero L, Espinal JF, McEwen J-S, Garcia-Perez M. Improving the Deconvolution and Interpretation of XPS Spectra from Chars by ab Initio Calculations. Submitted to Carbon, Dallmeyer I. Fish D. Fox SC, Smith MW, Garcia-Perez M. Mesoporous Activated Carbon from Softwood SPORL Lignin and Its Application in Vapor-Phase Mercury Capture. Submitted to Energy & Fuels, In Preparation 6. Smith MW, Helms G, McEwen J-S, Garcia-Perez M. Effect of Pyrolysis Temperature on Cellulose Char Aromatic Cluster Size by Quantitative Multi Cross-Polarization 13C NMR with Long Range Dipolar Dephasing. (Paper to be submitted to Carbon, 2016). 7. Smith MW, Pecha B, Helms G, Scudiero L, Garcia Perez M. Chemical and Morphological Evaluation of Chars Produced from Primary Biomass Constituents: Cellulose, Xylan, and Lignin. (Paper to be submitted to Biomass and Bioenergy 2016). 41

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86 Chapter 2: Structural Analysis of Char by Raman Spectroscopy: Improving Band Assignments through Computational Calculations from First Principles Published in Carbon Volume 100, April 2016 pages Elsevier, Reproduced with Permission Matthew W. Smith 1,4, Ian Dallmeyer 2, Timothy J. Johnson 3, Carolyn S. Brauer 3, Jean-Sabin McEwen 4*, Juan F. Espinal 5 Manuel Garcia-Perez 1* 1 Department of Biological Systems Engineering, Washington State University, Pullman, WA 99164, USA 2 Composite Materials & Engineering Center, Washington State University, Pullman, WA , USA 3 Chemical Physics & Analysis, Pacific Northwest National Laboratory, Richland, WA 99352, USA 4 Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Pullman, WA 99164, USA 5 Insitute of Chemistry, University of Antioquia, Medellin A.A. 1226, Colombia 64

87 Abstract: The complex heterogeneous nature of chars has confounded the complete analysis of the Raman spectra of these materials. The additional shoulders observed on the defect (D)-band and high intensity valley between the D and graphitic (G)-bands represent the primary regions of uncertainty. In this paper the effects of various vacancy and substitution defects in a coronene parent molecule have been systematically analyzed using density functional theory (DFT). The impacts of these defects are best understood in terms of a reduced symmetry as compared to a parent coronene molecule. Based on simulation results, a total of ten potential bands have been assigned between 1000 cm-1 and 1800 cm-1. These bands have been used to deconvolute a thermoseries of cellulose chars produced by pyrolysis at C. The shoulder observed in chars near 1200 cm-1 has been assigned to the symmetric breathing mode of various small polyaromatic hydrocarbons (PAH) as well as rings containing seven or more carbons. Intensity between 1400 cm-1 and 1550 cm-1 results from a range of coupled vibrational modes from various defect structures. The deconvolution of cellulose derived chars shows consistent growth of PAH clusters, loss of oxygen, and development of non-hexagonal ring systems as pyrolysis temperature increased. 65

88 2.1 Introduction Carbonaceous materials from biomass have been studied for a vast array of applications, with use in activated carbon production or as reducing agents in metallurgical applications are the most common [1, 2]. Application of biomass-derived chars to environmental applications has also gained support in the last decade [3]; this interest stems largely from applications in carbon sequestration [4-7], soil fertility [8, 9], and water treatment [10, 11]. In addition, the electrical properties of carbons produced at higher temperatures have spurred the investigation of their use in super capacitors [12], and metal ion batteries [13-15]. Despite the wide range of applications for amorphous, non-graphitizing, carbons, the highly heterogeneous nature of these materials can lead to significant challenges in characterization by spectroscopic techniques such as Raman scattering [16-18]. Non-graphitizing carbons have historically been modeled as small, randomly oriented graphenelike sheets (see Figure 1A) [19]. Such models have been employed in nuclear magnetic resonance (NMR) studies to identify overall cluster sizes for chars produced at low temperature, determining clusters to be small, approximately 8-27 rings for chars derived from pyrolysis and gasification [20, 21]. Despite the tendency to model biochars as simple systems, a complex structure is known to exist. These structures result from the degradation of heterogeneous lignocellulosic materials by an array of solid-gas, solid-liquid and solid phase thermochemical reactions [22-27]. More specifically, NMR studies of biomass pyrolysis chars have identified aliphatic fractions in pyrolysis chars, and to a lesser extent gasification chars [20, 21]. High resolution imaging techniques have highlighted the warped nature of carbon clusters in activated carbons, and the 66

89 inclusion of non-hexagonal ring systems in the structure of these materials [28, 29]. Figure 1B shows a schematic representation of the curvature identified in activated carbon regions by Harris et al. [28]. In addition, several oxygenated groups are known to be stable at temperatures between 300 C and 700 C [30, 31] and add to the complexity of the structure. Figure 1B shows a fullerenelike sheet, proposed by Harris et al. [25] as the basis for structures in activated carbon. Figure 1C shows the collapsed 2D model of coal proposed by Shinn [32] which depicts the complexity of oxygenated groups and defects within the carbon matrix. Several simulations have also been carried out using a variety of computational packages to generate 3D representations of coal [33] and nano-porous carbons [34]. 67

90 Figure 1. Several models exist that attempt to describe the underlying structure of coals and activated carbon, these include: (A) Representation of non-graphitizing carbon as randomly oriented nano-graphitic regions, as hypothesized by Franklin [19], reproduced by permission of the Royal Society. (B) Illustration of the curved nature of carbon fragments containing cyclopentane-, cycloheptane- and cyclohexane-ring systems as identified by Harris et al. [28] IOP Publishing. Reproduced with permission. All rights reserved. (C) A 2D chemical representation of coal structure, as proposed by Shinn [32], reprinted with permission from Elsevier. Analytical methods for the study of chars and activated carbons by Raman spectroscopy are typically based on graphitic structures and can be traced to the seminal work of Tuinstra and Koenig [35] in The authors identified the graphitic G-band, located at approximately 1575 cm -1, as the primary Raman active mode for highly ordered regions of graphite crystals. A second distinct mode, the D-band, near 1350 cm -1, was resolved by the authors when defective 68

91 regions near grain boundaries were analyzed [35]. Further work by Vidano et al. [36] in 1981 determined that the position and intensity of this peak is dependent on the excitation wavelength. This behavior was linked by Thomsen and Reich [37] in 2000 to a double resonance process. Excellent reviews of fundamental Raman active modes of graphitic systems have been completed by Thomsen and Reich [38] and Pimenta et al. [39]. Ferrari and Robertson [40] also reviewed the application of Raman to amorphous and diamond like carbon. In the last decade, significant work has been completed on the characterization of graphene by Raman spectroscopy as reviewed by Ferrari and Basko [41]. The physical description of the origins of the D and G-bands have been a vital guide to understanding the deconvolution and interpretation of graphite-like carbons [38]. While the same deconvolution and analysis methods used for graphite have been applied to amorphous carbons, analysis of the D and G peak is not sufficient to capture the full complexity of the systems [16, 17, 40, 42, 43]. Deconvolution of spectra from char and activated carbon systems often utilizes several additional peaks to improve the fit of shoulders not typically represented in spectra from graphitic materials. These bands have not yet been definitively assigned [16, 43]. Figure 2 shows the application of three deconvolution methods reported in the literature to the Raman spectrum of a cellulose pyrolysis char produced at 400 o C for this study. While several other methods have been reported [16, 44, 45], these methods demonstrate the varying complexity of models that have been employed in the deconvolution of Raman spectra for a variety of carbon systems. 69

92 Figure 2. Application of different deconvolution methods to the Raman spectra of a cellulose pyrolysis char produced at 400 C Fitting methods adapted from (A) Ferrari et al. [40, 42] (B) Hu et al. [43] and (C) Li et al. [17]. Figure 2A shows the simplest deconvolution as described by Ferrari et al. [40, 42]. This method uses two curves to fit data, a broad Gaussian to fit the primary D-band and an asymmetric Briet- Wigner-Fano (BWF) peak is used to represent the G-band. This method is excellent for analysis of well-ordered systems such as graphite, but fails to accurately reproduce the complexity of the cellulose char spectrum. Figure 2B depicts the deconvolution method employed by Hu et al. [43]. This method partially addresses the complex nature of the curve by inclusion of a transpolyacetylene (TPA) peak near 1200 cm -1, and an amorphous region (A-band) near 1500 cm - 70

93 1. The TPA, D and A bands are each modeled using Gaussian type curves while the G-band is modeled using a Lorentzian peak. A final Gaussian peak located approximately 30 cm -1 higher than the G band is added to capture a double resonance breathing mode described by Thomsen and Reich [37, 38]. While this method improves the fit with the experimental spectrum, it still does not demonstrate adequate complexity to fit the low wavenumber region. Moreover, uncertainty remains in the assignment of both the TPA and A bands. Figure 2C shows the deconvolution method employed by Li et al. [17]. In this method four regions are utilized to characterize the material, these include: the shoulder (S), defect (D), valley (V) and graphitic (G) regions. These regions are further subdivided into a total of 9 peaks, represented by: SR, S, SL, D, VR, VL, GR, G, and GL, where L and R subscripts denote left and right respectively. It must be noted that this method was designed for use with Raman spectra collected at 1064 nm: However because the D- band is dispersive with energy, the peak labels shown in Figure 2C are not accurate. The D-band should be red shifted by approximately 50 cm -1 to compensate for variance in the excitation energy of the incident light used [36]. However, the red shift required for the VR and VL bands is unknown. Despite errors in labeling when applied to a spectra collected at 532 nm, this method provides an exceptional fit to the experimental data, however the peak assignments provided are based on results limited by the availability of model surrogate compounds for many of the char structures, leaving uncertainty in the assignments. To better identify potential compounds responsible for spectral intensities in the S and V regions discussed by Li et. al. [17] (or TPA and A as presented by Hu et. al. [43]), spectra from a range disordered carbons structures are required. Here recent advances in computational chemistry can allow for the rapid screening of the Raman spectra of an array of structures that would otherwise 71

94 be difficult or impossible to isolate [46]. Molecular dynamic simulations have already been employed for several model compounds to determine the origins of various vibrational modes, and have demonstrated the capacity of DFT based models to accurately reproduce the experimental spectra of a range small carbon compounds [47], small polycyclic aromatic hydrocarbons (PAH) [48], and modified graphene and graphite [49]. Simpler computational methods have also been applied to large PAHs [50, 51]. In this paper both experimental and calculated Raman spectra from small PAH molecules are used to assist in the deconvolution of Raman spectra from complex carbonaceous materials derived from lingo-cellulosic feedstock processed at low temperatures. The molecules studied were chosen to represent the effects of cluster size, non-hexagonal systems, point defects, alkene groups, and heteroatom substitutions. The new deconvolution method is then used to evaluate the structural evolution of chars produced from Avicel cellulose. Avicel cellulose was chosen to provide a reasonably consistent and widely available initial feedstock, and is expected to produce many of the same spectral features as native biomass after pyrolysis. 2.2 Materials and Methods Model compounds All model compounds were purchased from Sigma Aldrich with a minimum purity of 95% and used as received, these standards include: naphthalene (product# ), pyrene (product# ), perylene (product# P1104), benzo[a]pyrene (product# B1760), benzo[g,h,i]perylene (product# B9009), coronene (product# C84801), and anhydrous tetracarboxylic perylene (product# P11255). All samples, except naphthalene, were mixed at a rate of 5 wt % with 72

95 spectroscopic grade KBr (LOT# BCBD3066V) prior to analysis. Naphthalene, due to its high crystallinity and comparatively low Raman intensities was analyzed neat. KBr mixtures were employed to ease material handling during packing and to minimize any potential heating effects [17] Cellulose pyrolysis chars A series of five chars was produced from avicel cellulose (LOT# BCBG9043V) at final heating temperatures between 400 C and 700 C using a spoon pyrolysis reactor following the method described by Wang et al. [26]. Briefly, the reactor was preheated to the desired temperature and the sample placed in a water-jacketed cooling zone prior to the furnace. The chamber was purged with N2 gas (99%) at approximately 300 ml/min for a minimum of 10 minutes prior to treatment. At the start of the experiment the sample was introduced into the furnace and allowed to react for 30 minutes before withdrawal to the cooling zone. A secondary preheated nitrogen sweep gas, of approximately 550 ml/min was employed in the reactor zone to minimize vapor-char interactions. Samples were allowed to cool to temperatures below 25 C before exposure to air. Sample temperature was monitored continuously by three exposed type-k thermocouples placed within the sample using an ExTech SDL200 temperature meter Experimental FT and Dispersive Raman methods 1064 FT system: To avoid potential fluorescence, all model compounds were analyzed by collecting Fourier transform Raman spectra with an FT-Raman spectrometer using 1064 nm excitation and 4 cm -1 resolution. The FTIR-Raman instrument and parameters have been 73

96 previously described [52, 53]. A Bruker IFS 66v/S spectrometer with a FRA 106 Raman accessory employing a CW Nd:YAG laser was used. The laser has a nominal line at cm -1 (air) absolute frequency, but can have daily variations of ± 0.50 cm -1 [53, 54]. The FRA 106 accessory allows either focused or unfocused laser spot with either 90 - or 180- backscatter light collection. Samples were pressed into standard aluminum discs, and the unfocused mode was used to collect the 180 -backscattered light. Calibration was performed for both the scattered light recording system and the frequency of the Raman excitation laser. To calibrate the interferometer HeNe laser frequency we use a series of five Hg lines known to span the spectral range of interest; these were compared to known NIST (air) values, and the HeNe frequency adjusted such that the mean deviation for all five lines is 0.2 cm -1. The absolute wavelength of the Raman excitation laser was then calibrated using the equivalence of the Stokes and anti-stokes frequency shifts; the Raman Nd:YAG 1064-nm laser wavenumber is set using the Stokes/anti-Stokes bands from a sulfur standard with Raman bands at ±479 cm -1. The excitation frequency was adjusted until the agreement was within ±0.20 cm -1, which is significantly smaller than the inherent Raman laser linewidths of room temperature solid samples. The measured spectra were also corrected for the intensity response of the system [54]. Laser powers of 100 and 300 mw were used to collected spectra from naphthalene and a laser power of 100 mw was used for all other standards. All spectra presented are the average of 100 interferograms. Data were transformed with power phase correction to deliver spectra in the range of +3,600 to +100 cm -1 Stokes shift and ca to -1,100 cm -1 anti-stokes shift. 74

97 532 system: Dispersive Raman spectra were collected for all standards as well as each cellulose pyrolysis char samples using a Horiba LabRAM HR microscope. A 250-mW, 532-nm wavelength laser (Ventus LP 532) operated at 90% of maximum intensity with a 1% transmittance filter was used for visible light analysis at an objective of 50x. The spot size is estimated as an ellipse with a major axis of 25 μm and minor axis of 20 μm for the visible laser, resulting in an average power of 229 W/cm 2 applied to the surface. Duplicate analysis of the initial spot was performed after a five minute cooling period to ensure a consistent signal was obtained. Spectra were collected from a minimum of three separate points on each sample with four scans per replicate. Sharp background peaks were noted for all samples collected on the 532 nm system; these peaks were removed in post processing using a blank scan and the resulting primary peak at 2437 nm as the reference. After correction all spectra were normalized using the maximum intensity of the G- band near 1600 cm -1 as the reference. A boxcar average over 7.5 cm -1 was employed to smooth the final curve. To increase the signal to noise ratio, the corrected spectra from each replicate were then averaged to create a final composite curve for peak analysis Computational methods A series of PAHs were studied to confirm the validity of simulation results against experimental spectra. Simulations were conducted on a range of defective structures based on an initial coronene system. Coronene was selected as the basis for defect studies as it represents the smallest PAH in which single and double point defects can be easily introduced. After constructing and optimizing a coronene system, one or two carbon atoms were removed from the center to create the defect. The system was then brought back to a charge neutral structure through formation of 5-membered 75

98 rings and/or hydrogen additions to create a series of possible point defects. Oxygen and nitrogen substitutions were also used to create defective structures and tests the effects of heteroatom substitution. A series of systems containing oxygenated edge sites were analyzed to determine the effects of recalcitrant oxygen fractions as well as the possible impact of post treatment oxidation, which is known to rapidly alter edge sites upon air exposure [55]. An alkene modified coronene system was studied to examine the potential impact of TPA type compounds on the spectra near 1200 cm -1 [43]. Cyclopentane and cycloheptane based ring systems were examined to isolate the impact of non-hexagonal rings on the final Raman spectra based on the suspected origins of intensity between the D and G-bands [16, 43]. All compounds have been evaluated using most abundant isotopes in the Gaussian 09 rev. B.01 software package [56]. Geometry optimizations and frequency analyses were completed using the Becke three-parameter Lee-Yang-Parr (B3LYP) hybrid functional [57]. Four basis sets were chosen based on the larger study of Cheesemen et al. [47]. These basis sets include a Pople type split valence 6-31G* basis set [58], a Dunning s correlation consistent polarized valence double zeta basis set (cc-pvdz) [59] and two of Dunning s augment correlation consistent basis sets (augcc-pvdz and aug-cc-pvqz) [60]. The simulated spectra at each level were obtained for naphthalene and compared to experimental results. All of the larger systems were evaluated only at the 6-31G* level. Previous investigations using PAHs have demonstrated effective prediction of Raman peak positions with DFT after appropriate scaling [61-63]. Input parameters for each compound studied were constructed using the WebMO platform [64] with a preliminary geometry optimization. For each compound, the singlet state multiplicity was confirmed by comparing the energy of the optimized singlet and triplet states. Following optimization of the geometry and 76

99 force constants at the desired theory level, frequency calculations were performed at the static limit. Raman spectra and vibrational modes are visualized using the WebMO tool [64]. All simulated spectra are visualized using a Lorentzian peak shape with a full width at half maximum (FWHM) of 4 cm -1 for each vibrational mode. For comparison, all spectra were normalized based on the peak of maximum intensity between 1000 and 1800 cm Deconvolution of Dispersive Raman Spectra from Cellulose Char All spectra were analyzed between 900 cm -1 and 2000 cm -1. A linear background correction was employed using the minimum intensity between 900 to 1000 cm -1 and 1800 to 2200 cm -1 as anchor points. These regions bracket the initial and final regions where clear signals from the char spectra are obtained. Deconvolution of the Raman spectra was conducted using the peak fit pro tool in the OriginPro 2015 software package (OriginLab, Northampton, MA). All peaks included in this method utilize a Gaussian profile, except the GL peak which is specified with a Lorentzian profile. Detailed discussion of each peak is provided in section 3.5. In this procedure the D and GL peaks are set based on the local maxima near 1350 and 1600 cm -1, respectively. Peak parameters were initially estimated, with all others fixed near 0 intensity and run for 200 iterations to obtain a reasonable fit. The remaining peaks were then centered based on shoulder locations and the intensities were allowed to vary. The FWHM values were also allowed to vary from cm -1 in this step. Curve fitting was allowed to progress for 20,000 iterations or until tolerance of 1*10-6 achieved. Finally, all peak positions were unlocked and the system allowed to converge until a tolerance of 10-9 was 77

100 achieved. After convergence, if the FWHM of any peak reached 100, the bound was increased to 120 and rerun to allow accurate fits. The method described above was utilized to avoid excessive peak drift or broadening during fitting. However, it should be noted that, due to the complexity of the spectra and the number of peaks utilized, truly unique fits do not exist. Modification of the peak parameters or fitting procedure can result in substantial variance in the deconvolution which will alter interpretation of the results. 2.3 Results and Discussions Selection of basis sets for calculations The effect of basis sets on the accuracy of the calculated Raman spectra for naphthalene was evaluated by comparing the simulated spectra from several different basis sets to the experimental spectra as shown in Figure 3. Each basis set was largely capable of reproducing the primary vibrational modes observed in the experimental results, though variations in predicted peak intensity were observed. Errors in position are largely a result of the B3LYP functional utilized for all calculations [62]. Peak intensity errors were calculated based on the normalized root mean square error of intensities for all peaks with intensities greater than The hydrogen stretching modes above 3000 cm -1 were excluded as these modes are most sensitive to the phase variance between experimental (solid) and simulated (gas) spectra. Each major peak position and the related intensity are reported in Table 1. Also included in are the %NRMS error in position and intensity for each basis set. 78

101 Figure 3. Effect of basis sets on the simulated Raman spectra for naphthalene. The experimental spectrum has been wavelength- and intensity-corrected for instrument response. 79

102 Table 1. Comparison of peak positions and intensities for experimental and unscaled simulated spectra of Naphthalene. Experimental 6-31G* CC-pVDZ Aug-CC-pVDZ Aug-CC-pVDZ ν (cm -1 ) I (arb) ν (cm -1 ) I (arb) ν (cm -1 ) I (arb) ν (cm -1 ) I (arb) ν (cm -1 ) I (arb) ν Error # (%NRMS) I Error $ (%NRMS) ν is frequency and I is relative intensity Data point excluded from NRMS error calculations # Data normalized to experimental peak positions $ Data normalized to most intense peak between 800 cm -1 and 1800 cm -1 for experimental and simulated spectra The results shown in Figure 3 and Table 1 indicate good prediction of the vibrational frequencies for each basis set chosen, but the most accurate frequencies were predicted by the augmented basis 80

103 sets. The 6-31G* basis set was the lowest theory level utilized and required the least CPU time to analyze. Despite this, the most accurate intensities were obtained from this method. The 6-31G* basis set was capable of capturing all major and minor observed vibrational modes with only minimal loss of accuracy, and without specifying significant additional signals, this basis set was deemed acceptable for the purpose of identifying distinctive regions for curve deconvolution. All further simulations were carried using this simple basis set. Errors in peak position for simulated spectra were evaluated by comparison with experimental peaks for naphthalene, pyrene, perylene, benzo[a]pyrene, benzo[g,h,i]perylene, and coronene. Offsets were found to have a generally linear characteristic with calculated peak position, though some deviation was observed at both the low and high wavenumbers. For the frequency range of interest, between 1000 and 2000 cm -1 a single parameter linear correction factor of [63] accounted for the great majority of calculation error when using the 6-31G* basis set Effect of cluster size and symmetry on Raman signal In terms of Raman band intensities for different aromatic species, the relative intensity of the most prominent peak for each compound is summarized in Table 2. It is noted that despite the use of pure naphthalene in the experimental analysis, the peak intensities remained considerably lower than for any of the other PAH study, all of which represent spectra obtained from 5 wt % dilutions in KBr. This result follows a trend highlighted by Li et al. [17] which shows only very low concentrations of sample in a KBr solution, less than 2% for char, are required to achieve 100% signal [17]. While the predicted relative intensities are considerably lower than experimental results for both pyrene and benzo[g,h,i]perylene and higher for coronene, calculated intensities are 81

104 reasonably accurate for perylene, and benzo[a]pyrene. Despite the strong discrepancies in overall intensities, the relative peak profiles within each simulated spectrum closely followed the experimental profile. The differences observed are likely linked to resonant enhancement of various vibrational modes which will be a focus of future work. Table 2. Relative uncorrected maximum intensity of each calculated and experimental Raman spectrum as compared to the uncorrected maximum intensity peak of Naphthalene. Compound Relative maximum intensity (naphthalene = 1) Simulated Experimental Deviation from Experimental (%) Naphthalene (reference) Pyrene Perylene Benzo[a]pyrene Benzo[g,h,i]perylene Coronene Comparison of the experimental and simulated Raman spectra for each PAH is presented in Figure 4. Simulated results (solid lines) have been frequency-corrected based on the single parameter factor given by Hall et al. [63]. All spectra are represented based on relative intensity compared to the most prominent peak between 600 cm -1 and 2000 cm -1 for each spectrum. After correction, frequencies obtained from DFT simulation show good agreement with the experimental results (dashed lines) within this range. While the simulated results generally fit very well with the 82

105 experimental data, an important deviation is noted for coronene: a doublet peak structure is present near 1380 cm -1 in the experimental spectra, while only a singlet is identified in the simulation. This effect may be due to mild asymmetry in the solid-phase sample distorting the idealized D6h symmetry used in the gas-phase model. Three primary vibrations are identified within each PAH, with the location of the primary peaks marked by black lines overlayed on figure 4A. These modes consist of symmetric, or asymmetric breathing modes, Kekulé vibrations, and asymmetric stretching. Each of these modes is visualized in figures 4B-4D respectively for a simple benzene system, though it must be stated that the symmetry will differ and these modes only represent approximate motion. Several peaks within each spectra also develop as a result of mixing of these primary modes. 83

106 Figure 4. (A) Comparison of experimental and predicted Raman spectra for various PAHs with their position correct simulation counterparts. Solid black lines represent simulated results, while dashed red lines represent experimental results. (B) Representation of the A1g symmetric breathing mode for a benzene ring (C) Kekulé type vibration for a benzene ring (D) E2g asymmetric stretch in alkene and aromatic carbons. Position lines denoting the change in location of the A1g, Kekulé and E2g vibrations are provided as black lines spanning the spectra of Naphthalene Coronene. The symmetry labels used in 4B-D are derived from the D6h structure of the benzene. 84

107 A spectrum collected from benzo[g,h,i]perylene using the 532 nm system previously described was compared to the spectrum collected using the 1064 nm system (data not shown). Though the signal to noise decreases dramatically due to fluorescence, all major peaks were found to agree to within 1 cm -1. Because the D-band of larger aromatic systems such as activated carbon and graphite is known to be dispersive with excitation energy, confirming that the larger ring systems do not show dispersive behavior was necessary before applying these results to the analysis of spectra collected under different excitation wavelengths. Table 3 lists the positions, intensities and origins of the most important vibrational modes seen in Figure 4. The frequencies of the simulated modes have again been corrected using a correction factor of From these results two primary modes are clearly observed between 1000 cm -1 and 1410 cm -1 ; the first is the totally symmetric ring breathing A1g mode, depicted in Figure 4b, which appears at 992 cm -1 for benzene [54] at 1000 cm -1 for naphthalene and increases logarithmically with cluster size to 1350 cm -1 (shown as a black line in Figure 4). The second mode is that of Kekulé vibrations for each compound. The position of this mode varies inconsistently in position for each compound but is typically located between 1360 cm -1 and 1410 cm -1. The only exception to this is coronene where, due to a high degree of symmetry, these modes have collapsed into a single normal mode containing both the A1g breathing mode by the center ring and the Kekulé type vibrations in the outer rings. The split modes observed in the experimental spectrum of coronene, however, suggest that the solid phase does not fully retain the idealized D6h symmetry of the gas-phase prediction, giving rise to two slightly shifted modes. An assortment of larger ring structures, studied by Negri et al. [50], show a similar trend of combined A1g and Kekulé type vibrations. These modes, concentrated between 1350 cm -1 and 1250 cm -1, often give rise to two 85

108 distinct peaks within this region. A third peak can also be resolved depending on the structure of the PAH, presenting as a shoulder on the peak nearest 1350 cm -1. The effect of not only cluster size, but symmetry, becomes apparent when examining the spectra of benzo[a]pyrene and benzo[g,h,i]perylene. Naphthalene, pyrene, and perylene each belong to the D2h point group and show distinct splitting of the symmetric breathing and Kekulé vibrational modes. Reducing the symmetry to C2v, as seen for benzo[g,h,i]perylene, results in the formation of two doublet sets near the symmetric breathing and Kekulé modes of perylene. As expected, lowering the symmetry to Cs, as seen in benzo[a]pyrene, shows still further splitting of the vibrational modes, with the Kekulé type vibrations near 1400 cm -1 becoming the most intense. The G-band region shows similar peak splitting as the D-band region, though the position shifts are less pronounced. The observed peak splitting in the G-band is narrow enough to likely be viewed as a broadening factor in highly heterogeneous materials, however distributions of ring breathing and stretching modes in the region of the D-band are sufficient to result in at least two broad peaks even for large polyaromatic systems [50]. The results of this investigation suggest that for solid carbons containing significant quantities of small polycyclic moieties such as pyrene or perylene the region near cm -1 would be expected to broaden and gain intensity due to Kekulé vibrations. These compounds would also be expected to contribute significantly to intensity in the range of cm -1, where ring breathing modes dominate. High concentrations would be expected to result in relatively well defined peaks, while low concentrations should result in minor shoulders attached to a primary D- band (larger polycyclic clusters). 86

109 Table 3. Primary experimental and simulated peak positions and position errors for each major peak (normalized intensity greater than 0.1) of the PAH tested. Vibrational Mode Experimental Simulated ν (cm -1 ) I (arb) νcorrected(cm -1 ) I (arb) F. Br F.Br Naphthalene Kek F. Kek Asm. St F. Br Br Pyrene Kek Asm. St Asm St F. Br Perylene C. Br., Per. F. Br C. Br., Per. Kek Asm. St Br Kek. Bnz., F. Kek. Py Benzo[a] Asm. St. Py Pyrene Asm. St. Bzn Asm St Br Benzo[g,h,i] C. Kek., Per. F. Br NA 0.49 Perylene C. Br., Per. F. Kek Asm. St C. Br., Per. Kek Coronene C. Br., Per. Kek NA C. Br. Per. Asm. St Asm. St F. = Frustrated; Br. = Breathing; Kek. = Kekulé; Asm. =Asymmetric; St. = Stretch; C = Center; Per = Peripheral; Py. = concentrated in pyrene group; Bzn. = concentrated in Benzene group Computational study on the effect of defects and strained ring systems The introduction of several defect structures into the PAH model systems results in a strong degradation of symmetry relative to either the benzene or coronene parent. This loss of symmetry lifts the degeneracies associated with certain irreducible representations of the D6h point group, and results in several formerly Raman-forbidden normal modes becoming allowed; this has 87

110 already been seen for many the modes previously discussed for certain hexagonal polyaromatic systems. The nature of these vibrational modes is largely analogous to the modes present in benzene or coronene and can be interpreted as such. For simplicity, the vibrational modes will be presented based on analogous benzene modes, these include: Breathing modes (A1g), Kekulé vibrations, and asymmetric stretches (E2g). In addition, semi-circular breathing modes are also present and become allowed in these much less symmetric ring systems. Because of the generally amorphous structure of char, our analysis is limited to the evaluation of changes in position and intensity of these generalized modes as a result of structural variations in the carbon systems Computational study on the effect of alkyl side groups In attempts to deconvolute Raman spectra of activated carbons, several authors have assigned TPA type molecules to a characteristic shoulder often observed between 1150 cm -1 and 1200 cm -1 [16, 42-44]. To assess the validity of this assignment the Raman spectra of a deca-penta-ene chain was again calculated at the same B3LYP/6-31G* theory level. The resulting frequency-corrected spectrum is depicted in Figure 5. In addition, the spectra of coronene with one and two buta-diene side chains were also evaluated. Both the lowered symmetry (C1 for one chain and Cs for two chains) and the addition of the chains resulted in a split of the parent E2g asymmetric stretch mode near 1600 cm -1, and the development of a second asymmetric mode near 1650 cm -1 related to asymmetric stretches in the free side chains. The spectra presented in Figure 5 shows breakdown of the D-band when side chains are added, due in part to a loss of degeneracy but also to mixing of the parent A1g breathing mode with carbon stretch modes within the alkyl chain. No significant peak formations near 1150 cm -1 were observed in relation to the buta-di-ene chains. It should be 88

111 noted that the original assignment by Ferrari and Robertson [65] of the TPA peak was based on evaluation of nano-crystalline diamond produced by chemical vapor deposition. A strong presence of TPA is not expected in chars or other carbons processed at temperatures much higher than 400 C as the reaction and decomposition of these groups has been reported to become significant at 420 C [66]. While TPA type groups may contribute to peak intensity near 1150 cm -1, the results suggest that the primary origin of this region is related to different carbon structures. Figure 5. Effect of alkyl chains on the predicted Raman spectra of a coronene-based molecule. 89

112 Isolated effect of non-benzene ring centers Isolation of a cyclopentane centered ring system (a fragment of a C60 fullerene) with a C5 symmetry shows an intense Raman active band containing mixed breathing and Kekulé type vibrations near 1450 cm -1, as seen in figure 6A. No significant vibrations near the typical D-band are observed despite a strong aromatic character, highlighting some of the difficulty in assignment when non-hexagonal systems are present. A secondary peak, comprised of a mixture of breathing and asymmetric stretch vibrations, is observed as a shoulder near 1470 cm -1. The second important peak near 1600 cm -1 is the typical asymmetric stretch common of most sp 2 ordered carbons. These results are highly consistent with published spectra for C60 [67, 68]. Figure 6. (A) Effect of cyclopentane center on position of symmetric breathing mode of the parent coronene molecule in the modeled Raman spectrum (B) Predicted Raman spectra of heptane ring system at the 6-31G level, detailing a symmetric ring breathing mode near 1175 cm-1. 90

113 A cycloheptane centered cluster was also modeled. This system contains only a single mirror plane of symmetry resulting a Cs point group. The overall distribution of Raman active modes is similar to that of benzo[g,h,i]perylene with a C2v grouping. Figure 6B shows the simulated Raman spectrum for the cycloheptane centered system, while the insert highlights the vibrational mode near 1200 cm -1. Vibrations near 1000 cm -1 and 1200 cm -1 are the result of symmetric breathing modes originating in the cycloheptane center. The most intense band, near 1350, represents several vibrational modes containing an assortment of strained Kekulé vibrations in the surrounding hexagonal rings mixed with semi-circular breathing of the heptane center. Mixed breathing and asymmetric stretch vibrations are visible near 1500 cm -1. The asymmetric stretch mode is split into three peaks: a weak peak is observed near 1585 consistent with most PAH and graphitic systems, while the two additional peaks are blue shifted towards 1650 cm -1, consistent with spectra from cyclooctane and cycloheptane containing ring systems as presented by Minaeva et al. [69] and Kudin et al. [49] respectively. These peaks contain asymmetric stretches within the hexagonal rings, while the heptane ring demonstrates semicircular and circular breathing modes respectively for the peaks at 1630 and 1660 cm Effect of single and double point defects To explore the effect of defective ring structures on the Raman spectra of PAH a variety of defects have been modeled using a coronene ring system as a basis. Coronene was chosen for two reasons: First, previous NMR studies reported in the literature have estimated that compounds of this size are representative of the average molecular structure of char [20, 21], and second because the relatively small size allows for rapid computation of many different configurations. The base 91

114 system was modified by inclusion of single and double point defects stabilized by (1) creation of strained ring systems such as pentane and octane rings; (2) introduction of hydrogen at defect points; and (3) generation of ether and/or carbonyl groups and (4) nitrogen inclusion in the coronene structure. Figure 7 shows the computational results of modification of coronene around a single point defect (SPD). These defects greatly reduce the symmetry of the system and show strong alterations of the resulting Raman spectra. The open defect seen in SPD-I results in a Cs symmetry. Vibrations near 1200 cm -1 contain well-formed breathing modes of the intact benzene rings, while the doublet peak near 1370 cm -1 is the result of splitting of the parent A1g vibration of coronene. These peaks result from Kekulé vibrations in two pairs of dissimilar benzene rings within the system. In both cases the center of the molecule maintains motion characteristic of a circular breathing mode analogous to unaltered coronene. Both the SPD-II and SPD-III are highly asymmetric, lacking all but the trivial rotational symmetry. The peak near 1450 cm -1 seen in SPD-II and SPD-III is a result of the mixed breathing mode of cyclopentane rings and Kekulé vibrations in the surrounding hexane rings shown previously in figure 6A. Low frequency modes between 1100 cm -1 and 1200 cm -1 develop in the SPD-II spectra due to a combination of in-plane breathing modes of the center defect and hydrogen wags. A range of asymmetric stretch vibrations were available due to the highly asymmetric defect structure, resulting in split peaks within the G-band region near 1600 cm -1. The same trend was also observed in SPD-III; however, the distortion caused by two adjacent cyclopentane rings resulted in the blue shift of these modes to near 1550 cm -1. Inclusion of nitrogen as a point defect (SPD-N) resulted a C2v system containing many of the same peaks as observed in the SPD-I spectra. This is due to similar changes in the overall configuration of the system. In 92

115 addition a single sharp peak is noted near 1650 cm -1, this peak resulted from strong asymmetric stretches in the two unconstrained nitrogen-containing rings. Figure 7. Effect of various single point defects on the calculated Raman spectra of a coronene based molecule (upper spectra contains a single nitrogen atom substitution denoted in blue). The spectrum of coronene is provided at the bottom of the figure for comparison. Figure 8 shows that the effect of double point defects (DPD) on the Raman spectra of coronene based compounds was even more pronounced than for SPD. Of the defects studied, DPD-II reveals by far the most complex Raman spectrum. This is readily understood in terms of group theory: upon substitution, the coronene D6h point group symmetry is lowered to Cs symmetry in the case of the DPD-I and DPD-III (single mirror plane) systems, and to C1 symmetry in the case of DPD- 93

116 II (trivial rotation only). The lowered symmetry and high variability in bonding throughout the system results in many modes splitting and/or becoming Raman allowed. In all cases, a strong relative enhancement of the asymmetric stretch modes are observed when compared to the parent coronene spectrum. Figure 8. Effect of various DPDs on the calculated Raman spectra of a coronene based molecule (The spectrum of coronene is provided at the bottom of the figure for comparison). The splitting of the coronene A1g mode between 1300 cm -1 and 1400 cm -1 observed for DPD-I is analogous to the splitting described for SPD-I. As in the SPD-I spectrum, a peak near 1200 cm -1 is observed, originating from symmetric breathing of the intact benzene rings. The strong peak near 1530 cm -1 is the result of mild mixing of asymmetric stretching modes of each carbon with 94

117 weak semi-circular breathing from the unaltered 3-ring system. The same primary peaks are observed in DPD-III within the cm -1 region. In contrast, the spectrum for SPD-I did not show any significant mode near 1530 cm -1, the likely cause of this being a sp 3 bonded carbon along the edge site of the defect. From this, it is hypothesized that this mode will be observed primarily for defects near edge sites that maintain sp 2 character throughout. In addition to the peak near 1530 cm -1, two considerably more pronounced E2g peaks near 1650 cm - 1 are present in the DPD-III spectra. These peaks have been observed in simulations by Kudin et al. [49] for a type Stone-Wales defect in graphite (see DPD-III in Figure 7 for a example of this defect). This result is also in agreement with simulated and experimental spectra of cyclooctane ring systems presented by Menivaera et al. [69]. The first peak results from asymmetric stretches in the pentane and hexane rings coupled to a breathing mode present in the octane ring. The second peak results from strong asymmetric vibrations along the pentane-octanepentane edge of the system. Several low to moderate intensity peaks are present between 1000 cm - 1 and 1200 cm -1, these vibrations are a result of circular breathing of the octane ring system and are in good agreement with previous results [69]. Surprisingly, no peaks are observed near 1450 cm -1 in relation to the pentane ring system, but this effect is most likely due to restriction of Kekulé vibrations in the adjacent hexagonal rings. The lack of symmetry and the presence of two sp 3 hybridized carbon in the DPD-II system results in a complex Raman spectrum that contains a number of strong vibrational modes, the strongest being combined semi-circular breathing modes for the pentane and hexane rings near 1400 cm -1, followed by assorted breathing modes and Kekulé vibrations of the three-ring, phenanthrene-like, 95

118 region near 1200 cm -1 and 1340 cm -1 respectively. Breathing modes and asymmetric stretch modes mix to produce a moderately intense band near 1470 cm -1 as well. Numerous asymmetric stretch modes are observed between 1500 cm -1 and 1600 cm -1, with those near 1500 cm -1 resulting from unconstrained carbons surrounding the defect, and modes near 1600 cm -1 originating primarily in the phenathrene-like fragment. The final peak near 1650 cm -1, as with the heptane centered ring system, results from constrained semi-circular breathing of the large ring system mixed with asymmetric stretching in the surrounding rings. In each defect examined, save nitrogen inclusion, a moderate decrease in frequency (red shift) was noted for the primary asymmetric stretch mode. This red shift becomes continually more pronounced as ring deformation increases. A similar effect has been observed in single layer graphene when subjected to out of plane strain [70, 71]. Combined, these results suggest that strained deformations of polycyclic clusters are a primary cause of the commonly observed asymmetry in the G-band of chars and activated carbons Computational study on the effect of oxygenated groups in defects and at edge sites Oxygen substitution at point defects, shown in Figure 9, results in many of the same type of spectral shifts previously discussed. The oxygenated defects do not appear to strongly affect the breathing and Kekulé modes between 1200 and 1400 cm -1 beyond the effects already observed for non-oxygenated defects. The inclusion of oxygen was, however, found to result in significant alterations of the asymmetric stretching modes. A strong red shift in the position of the primary asymmetric stretch mode for SPD-O-I and II as well as DPD-O-II was observed. This shift is the 96

119 result of moderate mixing of asymmetric stretches with the assorted breathing modes in one or more benzene rings. By contrast, neither DPD-O-I or III showed significant red shift of the asymmetric band. The oxygen defect in both systems causes relatively little constriction within the vibrations of the carbon structure, as compared to the other oxygenated defects. Because of this, mixing of the asymmetric and breathing modes was substantially less prevalent, though a distribution of asymmetric modes resulted in a more distributed G-band region for both compounds. The vibrational shifts observed suggest that the presences of oxygen in a deformed PAH results in the same G-band red shift as for non-oxygenated systems, though the degree of the shift appears to be more intense. The spectra reported by Gokus et al. [72] for the treatment of graphene by oxygen plasma resulted in not only the formation of a D-band, but a significant red shifted asymmetry in the G-band, consistent with this hypothesis. Wang et al. [73] also assigned a peak that developed near 1550 cm -1 to oxygenated compounds after electrochemical pretreatment of graphite in HNO3, while simulations by Kudin [49] also identified similar red shifts for oxygenated graphite. 97

120 Figure 9. Effects on the calculated Raman spectra of oxygenated single and double point defects of a coronen-based molecule. The spectrum of coronene is provided at the bottom of the figure for comparison. As seen in Figure 10, the effect of oxygen on the Raman spectrum of PAHs is less pronounced when edge sites are modified rather than inserted as defects, which break the conjugated structure. The accuracy of these calculations was evaluated by comparison of simulated and experimental spectra of tetracarboxylic perylene (excited at 1064 nm). This comparison demonstrates accurate relative intensity reproduction as well as consistent frequencies after correction. The spectral changes observed for edge modified coronene systems can also be partially understood in term of symmetry reduction; while the parent coronene is D6h, the derivatives are each reduced to the Cs 98

121 point group (mirror plane only). As the symmetry is lowered due to substitution, degeneracies are lifted and forbidden modes become allowed. Despite the lowering of all derivatives to the same point group, significantly stronger effects were observed for systems containing double-bonded oxygen attached directly to the aromatic structure as seen with the inclusion of a carbonyl group or a lactone group. While multiple additional peaks were present in each system, only those present in the lactone and carbonyl modified groups achieved significant intensity compared to the parent coronene peaks. This effect appears to be result of charge distribution near the oxygen. Double bonded oxygen systems more strongly affect the electron distribution across the ring systems, constraining movement of the adjacent carbon in breathing modes near 1350 cm -1. Restriction of this carbon motion results in the formation of strong secondary peaks. Such peak splitting is likely to be observed as generalized broadening of the D-band, rather than the development of defined peaks in heterogeneous systems such as char. This effect is substantially less pronounced in both the hydroxyl and carboxyl modified systems, which, by comparison, have only minor effects on the charge distribution of the adjacent carbon. Double bonded oxygen groups (carbonyls) can be easily identified by a distinctive stretch present at 1700 cm -1 (free carbonyl) to 1800 cm -1 (carboxyl/lactone), in line with typical frequencies in organic compounds [74]. 99

122 Figure 10. Effect of oxygenated edge sites on the predicted Raman spectra of a coronene-based molecule. The bottom spectra are of anhydrous tetracarboxylic perylene. Solid lines represent simulated data while the dashed red line represents experimental data. In addition to the coronene based spectra that have been presented, a selection of defects were also analyzed for circumpyrene and circumcoronene parent rings. The effects of defects within these systems were found to be in agreement with the results presented for coronene. Details of these spectra can be seen in Figures A1 and A2 in Appendix A. 100

123 2.3.4 Band assignments from simulation results Simulations of several different PAHs in the previous section have provided significant insight to the complex Raman spectra of amorphous carbons such as chars and activated carbons. The results of these studies are summarized in Table 4 with detailed descriptions of each band provided below. Shoulder band, Low (SL) ( cm -1 ): Each small PAH tested was found to have weak symmetric breathing mode vibrations between 975 cm -1 and 1075 cm -1 (see Figure 4). The observed vibrational modes in this region are coupled to hydrogen motion along the periphery, but, with the exception of the mode for naphthalene, these vibrations were generally very minor compared to the rest of the spectra. Also identified within this region is a strong secondary symmetric vibration for the cycloheptane centered molecule near 1000 cm -1 (see Figure 6B). This mode is also observed for larger cyclic rings such as cyclooctane [69]. Vibrations within these regions have previously been documented [48] for pure PAHs but are typically too weak to identify in chars and activated carbons [16, 43, 44]. Shoulder band (S) ( cm -1 ): Breathing modes of cyclic systems containing 7 membered rings have been observed within this region for modelled systems (figure 6B). Literature reports also cite similar modes for systems containing cyclooctanes [69]. Aromatic rings of a size similar to pyrene display symmetirc breathing modes within this region, these modes are also present in defective clusters such as SPD-II and DPD-II (Figures 7 and 8 respectively) that contain small aromatic moities. The presence of hetroatoms in adjacenct rings was not found to forbid these modes (Figure 9). Intensity in this region has previously been linked to aliphatic TPA type groups; 101

124 however, the simulations conducted here identified no compelling evidence that this is the primary mode associated with the shoulder in PAH ring systems (see Figure 5). Defect bands (Ds and D) ( cm 1 and cm -1 ): Vibrations within these regions are ascribed to a mixture of symmetric breathing modes and Kekulé type vibrations in larger ring systems. These modes become strongly enhanced in highly ordered systems due to degeneracy as well as resonant effects with the incident light [37]. In smaller systems with lower order symmetry, multiple vibrational modes exists due to coupling of breathing and Kekulé modes. These modes are red and blue shifted from the expected peak at 1350 cm -1. For small PAHs this can result in the formation of two distinct peaks, the first between 1250 cm -1 and 1300 cm -1 (Ds), and the second between 1370 cm -1 and 1400 cm -1 as can be seen in the spectra of perylene and benzo[g,h,i]perylene in Figure 4. Complicating the analysis of this region, combinations of breathing and Kekulé modes have been found to result in a strong D-band, with a moderate secondary mode near 1250 cm -1 (Ds) and a weak shoulder near 1360 cm -1 for larger aromatic systems [50, 51]. In addition, the work of Negri et al. [50] suggests that linearly arranged, Rylenetype, molecules show increased intensity near 1250 cm -1 as the total chain length increases. A general trend observed for systems larger than coronene is a gradual reduction in relative intensity for the primary breathing mode (D), as demonstrated by Negri et al. [50] and observed with both circumpyrene and circumcoronene in our calculations (Appendix A Figures A1 and A2). Amorphous bands (A1 and A2) ( cm -1 and cm -1 ): Uncertainty has remained in the assignment of the A-band within the literature. However, sources generally agree that this valley region is related to irregular structures [16, 43]. Here we identify two distinct bands, the 102

125 first (A1) is found between cm -1 and is assigned primarily to Kekulé dominated vibrations coupled to symmetric breathing of an adjacent cyclopentane ring. This is most clearly demonstrated by the cyclopentane centered system shown in Figure 6A and is consistent with both experimental and calculated spectra for C60 fullerenes [68, 75]. Evidence of this effect is also present in several point defect systems such as SPD-II and SPD-III (Figure 7) and DPD-II (Figure 8). The Stone-Wales defect in DPD-III did not show this band however. The second band (A2) is a mixture of breathing and asymmetric stretching modes of ring systems adjacent to point defects and is seen most prominently as moderate to intense vibrational modes between 1500 cm -1 and 1550 cm -1 as seen in the spectra for the cycloheptane center cluster, SPD- III, DPD-I and DPD-III(see Figures 6-8). The results of this study suggest that this region is strongly linked to out of plane deformation around defects. A second origin for this band involves heteroatom (specifically oxygen) defects. These defects partially restrict asymmetric stretch modes resulting in mixing with breathing modes. The net effect is a strong red shift to approximately 1480 cm -1 of the primary asymmetric bands in heavily restricted systems (see Figure 9). Both the presence of heteroatoms and large out of plane bends resulted in larger red shifts of the primary E2g related mode, though oxygenated defects resulted in substantially greater red shifts. Inclusion of nitrogen was found to have similar, albeit substantially less intense effect on the formation of a mixed breathing-asymmetric stretch modes (see Figure 7). Graphitic bands (Gg and GL) ( cm -1 ): The G-band represents vibrational modes associated with the asymmetric stretch of various sp 2 carbons [40], and is represented by the E2g stretch shown in Figure 4D. While asymmetric stretching occurs in this region for a wide range 103

126 of compounds, the structure of molecule and the overall symmetry of the system play an important role in the distribution of the vibrations, as can be seen in Figures To account for the varying effects of defects and PAH cluster size on the G-band, this region has been assumed to result from two overlapping bands. The first band, GG, is assigned a Gaussian profile and represents small PAHs and defects that produce a distribution of fragmented peaks concentrated in the 1550 cm -1 to 1650 cm -1 region. The second band, GL, is assigned a Lorentzian profile and represents medium to large ring clusters, as larger groups show a single sharp band with minimal distribution located near 1600 cm -1. These assignments have been made based on the theory that vibrational bands that arise from localized or only locally-distributed modes, such as those in graphite, are best represented by a Lorentzian style peak [40, 41], whereas Gaussian peaks better represent statistical distributions of different vibrational states, i.e. an inhomogeneous broadening mechanism [76, 77]. The distribution between these peaks is used in this analysis to qualitatively assess the overall character of the char. D band ( cm -1 ): In this study, the D band is related to the process of a central ring breathing mode with surrounding asymmetric stretch behavior. This mode was only significant for coronene (Figure 4A) and the cycloheptane centered ring system (Figure 6B). The frequency and relative intensity of this band are well predicted for coronene by the simulation. Carbonyl stretch (C)-band ( cm -1 ): Each simulated compound containing a carbonyl group shows a band located between 1700 cm -1 and 1800 cm -1 (see Figure 9), consistent with reported values [78]. The experimental spectrum from tetracarboxylic perylene (dashed red 104

127 overlay in Figure 9) confirms the location and intensity predicted for this band by the DFT simulations. Table 4. Summary of peak assignments Position (cm -1 ) Peak Shape Assignment SL Gaussian Breathing modes for small aromatic regions, secondary breathing mode for 7+ membered ring S Gaussian breathing mode for rings containing 7+ carbons with Kekulé modes in adjacent benzene rings, benzene ring breathing modes adjacent to heteroatom defects DS Gaussian Assorted Breathing modes for most PAHs D Gaussian Combined breathing/kekulé vibrations for PAHs. Larger more symmetric systems show peaks near 1350 cm -1, while peaks for smaller systems move towards 1400 cm A1 Gaussian Breathing mode for 5-membered rings with Kekulé vibrations in adjacent 6-membered rings and near pure Kekulé in small ring systems and moieties A2 Gaussian Mixed breathing and asymmetric stretch vibrational modes for sp 2 carbons near defects causing out of plane deformation. Heteroatom defects tend to cause greater red shift GG Gaussian Distributed asymmetric vibrations for distribution of small PAHs GL Lorentzian Standard E2g mode for large PAHs D Gaussian Double resonance activated breathing mode C Gaussian Carbonyl stretching mode, very weak Deconvolution of Dispersive Raman Spectra from Cellulose derived Chars Figure 11 shows the Raman spectra of cellulose derived chars obtained between 400 C and 700 C. Pyrolysis temperature can be seen to strongly affect the final Raman spectra of chars from cellulose, indicating significant differences do exist in the overall char structure. The results obtained from deconvolution of each spectrum are consistent with changes in cluster size, defects 105

128 and composition and strongly indicate increasing ordering within the system as well as a reduction in oxygen content as pyrolysis temperature is increased. The central D-band positon is found to shift substantially, moving from 1380 cm -1 to 1340 cm -1 with increasing pyrolysis temperature. The overall position of the shoulder near 1250 cm -1 does not appear to move significantly, though overall intensity of this mode decreases with pyrolysis temperature. The G-band shows consistent narrowing with temperature, with a sharp drop in the valley intensity between the G-band and D- band (the A-band region) as pyrolysis temperature was increased from 400 C to 600 C. At 700 C an increase in the minimum valley intensity is observed as well as moderate broadening of the G- band. Figure 11. Experimental Raman spectra of chars produced from cellulose at different temperatures. All data were collected using a 532-nm incident light. 106

129 The dispersive Raman spectrum of cellulose char produced at 400 C, shown in Figure 12A, exemplifies the difficulty in curve fitting spectra from pyrolysis chars. The band assignments given in table 4 have been used to deconvolute and analyze the complex spectra of these materials. The results from this study indicate a complex material structure containing a multitude of small PAH systems, ether groups and an assortment of non-hexagonal ring systems. The structural features identified by the band assignments are qualitatively consist with low temperature char models such as the coal model presented by Shinn [32] and reproduced in Figure 1C. The position and intensity of the peaks used to deconvolute the Raman spectra of cellulose chars produced between 400 C and 700 C are shown in Figure 12B-D. Figure 12B highlights changes in peak positions for S, D and A bands, while Figures 12C and 12D show changes in peak intensities for breathing/kekulé and asymmetric stretch dominated bands respectively. Table 5 details changes in peak width with pyrolysis temperature. 107

130 Figure 12. (A) Deconvolution of Raman spectrum of a cellulose char produced at 400 C using the newly proposed method. The red line (online version only) represents the summation of curves while the solid black line is the original experimental data. The dotted black lines are individual Gaussians based on the curve fitting parameters given in Figures 13B-D and Table 5. The effect of temperature on the deconvolution curve parameters for (B) Peak position (C) Peak intensity of breathing modes and (D) peak intensity of asymmetric stretch modes are also given. 108

131 Table 5. Peak widths at half maximum for thermoseries (cm -1 ). Pyrolysis Temperature ( C) Peak S Ds D A A Gg * GL *minimum peak width allowed in fitting procedure The peak area ratios for each band as compared to the summation of the GG and GL bands (GT) are provided in Table 6. The ratio I(D)/I(GT) follows the same increasing trend with temperature observed by McDonald-Wharry et al. [16] for pyrolysis chars, though the observed ratios are lower in this report. It is noted that we utilize the total peak area for this analysis while McDonald- Wharry et al. used maximum peak intensities. The summation of the S, DS, D, and A1 peaks (D*) the D band region typically obtained by a two curve deconvolution can be approximated. The G- band for this method can be approximated by the summation of GG, GL, and A2 (G*). Examining the I(D*)/I(G*) ratios reveals tends consistent with the I(D)/I(GT) ratio. The same trends are also observed when examining the intensity ratios of only the summed DS and D peaks (I(DT)/(GT)), indicating that the growth of the D-band is the controlling parameter within this region. The I(D*)/I(G*) ratios observed for each char, and the known structure of these materials, place all of chars within the hysteresis region between amorphous carbon and nano-crystalline graphite and are consistent with an ordering trajectory as discussed by Ferrari and Robertson [40]. The intensity ratios of other bands are consistent with the raw intensities show in figure 12C and 12D. 109

132 Table 6. Peak intensities compared to the total area of the G band (GT) Pyrolysis Temperature ( C) Peak I(SL)/I(GT) I(S)/I(GT) I(DS)/I(GT) I(D)/I(GT) I(A1)/I(GT) I(A2)/I(GT) I(ST)/(GT) I(DT)/(GT) I(AT)/(GT) I(D*)/(G*) T subscript denotes summation of related peaks D* is a summation of S, Ds, D, and A1 peaks G* is the summation of GG, GL, and A2 peaks The clearest changes observed as processing temperatures increase are concentrated in the D and G-bands. A red shift in the D-band peak position is accompanied by moderate band broadening, increasing by approximately 20% over the temperature range studied. The total intensity also increases by 50% over this temperature range. The red shift in peak position of the D-band is consistent with the formation of larger aromatic clusters. The identified D-bands shifts from approximately 1380 cm -1 (where bands from small compounds such as pyrene and perylene dominate) for chars produced at 400 C to 1340 cm -1 at 700 C, much more in accordance with the breathing mode of coronene and larger PAH molecules [50, 51]. The DS band is assigned to assorted breathing modes in various PAHs. The peak position for chars produced at 400 C is located at approximately 1275 cm -1, well within the observed range of these modes. As temperature increase, the position of this peaks moves towards 1250 cm -1 with consistent decreases in intensity. This result, coupled with the behavior of the primary D peak is consistent with the formation of moderately sized (coronene like) PAHs. These results do not exclude the formation 110

133 of larger aromatic systems, however such systems would be expected to be less prevalent within the structure. Changes in the G-band also are consistent with the formation of larger, less distorted ring systems as the pyrolysis temperature increases. The Gaussian character initially observed in the 400 C char gives way to a much stronger Lorentzian profile at 700 C. This change occurs sharply at treatment temperatures of 500 C and continues more gradually as temperature increases further. Trends in both the D-band and G-band are consistent with results previously published on the effect of temperature on char spectra [16, 44]. The consistent decrease in intensity observed in the A2 band as temperature increases from C, combined with the relatively low peak position near 1510 cm -1 suggests that oxygenated defects contributed to the intensity of this region for chars produced at temperatures lower than 700 o C. Numerous oxygen groups are at least partially stable in this temperature regime, only decomposing fully at temperatures approaching 650 C [30]. The apparent decrease and subsequent increase of the S-band with temperature suggests that at least two distinct structures contribute to this band. Intensity within this region may be partially due to TPA type regions in chars produced at 400 C, with degradation of these moieties upon heating to 500 C explaining the reduction in peak intensity. The increase observed after heating to 700 C is hypothesized to be a result of the formation of cycloheptane and larger ring systems as the char structure condenses (Figure 6B). Evidence for these structures has been observed in high-resolution transmission electron microscopy (HRTEM) images by Harris et al. [28, 29]. 111

134 Given the moderately intense breathing mode identified near 1180 cm -1 (see Figure 6B) for this structure, it is suspected that cycloheptanes increasingly contribute to the S-band observed in chars produced at temperatures greater than 500 C. The major peak identified near 1450 cm -1 is correlated to Kekulé dominated vibrations in small PAH clusters, as well as mixed breathing and Kekulé modes in systems containing 5-membered rings. The A1 band was found to be highly stable with temperature, consistently identified between 1450 cm -1 and 1460 cm -1. Increasing temperature resulted in both an increase in intensity as well as peak width. The position of the band suggests that Kekulé vibrations coupled with the A1g mode of cyclopentane rings is the primary origin of intensity within this region. Small PAH systems without pentane rings would be expected to show greater intensity near 1400 cm -1 and decrease with temperature. This result suggests that as the pyrolysis temperature increases pentane ring systems become more prevalent within the cellulose char. Analysis of the SL D and C bands was not possible due the minimal intensities of these features. 2.4 Conclusions The theoretical gas-phase Raman spectra of a variety of ordered and defective PAHs have been analyzed. The experimental spectra of several model compounds were used to validate appropriate frequency scaling factors and visualize important Raman active vibrations. Key vibrational modes of various defects were analyzed for distinctive regions to create a new series of band assignments specifically tailored for chars produced at temperatures below 700 C. Our results have shown that the shoulder peak identified near 1200 cm -1 is consistent with vibrational modes for PAH 112

135 structures, specifically, symmetric breathings modes of cycloheptane and larger ring systems which form between 1150 cm -1 and 1200 cm -1. The breathing modes of small PAHs (Naphthalenepyrene scale) were found to be present between 1200 cm -1 and 1300 cm -1 as well as for larger ring systems (greater than coronene). We have demonstrated that the valley commonly observed in Raman spectra and chars is consistent with the modeled system disorder. Intensity between 1400 cm -1 and 1450 cm -1 has been assigned to Kekulé dominated vibrational modes, especially those coupled to breathing modes of pentane ring systems. Intensity between 1480 cm -1 and 1550 cm -1, typically observed as an asymmetric G-band, is linked to coupling of breathing modes and asymmetric stretching caused by strained deformation within the PAH clusters and constriction of motion caused by oxygen inclusion. The new fitting parameters provided excellent fits of each char, but care must be taken to avoid peak divergence, as a sufficient number of fitting parameters are provided for non-meaningful deconvolutions to occur. Analysis of changes in peak parameters with increasing temperature reveal trends consistent with cluster growth, loss of internal oxygenated structures, and formation of non-hexagonal ring systems within the char samples. Acknowledgements: The authors are very thankful for the financial support provided by the Agricultural Research Center (NIFA-Hatch-WNP00701), the Washington State Department of Ecology, and the Washington State Department of Agriculture (Appendix A). It was also partially funded by the USDA/NIFA through Hatch Project #WNP00807 titled: Fundamental and Applied Chemical and Biological Catalysts to Minimize Climate Change, Create a Sustainable Energy Future, and Provide a Safer Food Supply. Part of the research described in this paper was supported in part 113

136 by the U. S. Department of Energy. PNNL is operated by Battelle for the U.S. DOE under Contract DE-AC05-76RLO1830. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of the manuscript, or allow others to do so, for United States Government purposes. 114

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146 Appendix A Supplemental Material for Chapter 2 A.1 Defect structures in circumpyrene and circumcoronene Figure A1. Assorted defects within a circumcoronene (CC) parent system. Single Point Defects (SPD) and Double Point Defects (DPD) correlate to the same defects utilized in the coronene parent throughout the paper. Figure A1 shows the effects of several defects on the Raman spectrum of circumcoronene (CC). Figure A2 shows the effects of adding these defects to circumpyrene (CP). Defects were created by removing atoms 1 and 2, shown in Figure A3A and A3B respectively from the parent structure 124

147 and creating a closed shell system by either replacing bonds and/or adding hydrogens. In the case of DPD-O-II defects, atoms 1 and 2 are replaced with oxygen atoms. The SPD-I-CC system results in the greatest loss of symmetry, a primary results of a sp 3 carbon within the ring structures. This defect results in a similar peak near 1450 cm -1, as observed with oxygenated defects, and shares many characteristics with the nitrogen defect (SPD-N) shown in figure 7. The DPD-I-CC system results in the formation of an isolated phenanthrene-type moiety and a moiety similar to coronene. The defect itself results in only very mild out of plane distortions. The coronene type moiety gives rise to a strong, single mode near 1350 cm -1 with the phenanthrene -type moiety contributing to weaker vibrations near 1280 cm -1. A constricted, semicircular breathing mode in the octane ring system of the DPD-III systems, mixed with breathing modes in the surrounding hexane ring systems exists near 1260 cm -1. More symmetric breathing modes are constricted by the adjacent pentane rings and give only very weak intensity below 1200 cm -1. The same defective coronene type moiety responsible for the peak near 1350 cm -1 in DPD- I-CC also exists in DPD-III-CC. The peaks near 1500 cm -1 are a combination of pentane breathing modes mixed with Kekulé vibrations for lower frequencies, and mixtures of breathing modes and asymmetric stretches at the highest frequencies. Peak locations observed for DPD-O-II-CC are in excellent agreement with those observed for DPD-O-II (see Figure 9), though the relative intensities of the peaks near 1200 and 1350 cm -1 are substantially more intense compared to the peak at 1450 cm -1 in the circumcoronene based system. 125

148 Figure A2. Assorted defects within a circumpyrene parent system. SPDs and DPDs correlate to the same defects utilized in the coronene parent throughout the paper. Inclusion of defects in the circumpyrene structure has much the same effect on the Raman spectra of the daughter compounds as is observed when circumcoronene is used as the parent, though the spectra themselves are somewhat simpler. A notable variation is the effect of the single point defect in SPD-I-CP. The system maintained Cs symmetry, resulting in a substantially simpler Raman spectrum. The effect of the pentane breathing mode on the surrounding phenanthrene/naphthalenetype structures in DPD-III-CP resulted in the strong peak near 1480 cm -1, slightly higher than expected based on the results of the paper but well within the region typically associated with the amorphous zone. The relatively uniform distribution of rings around the central cyclooctane defect 126

149 allowed for uniform breathing modes near 1200 cm -1, resulting in relatively strong peaks in this spectrum. The phenanthrene/naphthalene structures surrounding the defect DPD-O-II-CP resulted in the shift of the primary peak to approximately 1410 cm -1. This shift occurred because Kekulé vibrations become dominate in this configuration without adjacent breathing modes. Figure A3. Parent (A) circumcoronene and (B) circumpyrene compounds used to assess defects in larger ring systems. Numbers 1 and 2 denote carbon atoms removed to create defects. For SPDs only atom 1 is removed, for DPDs both atoms are removed or replaced. 127

150 Chapter 3: Improving the Deconvolution and Interpretation of XPS Spectra from Chars by ab Initio Calculations Paper Submitted to Carbon Matthew Smith 1,2, Louis Scudiero 3, Juan Espinal 4, Jean-Sabin McEwen 2, Manuel Garcia-Perez 1* 1 Department of Biological Systems Engineering, Washington State University, Pullman, WA 99164, USA 2 Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Pullman, WA 99164, USA 3 Department of Chemistry and Materials Science and engineering Program, Washington State University, Pullman, WA 99164, USA 4 Química de Recursos Energéticos y Medio Ambiente, Instituto de Química, Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia UdeA, Calle 70 No , Medellín, Colombia 128

151 Abstract: The interpretation of C1s spectra collected by X-ray photoelectron spectroscopy (XPS) from disordered carbons, such as chars, remains uncertain despite a variety of deconvolution and evaluation schemes reported in the literature. Here, a thermoseries of chars produced from cellulose was studied by XPS to evaluate these schemes and a newly proposed method. Six deconvolution methods derived from the literature have been evaluated based on their capacity to provide reasonable and self-consistent interpretation of C1s and O1s regions. None of the literature based C1s deconvolution methods studied were capable of correctly identifying the quantity and form of oxygen content determined analysis of the correlated O1s spectrum. To improve the selfconsistency of the XPS interpretation a new method is proposed based on a 7 peak C1s deconvolution, 3 C-C peaks, 3 oxygenated peaks, and pi-pi* transition peak. In this method deconvolution of the O1s by 4 peaks is used to determine O-C and O=C contributions which are used to provide upper a lower bounds for the related C1s peaks for C-O, C=O and COO. By constraining the oxygenated region of the C1s spectrum more accurate deconvolution of the C-C region is possible. To improve assignments, various functional groups and carbon structures have been examined via DFT using an initial state approximation. DFT calculations of model compounds (pyrene, cellobiose and peryelene tetracarboxylic dianhydride (PTCDA)) were compared with experimental results to confirm the validity of the calculation method used. From these results binding energies for carbons atom in cyclopentane systems were found to downshift ev compared with carbon atoms contained in adjacent aromatic rings. In contrast, carbon atoms in cycloheptane and cyclooctane ring systems were found to increase binding energy by ev. The DFT calculations justified the use of 3 peaks for deconvolution of the C-C region of C1s XPS spectra. Calculated shifts associated with oxygen groups are largely in agreement with previous literature values, however the presence of carbonyl groups has been 129

152 found to cause moderate increases in the binding energy of numerous atoms in a cluster, up to 0.4 ev per carbonyl. The presence of carbonyls, acids and esters is proposed to contribute strongly to the C-C peak near 285 ev. The new deconvolution method proposed results in C:O ratios with better agreements (within 5 %) of those obtained from total C1s and O1s peaks. Our deconvolution strategy demonstrates a sharp reduction in hydroxyl groups with treatment temperature exceeding 400 o C, in agreement with FT-IR results. A strong increase in the primary C-C peak asymmetry is also identified for samples pyrolyzed at temperatures greater than 500 o C. The new fitting procedures provide excellent internal consistency, with peak assignments validated against molecular simulations. Keywords: XPS, chars, deconvolution of spectra, DFT molecular modeling of carbons 130

153 3.1 Introduction Pyrolysis chars have received increasing attention in the literature for both agricultural and industrial applications. Both the physical and chemical structure of these materials have drastic impacts on critical parameters including reactivity and adsorption capacity, with accurate analysis of the surface being necessary to evaluate these parameters. Despite this, quantitative analysis of the physical structure of chars and other non-graphitizable carbons has proven to be a challenging endeavor [1-5]. Soluble surface compounds confound the titration analyses commonly used for activated carbon analysis [6, 7], while the continued release of volatile vapor phase products from materials produced at temperatures below 1000 K makes analysis by temperature programmed desorption (TPD) questionable [8]. Spectroscopic techniques can be useful in analysis, however techniques such as FT-IR and Raman spectroscopy [3, 9], where good signal dispersion can be obtained for carbons, are not directly quantitative [9]. X-ray photoelectron spectroscopy (XPS) is quantitative in nature, however the core level spectra of carbon tends to become heavily convoluted by multiple oxidation states and often demonstrate non-ideal behavior for both poorly conducting samples [10-12] and highly conductive samples [13, 14], complicating analyses. Despite these challenges, XPS is an exceptionally powerful tool for the characterization of the surface layers, and has been applied to the analysis of every type of carbon, ranging from amorphous and diamond like thin films [15-18], to graphite [14, 19], graphene [13], and carbon nanotubes [20-22]. There are also a number of publications [23-25] on the use of XPS for the study of chars. In these analyses the binding energy shifts associated with various heteroatoms including oxygen, nitrogen and fluorine are used to determine the elemental 131

154 composition of the materials surface. A relatively simple deconvolution for oxygen containing carbons, by far the most common heteroatom studied, sets the primary carbon-carbon peak at ev, with hydroxyl/ether, carbonyl and carboxylic groups shifted approximately 1.5, 3, and 4.5 ev higher, respectively [26, 27]. A fundamental problem exists with this analysis; the oxygen concentration determined from the C1s spectra is seldom consistent with the concentration determined by quantifying each elemental peak independently. To determine oxygen content from the C1s scan several quantification schemes have been proposed. The first, and simplest, method for the quantification of oxygen is based on the assumption that all C-O bonds are hydroxyl like and all COO bonds are carboxyl like, allowing for oxygen to be calculated as the sum of the C-O, C=O and twice the COO peak intensities [13, 14, 26]. A second quantification method proposed by Smith et al. [2] assumes a 50:50 distribution of C-O bonds in the form of hydroxyl (C-OH, C:O = 1) and ether (C-O-C, C:O = 2) like groups. This is achieved by assigning a multiplication factor of 0.75 to the C-O peak. Carbonyl and COO peaks are treated with the same assumptions as the previous method A separate quantification method has also been proposed for use when adventitious carbon is the primary contribution to the carbon peak [28]. In attempts to more accurately assign the C1s region, a variety of deconvolution schemes have been proposed including methods that use: two C-C peaks [14, 29], an asymmetric C-C [13, 14, 26], a combination of an asymmetric C-C peak with a second symmetric C-C peak, and most recently utilization of two defective peaks in combination with an asymmetric primary C-C peak [13]. The asymmetry factor often noted in graphitic carbons [14, 30] is attributed to semi-metal 132

155 effects resulting from conduction band electrons, and has also been identified in polyaromatic compounds larger than 1 nm by Cheung [31]. The secondary C-C peak, commonly shifted by ev from the first, is variously attributed to defect structures [14, 29] and sp 3 carbon [16, 32]. The defective peak assigned near 284 ev has also been assigned to defective carbon structures [22, 33, 34]. Each of these schemes affects the overall distribution and interpretation of deconvoluted peaks. To better identify the origins of defect structures in carbon, a recent study by Feng et al. [29] combined XPS analysis and Raman spectrometry to study defects formation in pyrolytic carbon when subjected to different doses of Ar + irradiation. This study demonstrated a strong correlation between the formation of Raman intensity near 1150 and 1500 wavenumbers and the formation of an intense peak, shifted to a higher binding energy by approximately 1 ev in the XPS spectrum. Raman intensity near 1150 and 1500 wavenumbers has been linked with out-of-plane distortions resulting ether various point defects [1] or mechanical stress [35]. These proposed defects are in strong agreement with those previously observed by high resolution transmission electron microscopy for activated carbon [36]. While these results have given some clarification on the origins of the defect peaks, the effects of various potential structures on the C1s profile is difficult to determine due to the variety of possible chemical states [37]. To better determine the effects of structure and bonding, density functional theory (DFT) calculations have been used to analyze a wide variety of systems [38-43]. For these calculations binding energies are determined using several possible approximations, including; initial state, final state, and transition state approximations. Initial state approximations are the 133

156 simplest to implement but least accurate, neglecting core-hole screening effects [44]. The final state approximation is more intensive, isolating the desired core-hole in the structure and determining the full screening effect. The transition state approximation utilizes partial orbital occupations to describe the excitation process [45]. These methods have been applied by several studies to examine the core binding energies associated with a wide variety of carbon containing compounds, including; small molecules [37, 38], graphitic carbons [42, 43] and chars [41]. These studies have used both initial state [37, 41, 43] and final state calculations [38, 42]. The work of Levi et al. [41] and Barinov et al. [42] provide an excellent initial assessment of the effect of defect structures on carbonaceous materials by DFT simulations. In this paper we will examine the deconvolution of XPS spectra from chars with assignments and positioning supported by molecular simulations. Here, the effects of several defect structures previously proposed for cellulose chars are examined with respect to their role on the core level binding energies relevant to XPS. This information is used in conjunction with a newly proposed combined O1s and C1s deconvolution strategy to better deconvolute and interpret XPS spectra obtained from chars. 3.2 Materials and Methods All studies described here have been performed with model compounds or thermally treated model compounds. Avicel cellulose (LOT# BCBG9043V) is used to evaluate the effect of pyrolysis temperature on the surface chemistry of the resultant chars. Several model compounds have been used to validate DFT simulations, including pyrene (product# ), cellobiose (product# 134

157 22150), and anhydrous PTCDA (product# P11255). All compounds have a minimum purity of 95% and have been used as received Pyrolysis A series of five pyrolysis chars have been produced at temperatures between 300 and 700 o C from Avicel cellulose in a spoon pyrolysis reactor following same methods as previously described [1, 5]. Briefly, the furnace is preheated to a desired temperature while a pre-weight sample is stored in a water-jacketed cooling zone. The cooling zone and furnace are purged with a N2 gas (99%) stream flowing at approximately 300 ml/min for a minimum of 10 minutes prior to treatment. At the start of the experiment the sample is introduced into the furnace and treated for 30 minutes before withdrawal to the cooling zone. A secondary preheated nitrogen sweep gas, flowing at approximately 550 ml/min, is employed in the reactor zone to minimize vapor-char interactions. Samples were allowed to cool to temperatures below 25 C under N2 before exposure to air General Characterization The bulk carbon to oxygen ratio of the cellulose chars was determined in triplicate using a LECO elemental analysis system. All measurements utilized approximately 150 mg of samples per trial. The calibration was checked by analysis of a cellulose standard (deviations of less than 1%). FT-IR spectra were obtained using a ThermoFisher Nicolet IS10 spectrometer. Final spectra are the average of 64 scans collect between 600 and 4000 cm

158 Surface area was determined based on the Dubinin-Radushkevich (DR) equation [46, 47] for CO2 adsorption isotherms collected at 273K as described previously [2] Computational Pyrene, cellobiose, and PTCDA have been analyzed via density functional theory (DFT) to confirm the validity of the computational methods presented here. Defect based daughter compounds of polyaromatic parents have been used to evaluate the effects of various carbon bonding structures proposed to be prevalent in the chars [1] and activated carbons [36]. Several oxygenated defects have also been included to determine likely shifts associated with both the C1s and O1s spectra. All calculations have been performed using the Gaussian 09 rev. B.01 software package [48], and evaluated using most abundant isotopes. Geometry optimizations is performed using the Becke three-parameter Lee-Yang-Parr (B3LYP) hybrid functional [49], and a Pople type split valence 6-311G(d,p) basis set [50], following the results presented previously by Giesbers [37]. A singlet state was previously confirmed to be the ground state configuration for each daughter compound examined in this study [1]. The individual electron energies for each atom were determined using the NBO 3.0 package available within Gaussian 09. Koopmans theorem [44] has been applied, in which the core-binding energy is estimated as the negative of the electron energy in the initial state. This estimate does not take into account electron rearrangement, but has been found to provide a reasonable estimate for binding energies using a simple linear correction factor [37], given in Eq. 1a. This equation was established using a reference binding energy of ev for alkene carbons, to accurately reflect the reference energy used here of ev the offset was reduced by 0.6 ev to ev, Eq. 1b. Because of its simplicity, this method allows for rapid screening of multiple compounds without the need to calculate additional electronic 136

159 configurations for each molecule of interest, as required for difference or final state approximations. BE corrected (ev) = BE B3LYP (ev) (eV) BE corrected (ev) = BE B3LYP (ev) (eV) Eq. 1a Eq. 1b The linear fit presented in Eq. 1a is based on the best fit results obtained by comparing experimental and simulated C1s binding energies from 9 organic compounds comprising a total of more than 20 unique carbons sites. The resulting mean deviation was 0.29 ev from experimental results with a maximum devotion of 0.72 ev. From this, a variance of more than 0.4 ev (0.29 ev * ) from the average calculated binding energy of a coronene structure is considered significant for the results of the current study XPS The X-ray photoemission spectra of each char in the thermoseries, as well as all reference compounds, were evaluated using an AXIS-165 manufactured by Kratos Analytical Inc. (Spring Valley, NY, USA). Scans are conducted following the same method previously employed [2]. Briefly, an achromatic X-ray radiation of ev (MgKα) was used for each material. All spectra were recorded using a pass energy of 40 ev and spot size of approximately 120 µm. The spectrometer was calibrated against both the Au 4f7/2 peak at 84.0 ev and the Ag 3d5/2 peak at ev. Survey scans have been obtained using step sizes of 1 ev to determine overall chemical composition. To determine the speciation of carbon-oxygen groups high resolution scans of the C1s and O1s regions have been collected for each material using 0.15 ev step sizes. All XPS 137

160 spectra were analyzed using the XPSpeak4.1 software. Baseline corrections were made using a Shirley type background correction [51]. Static charging was detected in raw cellulose and chars produced at temperatures of 500 o C or less. This charging was corrected with a neutralizer (flood gun) by centering the dominate C-C peak near ev (filament current set to 1.8 A, charge balance varied between V). This procedure introduced varying degrees of shift in the baseline, which have been corrected by applying an offset of ev XPS Deconvolution Existing XPS approaches deconvolution schemes: Examples of several deconvolution schemes proposed in the literature are given in supplementa Figure B1 (see Appendix B section B1) and have been applied to the thermoseries of cellulose chars using the XPSpeak4.1 software. These schemes are broken down into two broad classes: three schemes using only symmetric line shapes, denoted Sm1-Sm3 (Figure 3A-3C) [20, 27], and three schemes using an asymmetric C-C peak at approximately 284.4, denoted A1-A3 (figures 3D-3F) [13, 14, 26]. The Appendix B section B2 details the use of this asymmetric peak shape. Each of these classes utilize one [26, 27], two [2, 14, 15, 52], and three [13] C-C peaks. The primary C-C peak is that typically assigned at ev for aromatic C-C/C-H bonds. The second peak, near 285 ev is variously assigned to sp 3 [15] carbons and defective carbon structures [14, 52], The third and most recently implemented peak is situated near 284 ev and has been assigned to a second class of defective carbons [13, 21, 22]. The sets of binding energy positions used for each scheme are given in Table

161 Table 1. Summary of binding energies used for the deconvolution of C1s and O1s spectra (ev). Method Peak I Peak II Peak III Peak IV Peak V Peak VI Peak VII Carbon C1s C-C low C-C primary C-C high C-O C=O COO Pi-Pi* 1 N/A N/A PII PII PII N/A PII PII PII PII PII PII PII PII PII Oxygen O1s C=O C-O aliphatic C-O aromatic O 2/H 2O PII: Represents the actual binding energy (ev) determined during deconvolution for peak 2, the primary C-C peak The same peak positions are used for both Sm and A deconvolution schemes Deconvolution of the O1s spectrum is preformed based on the assignments given by Beamson and Briggs [53] for oxygenated polymers. These positions are also summarized in Table 1. This strategy places a C=O peak at ev with an aliphatic C-O group positioned at ev and aromatic C=O positioned near ev. These positions are consist with those reported by other groups [54]. The assignment of adsorbed moisture and oxygen is variously assigned between 533 and 535 ev. Work by Herman et al. [55], demonstrated that the binding energy of water was sensitive to total surface coverage on anatase. At coverage less than 1 monolayer, binding energies of approximately 535 ev are observed. The apparent binding energy decreases toward 534 ev as the surface coverage exceeds 1 monolayer. Because sub monolayer adsorption is anticipated on chars only exposed to atmospheric conditions and then degassed, the moisture peak is assigned here at ev. Three oxygen quantification schemes have been evaluated; see equations 2a-2c. These methods are referred to scheme a-c. The first (scheme a), given by equation 2a, is the most commonly utilized method for the quantification of oxygen. Here, the described oxygenated species are taken as isolated systems and the sum of peak intensities of the C-O, C=O and twice the COO peaks gives the total oxygen intensity [13, 14, 26]. The second (scheme b), proposed by Smith et al. [2] and shown in equation 2b, assumes that C-O bonds are evenly distributed between carbon bound 139

162 hydroxyl groups and ethers by assigning a sensitive factor of 0.75 to the C-O peak. The third quantification method (scheme c) given in equation 2c, assumes that the entirety of the C-O signal results from ether bonds and lactones, while the COO peak results entirely from lactones. These assumptions yield the minimum possible oxygen content for the deconvoluted C1s spectra. O C1s = A C O + A C=O + 2 A COO O C1s = A C O A C=O + 2 A COO Eq. 2a Eq. 2b O C1s = A C O A COO 2 + A C=O + 2 A COO Eq. 2c Where: Ax = the total integrated intensity of the specified deconvolution peak (C-O, C=O, and COO) OC1s = equivalent oxygen content determined from C1s scan New C1s Deconvolution: The most detailed of the previously discussed schemes (A3) is used as the basis for a more constrained fitting procedure. Several modifications have been made to this procedure to improve the estimation of the C/O ratio and ensure a self-consistent evaluation, these include; utilization of sequential deconvolution of the O1s and C1s spectra, fixed asymmetric tail length (TL) and a freely variable asymmetry contribution (TS), as well as inclusion of a variable oxygen quantification scheme, Eq. 3, that allows for shifting distributions of hydroxyl and ether like groups, DHE (0 for all hydroxyl and 1 for all ether), as well as carboxyl and lactone/ester groups, DCL (0 for all carboxyl, 1 for all lactone). This method also estimates the distribution of carbons bonded to two ether/hydroxyl groups and carbonyl groups. In this assessment, carbons 140

163 bonded to two oxygens by single bonds are evaluated as part of the AC-O peak. Details of the oxygen constraints are given in Appendix A section A3. O C1s = (A C O D CL A COO ) (1 D HE 2 ) + A C=O + 2 A COO Eq. 3 All deconvolutions utilizing this method have been performed using an in-house excel based routine. A Shirley type background correction is used; calculated based off of 10 iterations. Deconvolution is conducted using a sum based asymmetric pseudo Voigt function, as implemented in XPSpeak 4.1 and shown in Eq. 4, for the primary C-C. A symmetric pseudo Voigt function (A(x,p,w,m) = 0 in Eq. 4) is used for all other peaks. Optimization is performed by minimization of the sum of the square errors between the deconvolution curve and real spectrum using the built in GRG2 solver in excel. A convergence criterion of 10-7 over 5 iterations was used to determine convergence. AGLsum(x, p, w, m, h) = h[g(x, p, w, m) + L(x, p, w, m) + A(x, p, w, m)] Eq. 4 2 G(x, p, w, m) = (1 m) e ln(2) [2 (x p) w ] m L(x, p, w, m) = x p 1 + (2 w )2 2 2 A(x, p, w, m) = TS [1 e ln(2) [2 (x p) w ] ] e 6.9 TL (2 (x p) w ) Where: G = Gaussian contribution; L = Lorentzian contribution; A = Asymmetric contribution 141

164 x = binding energy (ev), p = peak center (ev), w = FWHM (ev), m = Gaussian-Lorentzian mixing (0 Gaussian: 1 Lorentzian), h = peak height (counts/sec) TS = asymmetry parameter, and TL = asymmetry tailing parameter Deconvolution of the C1s spectra utilizes 7 peaks (3 C-C peaks, 3 C-O peaks and a pi-pi* shakeup peak) as discussed by Blume et al. [13]. The full width half-maximum (FWHM) of each C-C peak is set to ev while the oxygenated peaks are set to ev. This discrepancy is due to the larger distribution of possible oxygen binding states for each group as compared to the C-C region. A minimum broadening of approximately 1 ev is expected due to the X-ray source. The pi-pi* transition peak, is assumed to be a broad feature and is allowed to vary between 2 and 3 ev. The primary C-C (peak II) is assigned to aromatic carbons, and is allowed a variable asymmetry factor based on the empirical equation utilized by Kwok in XPSpeak 4.1, given by A(x,p,w,m) in equation 1, with the TL value fixed at 200 (see Appendix B section B2 for further discussion regarding this selection). The remaining two C-C peaks, centered near ev (peak I) and 285 ev (peak III), are assigned to assorted defects and evaluated as symmetric peaks. The oxygenated region consists of three curves centered at approximately ev (C-O, curve IV) ev (C=O or O-C-O, curve V) and 289 ev (O-C=O, curve VI). These peaks are evaluated as symmetric peaks and are constrained by information from prior deconvolution of the O1s spectrum. 3.3 Results Cellulose chars have been produced at temperatures from 300 to 700 o C using the spoon pyrolysis reactor at WSU. The apparent surface area (SA) and elemental composition are presented in Table 2, here chars are denoted as CX, where X is the pyrolysis temperature. Pyrolysis yield drop off 142

165 significantly as temperature is increased to 500 o C. At higher temperatures the total yield decreases only slightly suggesting that the primary loss of carbon and oxygen occurs by 500 o C with subsequent mass loss a result of poly-condensation reactions [5, 56, 57]. Both surface area and total carbon content were found to increase continuously as pyrolysis temperature was increased (see Table 2). A small contamination of nitrogen was found to exist in each char, increasing with pyrolysis temperature, however did not exceed 0.4% for any material. The content of H was found to decrease as a function of temperature, from approximately 6 wt% to 1.5 wt% (see Table 2). Increasing pyrolysis temperatures resulted in substantial increases in surface area. Despite the increased surface area, higher treatment temperatures also resulted in a more hydrophobic surface, resulting in reduced adsorption of moisture from the atmosphere following production. These results clearly indicate that the structural composition of chars can vary widely over the pyrolysis temperature range studied here, and interpretation via XPS must be robust to account for the varying forms of the material. Table 2. Bulk properties associated with cellulose and cellulose chars Avicel c300 c400 c500 c600 c700 Moisture (wt %) 3.6 (0.12) 2.7 (0.15) 2.6 (0.09) 1.7(0.30) 1.0(0.31) 1.0 (0.21) SA (CO 2) (m 2 /g) N/A C (wt %) 42.8 (0.14) 44.5 (0.05) 74.5 (0.28) 81.5 (0.17) 87.8 (0.37) 90.2 (0.11) H (wt %) 6.4 (0.03) 6.1 (0.05) 3.9 (0.02) 3.5 (0.06) 2.7 (0.02) 2.0 (0.02) N (wt %) 0.06 (0.01) 0.03 (0.01) 0.08 (0.01) 0.11 (0.02) 0.24 (0.01) 0.36 (0.01) O* (wt %) 50.8 (0.01) 49.4 (0.09) 21.5 (0.28) 15 (0.13) 9.3 (0.4) 7.5 (0.12) Ash <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% C:O (Molar, daf) *Calculated by difference daf: dry ash free basis A preliminary assessment of bulk oxygenated groups has been performed by FT-IR analysis, given in Figure 1. These results indicate a sharp reduction in in O-H stretching modes near 3300 cm -1 when pyrolysis temperatures are increased from 300 o C and 400 o C with nearly complete loss of these groups by 500 o C. Despite the loss of hydroxyl groups, aromatic C-O stretches, which present 143

166 near 1200 cm -1, are identified at all treatment temperatures at or above 400 o C, indicating the formation of ether or ester like groups within the aromatic structures. Acid or ester groups can also be identified by a relatively sharp peak near 1700 cm -1 that persists on chars produced at o C. Because little OH stretching is observed at temperatures above 400 o C these vibrations are most likely related to esters and lactones. The IR results demonstrate a consistent decrease in C- H modes near 2900 cm -1, as well as rapid development of C=C stretching modes near 1600 cm -1 at treatment temperatures of 400 o C consistent with increasing aromatic condensation. It is important to note that in comparison to XPS, FT-IR has a greater sampling depth, resulting in greater signal contributions from the bulk.. Still, these results provide useful insights into the changes in composition of the char with temperature. The change in hydroxyl and ether group distribution identified must be considered in any oxygen quantification scheme based on the C1s spectra since the C:O ratios for these groups differ (1:1 for carbon bound to hydroxyls and 2:1 for ethers). The same is also true for potential shifts in carboxylic acid and lactone/ester distributions (2:1 and 1:1). 144

167 Figure 1. FT-IR transmittance for a thermoseries of cellulose chars produced at temperatures from 300 o C to 700 o C. Dash lines indicate important regions of the various spectra XPS analysis of thermoseries Survey scans have been collected for each char in the thermoseries. These results are displayed in Figure 2A. A small peak is also identified at ~52 ev, however the location, and lack of additional peaks throughout the spectra indicate that this is a carbon ghost peak resulting from Al Kα x-ray contamination [58]. This result is supported by a minor peak near 300 ev identified in the cellulose 145

168 and C300 spectra which decreases proportionally with the primary oxygen peak. The results demonstrate that only C and O contribute significantly to the surface chemistry. Quantification of the C1s and O1s region has been achieved by applying a Shirley type background correction [51] to each peak and applying the pertinent relative sensitivity factors (RSF) to standardized the reported counts. The RSF for oxygen compared to carbon is 2.31 for the AXIS 165 instrument used based on the factory turning. This value is considerably lower than the commonly used Scofield RSF of 2.93 [59], highlighting the importance of accurate tuning parameters when quantification is required. The resulting C:O atomic ratios determined by XPS using this value compare exceptionally well to the bulk elemental ratios for materials treated at temperatures below 400 o C, as shown in the parity plot, Figure 2B. Comparison of more heavily surface weighted results determined by XPS and bulk C:O ratios determined by combustion analysis demonstrate increasing divergence of the bulk and surface properties as pyrolysis temperature is increased above 500 o C. This effect is attributed to rapid chemisorption of oxygenated species at active sites [27, 60] and has been previously observed for a thermoseries of cellulose chars [61]. Similarly, dissociative adsorption of CO2 at carbene like sites has also been proposed [62]. Previous studies have established that only a small fraction of the char surface contains these free radicals, however they tend to form more readily at temperatures above 400 o C during pyrolysis [63, 64]. Combined with the low oxygen content of chars produced at these elevated temperatures, dramatic offsets, as seen in the parity plot, are not unexpected. 146

169 A O1s C1s B Figure 2. (A) Comparison of the wide-scan XPS results for Avicel cellulose and the resultant chars. (B) Parity plot of the atomic bulk C:O ratio from elemental analysis with the C: O ratios obtained by XPS using by high resolution C1s and O1s scans. The C:O ratio determined by the wide scan comparison of carbon and oxygen represents, in theory, the maximum quantity of oxygen that can be bound to carbon. In materials such as chars or activated carbons from biomass the quantity of oxygen that can be bound to carbon will be lower (larger C:O ratio) due to oxygen associated with inorganic moieties (such as CaO or SiO2) in these complex materials and must be considered in any quantification. In the case of cellulose chars presented here this effect is of only nominal importance because of the very low mineral content of the original Avicel cellulose. Therefore the oxygen content determined for the O1s peak area and deconvolution of the C1s peak should be in strong agreement. In more complex biomass systems containing quantifiable mineral matter, it will be necessary to determine the oxygen associated with the mineral content first to accurately quantify the oxygen associated with carbon. 147

170 Deconvolution of XPS curves by published methods High resolution scans of C1s and O1s for a thermoseries of cellulose chars is given in Figure 3. A strong reduction in intensity of peaks near ev is noted with increasing pyrolysis temperature, a product of the loss of hydroxyl and ether groups. These results are qualitatively in agreement with both the wide scan data and the bulk elemental analysis data. A B 700 o C 600 o C 500 o C 400 o C 300 o C Avicel Figure 3. Development of (A) C1s and (B) O1s XPS spectra with increasing pyrolysis temperature Total peak areas for the C1s and O1s spectra of each material are given in Table 3. The O1s deconvolution results are also given for each material. From these results, the development of the O=C peak is apparent at pyrolysis temperatures of 400 o C or greater. The content of this group 148

171 increases from negligible in the raw material and the material produced at 300 o C to approximately 35% at 600 o C and 700 o C. Table 3. Fine Scan C1s and O1s peak parameters with O1s deconvolution Fine scan Total peak areas Cellulose c300 c400 c500 c600 c700 C1s (counts/sec) O1s (counts/sec) C:O* O1s Deconvolution (atomic %) O-C (aromatic) O-C (aliphatic) C=O O 2/H 2O *results from comparison of C1s and O1s fine scans Each of the deconvolution schemes derived from the literature has been used to analyze the C1s char spectrum for each material. Table 4 details the results obtained by the totally symmetric deconvolution methods Sm1-Sm3. These results highlight the wide ranging variability of chars as a function of temperature, as well as the difficulty associated with accurate deconvolution. Each symmetric deconvolution procedure produced good results when comparing the estimated and measured oxygen content for cellulose and C300, while only scheme Sm2 and Sm3 provided reasonable results for C500. This improved fit is most strongly correlated to the shift of the C-O peak by +1.8 ev. Addition of secondary and tertiary C-C peaks without shifting this position did not result in substantial changes to the results (data not shown). Deconvolution using these methods substantially overestimates the oxygen content of C400. Based on the strong signal intensity near ev, it is probable that much of the intensity attributed to C-O bonds can instead be attributed to the secondary C-C defect peak and that the C-O position may need to be shifted to 149

172 higher binding energies. The symmetric peak analysis failed to reasonably quantify the oxygen content of chars produced above 500 o C, revealing substantial overestimations of oxygen, even when considering the least oxygen intensive quantification, scheme c. The inclusion of secondary and tertiary C-C peaks (Sm2 and Sm3) did improve oxygen quantification somewhat for both C600 and C700 samples, however not substantially. The poor fitting here suggests that secondary emission effects are occurring that distort the C1s spectrum for each of these materials. Table 4. Application of symmetric deconvolution methods utilized within the literature and comparison of C:O ratios to totals determined from the total C1s and O1s spectra. Negative values for the deviation from the C1s:O1s ratio indicates an overestimation of oxygen. Sample Method C-C low XPS Deconvolution Peaks (% of total peak area) C-C C-C high Calculated C:O distribution (deviation from C1s: O1s) C-O C=O COO pi-pi* C:O a C:O b C:O c Cellulose Sm (-19.3%) 1.37 (-5.4%) 1.70 (17.5%) c (-20.9%) 1.66 (-4.9%) 2.17 (24%) c (-61%) 2.55 (-53.6%) 3.38 (-38.4%) c (-48.7%) 3.47 (-40.1%) 4.64 (-20%) c (-59.5%) 4.46 (-53.6%) 5.85 (-39.2%) c (-72.5%) 4.04 (-68.5%) 5.2 (-59.4%) Cellulose Sm (-19%) 1.37 (-4.9%) 1.71 (18.5%) c (-17.2%) 1.70 (-2.5%) 2.17 (24.1%) c (-53.5%) 2.94 (-46.5%) 3.80 (-30.8%) c (-29.7%) 4.54 (-21.7%) 5.85 (0.7%) c (-59%) 4.49 (-53.3%) 5.95 (-38.2%) c (-67.6%) 4.66 (-63.6%) 5.96 (-53.5%) Cellulose Sm (-19.4%) 1.36 (-5.6%) 1.71 (17.9%) c (-16.6%) 1.73 (-0.9%) 2.22 (27.3%) c (-52.1%) 3.05 (-44.5%) 3.96 (-28%) c (-28.6%) 4.64 (-20%) 5.98 (2.9%) c (-55%) 4.89 (-49.1%) 6.45 (-33%) c (-67%) 4.76 (-62.8%) 6.11 (-52.3%) 150

173 The results for asymmetric deconvolution of the C1s spectra are presented in Table 5. Because the symmetric deconvolution was found to fit the results for most material treated at temperatures at or below 500 o C well, analysis of the impact of asymmetric peak shapes is limited only to materials treated at 500 o C and higher. In this analysis the asymmetry factor is varied manually in 0.01 step increments until reasonable agreement with total oxygen is obtained and fit error is minimized. An error in the quantification of the asymmetric peak within XPSpeak4.1 is noted, where the total area of the asymmetric peak can, under moderate asymmetry, exceed to the total signal substantially. To minimize this challenge the total peak area is assumed to be the total background-corrected area. The symmetric peak areas of the defect and oxidation peaks are subtracted from this value, and the asymmetric peak fraction reported here is the calculated difference. Table 5. Asymmetric Deconvolutions XPS Deconvolution Peaks (% of total peak area) Calculated C:O distribution (deviation from C1s: O1s) Sample Method C-C low C-C (asym) C-C high C-O C=O COO pi-pi* C:O (a) C:O (b) C:O (c) c500 A (0.04) (-38.3%) 4.22 (-27.3%) 5.69 (-1.9%) c (0.09) (-21.3%) 8.82 (-8.4%) (28.4%) c (0.14) (2%) (17%) (64.1%) c500 A (0.04) (-25.2%) 4.9 (-15.4%) 6.42 (10.5%) c (0.09) (-12.3%) 9.56 (-0.8%) (37.8%) c (0.14) (-9.7%) (1.1%) (39.4%) c500 A (0.05) (-11.3%) 5.79 (-0.2%) 7.5 (29%) c (0.11) (-6.1%) (5.2%) (46.2%) ( (- c (0.15) %) 11.8%) (17.4%) The results for the asymmetric deconvolution of C500-C700 show substantially better agreement with the oxygen content predicted by comparison of the C1s and O1s scans, particularly when 151

174 considering quantification scheme b. The optimized peak asymmetry was found to vary slightly depending on the defect peaks used, however a consistent trend of increasing asymmetry was observed with temperature. The TS parameter was found to increase from approximately 0.05 to 0.15 as pyrolysis temperature increased. The wide variety of fitting methods proposed for XPS spectra in the literature, and the relatively poor internal consistency obtained when applied to chars, clearly demonstrate the need for additional care in fitting the C-C region of many char spectra. While at least one combination of peaks (Sm 1-3 or A 1-3) and oxygen quantification schemes (a-c) did provide an internally consistent result for most chars, no single method was effective for the deconvolution of all materials. The results demonstrate that while simple fitting procedures may be valid for material produced at temperatures at or below 300 o C, additional C-C peaks and asymmetry are often needed for chars produced at higher temperatures. To improve on the results of the initial deconvolution trials a new procedure is needed. To ensure reasonable peak assignment and constraints for each deconvolution parameter, ab initio DFT calculations have been performed to evaluate the contributions of a variety of carbon-carbon and carbon-oxygen bonding conditions. These results are combined to propose an improved deconvolution scheme in section Computational analysis of strained and oxygenated systems To establish the validity of the computational models used in this study, several reference model compounds (pyrene, cellobiose, and PTCDA) were evaluated experimentally and by DFT analysis. 152

175 The results of these studies are compared in Figure 4. The black line represents the calculated spectrum for the listed compounds, while the red line gives the corresponding experimental spectrum. The calculated positions were corrected based on the empirical linear correction factor (Eq. 1b) based on the results published by Giesbers et al. [37]. Charging effects required baseline correction of ev for the experimental spectra. This equation has tentatively been extended to the O1s spectra with the offset increased to ev to fit the O1s peak position of cellobiose. A B Pe C Pe D Figure 4. Experimental (red) and theoretical (black) binding energy overlays for (A) Pyrene C1s (B) Cellobiose C1s (C) PTCDA C1s (D) cellobiose O1s. The experimental lines are computed using the corrected bindings determined via DFT, and expanded based on the individual broadening parameters given in Table 6. The intensity of both the experimental and theoretical lines are normalized against the point with greatest intensity. Individual binding energies for each C and O atom are given in Appendix B section B4, Figure B3. 153

176 The computational and experimental fitting parameters used for each reference compound are listed in Table 6. To match the shapes of the experimental spectra, a Gaussian:Lorenztian sum (G:Lsum) function was used to broaden the calculated binding energy identified for the core electrons of each carbon in the model system. To optimize this parameter, the G:L distribution and the full width at half maximum (FWHM) were allowed to vary as a single parameter for all atoms within each individual compound. A single G:L ratio and FWHM was not universally calculated because of varying effects such as charging, which can cause minor variations in the recorded line-shape of each spectrum [11]. These parameters are compared to those obtained by fitting a single deconvolution peak to the primary C-C peak of each experimental spectrum. Here, the optimized FWHM parameters compare well to the single peak analysis, while the Lorentzian contribution is significantly higher for the simulation fit parameters. This behavior is expected as the convolution of several overlapping Lorentzian signals will tend to produce a curve with far more Gaussian character. While neither the FWHM nor the distribution of G:L shapes was consistent between samples, an average FWHM of approximately 1.56 ev with a 55% Lorentzian profile is estimated based on the results. This averaged broadening factor is used to produce theoretical line shapes for all simulated spectra. These results indicate that any deconvolution peak should have a minimum G:L ratio of no more than 0.3 and a minimum FWHM of approximately 1.4 to 1.5 ev for non-conductive samples. Materials with multiple atoms with similar peak positions will show substantially lower G:L ratios. 154

177 Table 6. Fitting parameters used for the analysis of model compounds with a GLsum line shape. Simulation fit parameters Experimental fit parameters Sample FWHM (ev) GL FWHM (ev) GL Pyrene Cellobiose PTCDA (1.53)* 0.29 (0.37)* Average * values in parentheses are for a necessary secondary peak and have not been included in the average Overall, the computational models identified shifts in the C1s binding energies exceptionally well and the use of a GLsum function was found to provide a good approximation the shapes of the experimental peaks, see Figures 4A-C. The excess tailing observed in the experimental C1s scan of PTCDA (Figure 1C) near 292 ev is attributed to a shake-up peak [65, 66]. An important effect is noted for the cellobiose sample, Figure 4B, where a shoulder, shifted approximately 1.5 ev from the primary C-O peak is observed. This peak results from carbons at the C1 position in each monomer. These carbons are linked to both the internal ether and the 1-4β glyosidic linkage, resulting in two C-O bonds for each carbon atom. This causes a shift comparable to that reported for carbonyl groups and must be considered in the analysis of chars produced at low temperatures, where portions of the original biomass structure may not be fully degraded. O1s fine spectra were also collected and calculated for each compounds. The calculated results for cellobiose, show good agreement when an offset of ev is employed, Figure 4D, though total FWHM is somewhat larger than the experimental results. These results demonstrate a relatively wide dispersion for O-C, roughly 1.8 ev within cellobiose alone. This high dispersion would account for the relative insensitivity of peak broadness to X-ray source observed in previous studies [13]. The results for PTCDA do show strong shifts between the C-O and C=O positions 155

178 for the cyclic anhydride groups, however the predicted shift between the C-O and C=O are calculated to be 3.8 ev, more than 1 ev greater than the experimental shift. Similar exaggerations in O1s binding energies were also observed for simulated compounds presented in In addition to positional offsets, the experimental intensity of the peak associated with the bridging ether oxygen is substantially greater than expected. This effect has been observed previously and is linked to a shake-up peak associated with the carbonyl that presents near the ether bonded oxygen [65, 66]. Based on these results it is concluded that to properly simulate the O1s spectrum of aromatics, final state effects must be considered. This is beyond the scope of this work, and so O1s deconvolution parameters have been taken from experimental literature results, and have been found to agree with the limited reference peaks obtained here. While this may somewhat limit interpretation of results, this also limits the possibility that peak positions are erroneously assigned Effect of hybridization and hydrogenation To confirm that the calculated spectra of aromatic systems of varying sizes do not show substantial binding energy variations, three polyaromatic systems of increasing size were adopted as parent structures. These include coronene, circumpyrene, and circumcoronene. Figure 5 shows the normalized calculated XPS spectra for each of the parent molecules used. As with pyrene, each displays a sharp symmetric peak centered near ev. Only a very mild shift in the central binding energy is observed as ring size increases. This is attributed to the reduction of C-H and C-C which presents slightly shifted positions. 156

179 Figure 5. Reference spectra for Coronene (green), circumpyrene (black), and circumcoronene (red) The effect of sp 3 carbons was tested by incorporating alkane side chains to the periphery of a coronene molecule with the results shown in Figure 6A and 6B. The addition of these carbons had an unexpected effect; a general reduction in binding energy identified for the overall molecule of ev. This downshift is outside of the quantifiable limits of the experiments performed here, but is surprising as sp 3 carbons are commonly assigned near ev. This effect is attributed to the high degree of hydrogenation associated with these chains. In contrast to the deviations that result from sp 3 carbons, alkene chains, shown in Figure 6C and 6D, do not have any appreciable effect on the resulting XPS signal. Though minor shifts in binging energy are 157

180 associated with hybridization and hydrogenation, they are not sufficient to explain the substantial defect peaks observed previously. To explain these peaks defect structures must be considered. A B C D Figure 6. Reference sp 3 containing carbon structures (A) single pentane chain linked to coronene (B) two pentane chains linked to coronene (C) single buta-di-ene chain linked to coronene (D) two buta-di-ene chains linked to coronene. The black line in each Figure denotes the modified coronene structure, while the red dashed line gives the parent coronene. Individual binding energies for each C atom are given in Appendix B section B4, Figure B4. 158

181 Effect of Defects on C-C core electron binding energies The effect of an internal cyclopentane ring within a polyaromatic structure is shown in Figure 7A. In this structure three distinct carbons are present and labeled A, B and C. These carbons are repeated in each section around the structure. The central location of the cyclopentane results in a circular out of plane bending for the adjacent benzene rings. Examining the core binding energies for carbons atom in the cyclopentane systems reveals a downshift of 0.57 ev compared to the average C1s binding energy of coronene, and ev when compared to carbon atoms contained only in the adjacent rings. This shift is considered significant based on the average error previously reported for this correction factor. As a result of this downshift a distinct asymmetry is observed on the low binding energy side of the carbon peak. When compared to an unmodified coronene system (dashed red line) it is apparent that, while the binding energy of the core electrons in the cyclopentane system does decrease, an increase in binding energy occurs within the surrounding benzene rings. The greater distribution of carbons within these rings results in an overall increase in apparent binding energy, with only very mild increase on the low binding energy side. Despite this, these shifts are not considered significant based on the errors associated with this analysis. 159

182 A B Figure 7. Effect of (A) cyclopentane defect and (B) cycloheptane defect on core binding energies. Values A-C give the respective shift of the calculated binding energies for each unique position relative to the average binding energy calculated for coronene ( ev). The black line denotes the calculated spectrum for the cyclopentane centered ring system shown, while the red dashed line is that of coronene. In contrast to the effect of cyclopentane, inclusion of larger rings such as cycloheptane, see Figure 7B, results in a significant increase of 0.57 ev in binding energy for carbon core electrons associated with the large ring system. Similar to the cyclopentane results, a contrasting, but not significant, decrease is observed for those carbons in the adjacent benzene-like rings, and because of the greater density of these carbons, the defect results in an apparent binding energy reduction compared to unmodified coronene (dashed red line). A summation of these effects can be seen in the Stone-Wales defects introduced into polyaromatic parent structures. Figure 8A details the structure and binding energy shifts associated with circumpyrene, while the simulated spectra for this defect in coronene, circumpyrene and circumcoronene are detailed in Figure 8B. Detailed figures for coronene and circumcoronene are 160

183 provided in Appendix B section B4, Figure B5. The results indicate that ring structures containing more than 6 carbons result in mild to moderate increases in the associated binding energies, while carbons present in cyclopentane rings experience a moderate reduction in binding energy. The defect introduced into coronene resulted in a portion of the cyclooctane ring system as well as much of the cyclopentane rings to exist as edge sites in the polyatomic structure. Under these conditions the binding energy shift associated with each defect was substantially reduced. This resulted in less severe tailing at low binding energies than was observed for defects in either circumpyrene or circumcoronene. While changes to the spectra are apparent when using the averaged parameters obtained from the model compound analysis, pertinent to the XPS system used for this study, the impact of defects is far more evident when the FWHM is reduced to 0.5 (Figure 8C). This resolution is not possible on the equipment used here, as the line broadening from the achromatic Mg x-ray source alone exceeds 0.7 ev; however, these substantially improved resolutions are possible with a synchrotron X-ray source as shown by Blume et al. [13]. Using this source the authors identified the formation of two additional C-C peaks shifted +0.4 and 0.4 ev from the primary peak. These peaks were approximately equal in nature and agree very well with the position and behavior noted here for a Stone-Wales defect in circumcoronene, which have been postulated to form as a result of argon bombardment [29]. Though these structures are likely not the exact form to be found in amorphous chars, the nature of the defects presented in Figures 6-8 are informative regarding potential structures. 161

184 A A = 0.89 ev B = 0.74 ev C = 0.57 ev D = 0.87 ev E = 0.21 ev F = 0.18 ev G = 0.06 ev H = 0.10 ev I = 0.40 ev J = 0.35 ev B Circumcoronene Circumpyrene Coronene C Circumcoronene Circumpyrene Coronene Figure 8. (A) Effect of Stone Wales defect on core binding energies in circumpyrene parent system, values A-J give respective calculated binding energy shifts relative to the average shift of coronene, ev, bold denotes significant shifts, values in red are negative shifts (B) Simulated C1s plots for defects in (black lines) and unmodified (dashed red lines) coronene, circumpyrene and circumcoronene parent systems with FWHM of 1.56 and G:L = 0.55 for each atom (C) Spectra from B with FWHM reduced to 0.5. Individual binding energies for coronene and circumcoronene are given in Appendix B section B5. 162

185 Effect of oxygen on C1s binding energies for bound and nearest neighbor carbons The effect of oxygen on the binding energy of adjacent carbons is well known throughout the literature. However the long range effects of oxygen is not typically considered. The examination of heavily oxygenated carbon species, such as PTCDA demonstrates that the presence of oxygen can have significant effects even on non-adjacent carbons (see Figure 6C). In this case, long range effects resulted in a calculated binding energy shift of approximately 1.2 ev for all non-adjacent carbons. Without accounting for this effect, a preliminary analysis of the spectrum would suggest that the system was composed entirely of carboxyl and hydroxyl or ether bonded carbons. To determine the effects of individual functional groups on the binding energy distribution of small aromatic compounds, the effects of various oxygen groups, shown in Figure 9 for coronene, were examined. Analysis of the effects of oxidation on a variety of carbon sites, Table 7, yields results consistent with those obtained for the coronene. From these results, the position of the hydroxyl bonded carbon is estimated to be shifted ev from the primary carbon peak. Carbonyl groups are estimated to cause shifts of ev while carboxyl and lactone groups resulted in shifts of 4.2 to 4.5 ev. All results are within the parameters published for such groups[53]. Lactone groups, being directly bonded to two carbons, show equal signal intensity in the same region as carboxyl groups and near hydroxyl groups. Because of this care must be taken in quantification when lactones or esters are present, or the oxygen content will be overestimated. Carboxylic groups were also found to have a moderate effect on the next nearest carbon, resulting in a positive binding energy shift of ev relative to the unmodified parent. Each functional group, aside from hydroxyls, in each configuration, was found to shift the overall binding energy of the rest of 163

186 the cluster by an average of ev. Though mild, these shifts are strong enough to account for at least some of the defect peak considered near ev. Figure 9. Binding energy shifts in adjacent, as well as second nearest neighbors associated with (A) hydroxyl (B) carbonyl (C) carboxylic and (D) lactone groups. Group A represents the average reference shift for C-H atoms, while B is the average shift of C-C in each compound. All shifts are relative to the original binding energy of atoms at the same relative position in the parent coronene 164

187 Table 7. Calculated binding energies for various oxygenated functional groups positioned on assorted carbons. Lactone and carboxylic group (1) refers to the carbon connected to both oxygens. Lactone (2) refers to the ether bonded carbon, while carboxyl (2) refers to the carbon adjacent to the carboxyl group. Model Compound Binding energies for carbons associated with listed functional group (ev) Carboxyl Carboxyl Hydroxyl Carbonyl Lactone (1) Lactone (2) (1) (2) Coronene defect pentane ring Alkane side chain Summary of peak interpretations and constraints From the simulation results reported here, a general interpretation of deconvolution peaks is proposed in Table 8. These interpretations require assessment of treatment temperatures and potential functional group distributions to accurately interpret, as several overlapping features do exist. The FWHM has been set to 1.2 to 2 ev for the C-C peak region based on the results for known compounds discussed previously, and the assumption that binding energy distributions within each peak region will be low. Because of this assumption, a relatively large G:L ratio is allowed for with the bounds set to vary from based on the pure compound results as well. A larger ev FWHM range is given for C:O peaks to allow for broadening due to a 165

188 distribution of groups. This broadening effect is also associated with increasing Gaussian character and so the range of the G:L ratio here has been reduced to Table 8. Peak assignments and parameters for the interpretation of O1s and C1s spectra of chars Peak Assignment BE (ev) FWHM (ev) G:L (0-1) O-C(1) Ether and hydroxyl groups bonded to aromatics O-C(2) Ether and hydroxyl groups bonded to aliphatics & carbonyl shake-up O=C In carbonyl, lactone and carboxylic groups (H 2O) Absorbed water/oxygen, sub monolayer C-C low Cyclopentane ring atoms within cluster C-C Primary Primary C-C/C-H peak C in cycloheptane or larger rings within clusters, C-C High C-O C=O C in small clusters containing C=O bonds, sp3 bonded carbons Ether and hydroxyl bonded C, C associated with ether bond in lactone/esters Carbonyl groups and carbons attached to two ether/hydroxyl groups COO Carboxyl, lactone and ester groups Pi-Pi* HOMO-LUMO transition for primary C-C peak Constrained C1s Deconvolution procedure Based on the results of the preliminary fitting given in section 3.1 and the molecular modeling results informing the nature of shifts in C1s peaks shown in section 3.2 a new deconvolution method is proposed for pyrolysis chars. An outline of this procedure is provided in Figure

189 This method employs the full range of C1s curves utilized by Blume et al. [13], as well as the deconvolution peaks from the related O1s spectrum as additional constraints to allow for more consistent assignment of the C-C region as well as defect peaks. For this, the total peak area of each deconvoluted O1s spectrum is used to specify upper and lower constraints for the three oxygenated peaks identified in the C1s spectra as well as their sums. The oxygen constraints are estimated based on maximum and minimum distributions for eight potential carbon sites in six oxygenated groups. These sites, highlighted in bold, include: carbon liked to a single oxygen, hydroxyl groups (C-OH), ether groups (C-O-C), and the ether linked carbon in lactone/ester groups (COOC); carbons linked to two oxygen bonds, carbonyl groups (C=O), and carbon linked to two ether/hydroxyl bonds (O-C-O); and carbon linked to three oxygen bonds; carboxyl groups (COOH), and the primary carbon in lactone/ester groups (COOC). Ether and hydroxyl groups resolve near ev and show C:O ratios of 2:1 (maximum) and 1:1 (minimum) respectively, the final distribution of these groups is estimated by the distribution coefficient DHE. Carboxyl and Lactone groups resolve near 289 ev. Carboxyl groups show a C:O ratio of 1:2 while lactone and ester groups result in a 1:1 ratio for the peak at 289 and result in a second peak near ev, indistinguishable from ether like carbons. The final distribution of carboxyl and lactone groups is given by the distribution coefficient DCL. 167

190 Survey scan, O1s and C1s high resolution scans, additional high resolution scans if needed Desired Peaks Bounds for all free parameters See Table 8 for recommended conditions Evaluate survey scan for all elements present Lock the asymmetry parameter (TS) at 0 for the primary C-C peak Yes Did the Carbon show Charging? No Specify the maximum allowable asymmetry (0.20 is recommended for chars) Select desired peak and correct peak position Binding Energy likely shifted 1-2 ev Correct peak position to ev for C-C bonds Binding Energy likely <0.5 ev Apply baseline correction to O1s Peak Deconvolute O1s peak using 4 symmetric GLsum peaks, repeat until fit reaches minimum Calculate maximum and minimum apparent C-O/C=O/O-C=O, total C-O, total C=O and total C:O bonds as shown in Equations S2-S12 Correct O-C and O=C values as needed if additional compounds (eg CaO) are present Deconvolute C1s peak using input bonds and bonds from the O1s Deconvolution, repeat until fit reaches minimum Adjust initial guess parameters and reoptimize No Reasonable fit achieved? Yes Optimize DHE, DCL and C:O ratio by comparison of C1s and O 1s deconvolution results using equations S13-S15 Additional adjustment of fitting parameters required for material Multiple No reasonable agreement No (<10% error)? Yes Evaluate survey scan for additional elements, reevaluate assignments for non C/O deconvolutions, adjust initial guess for O1s and C1s Peaks O1s and C1s fit results and parameters End Figure 10. Basic algorithm for the combined O1s/C1s deconvolution of XPS spectra of chars and amorphous carbons. 168

191 To estimate the potential contribution of O-C-O to the carbonyl peak region, the probability of 2 C-O bonds forming on the same carbon is estimated. This is done by assuming a random distribution of carbon and oxygen atoms with 3 carbons or oxygens bonded to each carbon. The distribution of O-C-O and C=O groups is uncertain as no distinctive peaks are available from the O1s spectra to guide this deconvolution. To estimate the quantity of carbonyl like groups, the quantity of C=O oxygen associated with the carboxylic/lactone peak from the C1s deconvolution is subtracted from the quantity determined from the O1s C=O peak. The remainder is assumed to be carbonyl carbon. The estimated carbonyl carbon can be subtracted from the C1s C=O peak to give the fraction of O-C-O. These parameters are detailed by equations B2-B12 in the Appendix B section B3. Equations B13-B15 detail the estimation of each O1s peak from the C1s deconvolution. Application of this quantification method predicts a DHE value of 0.57, or 4 or 7 oxygen bonds related to ether. This result is highly consistent with the presence of the 2 ether groups and 3 hydroxyl groups within each monomer unit of cellulose Application to cellulose char thermoseries Figure 12A and 12B respectively show the deconvolutions for the C1s and O1s spectra from C600. The defect peak positioned near 284 ev is assigned to both hydrogenated carbons and small rings (C5 or less) within larger aromatic systems. This peak has not been found to decrease consistently with temperature, from 11% to 3.5% as temperature increased from 400 o C to 700 o C. This result suggests that a reduction of total small ring systems occurs with higher treatment temperatures. The fractional distribution of each group obtained from the C1s deconvolution of spectra from cellulose chars are given in Table 9 and show consistent temperature trends. Additional details 169

192 regarding peak position and peak width are given in Tables B1 and B2 respectively in Appendix B section B5. A B Figure 11. Deconvolution of (A) C1s and (B) O1s spectra from C600. The primary C-C peak shows strong development with treatment temperature, and a consistent narrowing of the FWHM as temperature increases from 400 o C to 700 o C, indicting the formation of an increasingly regular aromatic structure. The asymmetry factor has been found to increase with treatment temperature. While an asymmetric C-C peak was not identified for chars produced at or below 500 o C, it quickly develops for materials as treatment temperature is increased above 500 o C. This trend is consistent with the charging effects (or lack of) observed for each sample, and is indicative of the formation of increasing aromatic condensation [31]. 170

193 Table 9. Peak distribution and C:O ratios determined using proposed deconvolution scheme Deconvolution peaks Cellulose C300 C400 C500 C600 C700 C-C low (%) C-C Primary (%) TS (asym. factor) C-C High (%) C-O (%) O-C-O/C=O (%) O-C-O estimated COO (%) Pi-Pi* (%) D HE D CL C:O (C1s) C:O error (%) The defect peak noted near 285 ev develops rapidly to 27% of the C1s spectrum as treatment temperature increases to 500 o C. This is linked to the formation of relatively large rings (C7+) and may also result from the presence of double bonded oxygen on small ring systems. As temperature increases further, these oxygen groups are reduced and irregular ring systems rearrange to form more stable six carbon rings causing a reduction in this peak to approximately 9% at 700 o C. As with the primary C-C peak, a consistent reduction in peak width is noted as temperature increases, suggestive of an increasingly regular structure. The peak associated with ether and hydroxyl groups decreases rapidly and consistently with treatment temperature, falling from 66% of peak intensity for cellulose to just 4% for C700. This reduction is associated with a rapid loss of hydroxyl groups as pyrolysis temperature is increased to 400 o C, as demonstrated by the rapid increase in the DHE coefficients in Table 8. This is followed 171

194 by continued reaction and loss of ether groups. The distribution of hydroxyl groups begins to increase again at 500 o C and stabilizes near a 1:1 distribution at 600 o C and 700 o C. This result is attributed to the initial chemisorption of oxygen at radical sites immediately following pyrolysis. The carbonyl peak shows additional signal from carbons bonded to two ether groups. These O-C- O are the primary contributions to this peak for cellulose and C300. The quantity of this contribution is estimated based on the assumption of a randomized distribution of ether/hydroxyl groups, and assumes that the fraction of O-C-O groups is equal to the square of the O-C fraction. This contribution becomes relatively unimportant at treatment temperatures of 400 o C or higher, resulting in contributions of 2.3% or less. The results indicate no significant quantity of carbonyl groups at any temperature, suggesting that these groups tend to form most stably instead as either carboxyl groups or lactone/esters. Carboxyl/Lactone groups do not form significantly until treatment temperatures of 400 o C or higher are reached. As temperature is increased above 500 o C minor decreases in total contribution are noted. The contribution of lactone groups is highest at 400 o C, however rapidly gives way to carboxyl groups as temperature increases, see the DCL ratio in Table 8. This result is in contrast to the typical stability observed by temperature programed desorption, which shows carboxyl groups unstable at temperatures above 300 o C, where lactones show stability between 500 o C and 700 o C. The observed increase in carboxyl fractions, as with the increase in hydroxyl content discussed previously, is linked to chemisorption of oxygen at radical sites upon first exposure to air. These strong shifts are consist with, and required, to explain the large increase in surface oxygen content compared to bulk shown in Figure 2B for chars produced at temperatures of 500 o C and higher. 172

195 Overall, the results of deconvolution using this new method are highly internally consistent and was capable of reproducing each spectra accurately without deviation from the stated protocol. These results provide functional group distributions for a range of chars produced between 300 o C and 700 o C that are consistent with expected behaviors. The current set up was however unable to provide conclusive structural information from the C-C region. Analysis by equipment with increased resolution, such as that afforded by synchrotron x-ray sources, may be able to more conclusively resolve features within this region. 3.4 Conclusions A new curve fitting procedure has been proposed for amorphous, oxygen containing carbons that utilizes deconvolution of the O1s peak as a boundary parameters for the interpretation of the C1s peak. The deconvolution of C1s was modified by taking into account the result of molecular modeling studies. Molecular simulations provided insight into the origin of each peak. These results indicate that the peak near 285 ev results from a variety of defects including weak to moderate long range shifts of C-C/C-H binding energies in oxygen containing molecules, aromatic rings larger than benzene, and dehydrogenated sp 3 carbons. The defect peak that is present at lower binding energies has been linked to aromatic regions containing small rings such as cyclopentane. Using this method, C1s deconvolutions were obtained that provide an arcuate fit to the complementary O1s data. A generalized oxygen quantification scheme is given that utilizes two distribution coefficients DHE and DCL for the interpretation of oxidation peaks. This method allowed for reasonable interpretation of the C-C peak asymmetry as well as secondary defect peaks. 173

196 Acknowledgement: The authors are very thankful for the financial support provided by the Agricultural Research Center (NIFA-Hatch-WNP00701), the Washington State Department of Ecology, and the Washington State Department of Agriculture (Appendix A). J.-S. M. acknowledges the financial support from the US Department of Energy (DOE), Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences under award number DE-SC Dr. Espinal thanks partial support from the Programa Sostenibilidad of the University of Antioquia. 174

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205 Appendix B Supplemental Material for Chapter 3 B.1. XPS Deconvolution Figures Figure B1. Various deconvolution schemes utilized for chars and activated carbons in the literature using the C400 C1s spectrum as a reference. (A) Basic Deconvolution (B) inclusion of Defect/sp 3 carbon peak (C) implements both C-C peaks from B and adds an additional defect peak shifted -0.4 ev from the primary C-C peak (D) use of an asymmetric primary C-C peak (E) use of both a defect/sp 3 peak and asymmetric primary C-C peak (F) uses the same peaks as described in D with the addition of a low energy defect C-C peak 183

206 B.2 Asymmetric line shape for primary C-C peak Peak asymmetry of the primary C-C band for chars produced at elevated temperatures is most likely a result of secondary emissions effects. This effect is linked to the increased aromatic condensation of these materials and is a well-known effect in both graphites and activated carbons. Proper consideration of the asymmetry factor of the primary C-C peak is essential for the accurate deconvolution of the C1s spectrum. This asymmetry is attributed to the excitation of conduction band electrons following a core emission, and has been previously described analytically by Doniach and Sunjic [1] for metallic systems. The final analytical description is based on a Lorentzian type curve and is given in equation 4. a [pi DS(x, a, F, E) = cos 2 + (1 a) tan 1 x E ( F )] (F 2 + (x E) 2 ) 1 a 2 Eq. S1 Figure B2. Comparison of empirical asymmetry equation to DS line shape for (A) uncorrected and (B) Shirley background corrected DS line shape. Black line is DS line, dotted black line empirical line-shape with TL = 200, red dots empirical line shape with TL = 600. Asymmetry parameters alpha=ts =

207 A comparison of the DS line shape with the empirical asymmetry factor before and after the effects of background subtraction is presented in figure A3A. While the DS line shape provides excellent reproduction of asymmetric features, the tail will only approach 0 asymptotically but does not converge. When used in conjunction with a converging, empirical background, designed to limit total asymmetry, specifically the Shirley background employed here, this has the potential to under estimate binding at higher oxidation states. To limit this effect, the empirical asymmetry estimation used in XPSpeak 4.1, see the final TS term equation 3, has been optimized to best fit the DS equation between 284 and 290 ev for use at low asymmetry factors (alpha = ). Based on this optimization, assuming a TL value fixed at 600 provides excellent reproduction of the uncorrected DS line-shape, while using the maximum value available in XPSpeak4.1 (TL =200) results in significant underestimation. However, if it is assumed that a portion of the DS line shape is corrected by application of a Shirley type background the results change substantially. When a Shirley type background is applied to the DS equation results, Figure B3B, the empirical asymmetry equation is found to fit most accurately at a TL value of 200. To maintain consistency with both background assessment and peak shape, the asymmetric primary C-C peak near ev is evaluated using the full empirical AGLsum line-shape given in equation 3, with TL fixed at

208 B.3 Oxygen bracketing equations B.3.1 Individual C1s peak constraints Below are explicit statements of the bounding equations used in the combined O1s C1s deconvolution employed here. In these equations Peak XO1s refers to the total area of the O1s deconvolution peak referenced (see Table 1 of the main text), while peak XC1s is that of the referenced C1s deconvolution peak. SF referrers to the instrument specific relative sensitivity factor of the O1s peak compared to C1s, in this case peak 4 C1s (Lower) = [peak 2 O1s + peak 3 O1s peak1 O1s ] 0.9 SF Eq. B2 The peak 4C1s lower bound equation assumes that the entire contribution of C-O oxygen is from either hydroxyl or carboxyl groups, where each oxygen detected is related to a single carbon. A 10% negative error is included. peak 4 C1s (Upper) = [peak 2 O1s + peak 3 O1s ] SF Eq. B3 This equation assumes that all C-O is present as ether groups that relate to two carbons and that all C=O oxygen is contributed by carbonyl groups, eliminating potential interference from carboxyl and lactone groups A 10% positive error is also included Peak 5 C1s (Upper) = [peak 1 O1s + 3 A 2 (1 A) (peak 2 O1s + peak 3 O1s )] 1.1 SF Where: 186

209 A = peak 2 + peak 3 SF Area C 1s + Area O 1s Eq. B4 The origin of C=O bonds identified in peak 1 cannot be directly determined as the associated shifts vary only slightly. For the upper bound, the entirety of peak 1 is assumed to relate to carbonyl groups. The upper bound for peak 5C1s peak, Eq. B4, has also been allowed to expand to include potential contribution for O-C-O groups. This contribution is estimated by assuming 3 carbon/oxygen bonds per carbon and the ratio of oxygen atoms single bonded to a carbon vs total atoms (A in Eq. B4). From these assumptions the likelihood of two oxygens being bonded to one carbon by single bonds is calculated based on a statistical distribution. While this is an oversimplification for complex organic matter with defined structure and char materials due to varying thermal stability it is unlikely to under predict potential O-C-O contributions. A 10% error has also been included. peak 6 C1s (Upper) = [peak 1 O1s ] 1.1 SF Eq. B5 The origin of C=O bonds identified in peak 1O1s cannot be directly determined as the associated shifts vary only slightly. For the upper bound, the entirety of peak 1O1s is assumed to relate to carboxylic, lactone or ester groups. peak 5 C1s (Lower) = peak 6 C1s (Lower) = 0 Eq. B6 187

210 The lower bound for both peak 5C and peak 6C is 0. This can be achieved by assuming that the total contribution of peak 1O1s is from either peak 5C1s or 6C1s. B.3.2 Constraints on the summation of C1s peaks peak 5 C1s + peak 6 C1s (Upper) = peak 5 C1s (Upper) Eq. B7 The sum of peaks 5C1s and 6C1s is constraint to a maximum of the upper bound for peak 5C1s. Because all C=O bonds are accounted for in this group, as is any potential O-C-O contribution, any carboxylic or lactone character must necessarily result in a reduction of peak 5C1s from the maximum. Peak 5 C1s + peak 6 C1s (Lower) = peak 1 O1s 0.9 SF Eq. B8 The lower bound for the sum of peaks 5C1s and 6C1s assumes no contribution from O-C-O groups, limiting the potential source of intensity to that identified by peak 1O1s. A 10% error has been included. 6 peak i C1s i=4 (Upper) = [peak 1 O1s + 2 peak 2 O1s + 2 peak 3 O1s ] 1.1 SF Eq. B9 188

211 6 peak i C1s (Lower) i=4 peak 1 O1s, peak 2 O1s + peak 3 O1s < peak 1 O1s = { [peak 2 O1s + peak 3 O1s ] 1.1 SF, peak 2 Eq. B10 O1s + peak 3 O1s peak 1 O1s The upper and lower bounds for total oxygen are assigned based only on the first 3 assigned peaks and assume a 10% margin for error. B.3.3 Estimation of Peak 5C1s contributions The contribution of carbonyl and double ether/hydroxyl groups to peak 5C1s cannot be directly determined. To estimate these contributions, the estimated content of carboxyl/latone/ester groups (peak 6C1s) is subtracted from double bonded oxygen determined from the O1s spectrum (peak 1O1s). This leaves the theoretical contribution of carbonyl groups, Eq. B11. By subtracting this contribution from Peak 5C1s the contribution of double ether/hydroxyl groups is determined. peak 5 C1s (C = O) = [peak 1 O1s ] SF peak 6 C1s peak 5 C1s (O C O) = peak 5 C1s peak 5 C1s (C = O) Eq. B11 Eq. B12 B.3.4 Estimated O1s peaks Deconvolution of the oxygenated C1s region can be checked by comparing the theoretical oxygen content to the measured values from the O1s contribution. Estimation of Peak 1O is given by 189

212 equation XX and is a straight forward addition of the carbonyl and carboxylic/lactone/ester peak contributions (peaks 5C1s and 6C1s) with the estimated double ether/hydroxyl groups removed. Estimation of the single bonded oxygen concentration (equal to the sum of peak 2O1s and 3O1s) is more involved, requiring the use of the distribution coefficients discussed in the main text. The DHE coefficient denotes the distribution of ether and hydroxyl bonds (not technically groups, but this variance is small when peak 5C1s (O-C-O is small), while DCL is the carboxyl-lactone coefficient. These coefficients may be specified by the user or optimized by minimizing the error between the measured and calculated values peak 2 o1s + peak 3 (estimated) = [(1 D HE 2 ) [peak 4 C1s peak 6 C1s D CL + 2 peak 5 C1s (O C O)] + peak 6 C1s ] SF Eq. B13 peak 1 O1s (estimated) = peak 6 C1s + peak 5 C1s (C = O) Eq. B14 O1s (estimated) = peak 1 O1s (estmiated) + peak 2 O1s estimated + peak 3 O1s (estimated) + peak 4 O1s (meassured) Eq. B15 190

213 B.4 Detailed binding energy distributions for assorted compounds presented in the text 191 Figure B3. Calculated C1s core binding energies relative to the average calculated binding energy of coronene ( ev) are given for each lettered assignment for (A) Pyrene (B) cellobiose and (C) PTCDA. (D) Calculated O1s binding energies for each oxygen in cellobiose. These values are used to calculate the respective spectra given in figure 4 of the main text. Bold values denote shifts from the coronene reference greater than 0.4 ev. Red values indicate negative shifts.

214 Figure B4. Calculated C1s binding energies for (A) alkane and (B) alkene chain modified coronene structures as discussed in Figure 6 of the main text. Only coronene modified with 2 chains are shown here, however the effects for a single chain are highly similar. All shift values are given relative to the average calculated binding energy of coronene at ev. Bold values indicate shifts greater than 0.4 ev while red values indicate negative shifts. 192

215 Figure B5. Calculated C1s binding energies for stone-wales defect inclusions in (A) coronene and (B) circumcoronene, as discussed in Figure 8 of the main text. All shift values are given relative to the average calculated binding energy of coronene at ev. Bold values indicate shifts greater than 0.4 ev while red values indicate negative shifts. 193

216 B.5 Additional C1s peak tables for cellulose deconvolution Table B1. Peak positions for all peaks used in the deconvolution of cellulose chars Samples Peak cellulose C300 C400 C500 C600 C700 C-C low Defect C-C Primary C-C High Defect C-O C=O COO Pi-Pi* Table B2. Full Width at Half Maximum values used for all peaks in the deconvolution of cellulose chars. Samples Peak cellulose C300 C400 C500 C600 C700 C-C low Defect C-C Primary C-C High Defect C-O C=O COO Pi-Pi*

217 B.6 References [1] Doniach S, Sunjic M. Many-electron singularity in X-ray photoemission and X-ray line spectra from metals. Journal of Physics C: Solid State Physics. 1970;3(2):

218 Chapter 4: Effect of Pyrolysis Temperature on Cellulose Char Aromatic Cluster Size by Quantitative Multi Cross-Polarization 13 C NMR with Long Range Dipolar Dephasing To be submitted to Carbon Matthew Smith 1,2, Greg Helms 3, Jean-Sabin McEwen 2, Manuel Garcia-Perez 1 1 Department of Biological Systems Engineering, Washington State University, Pullman, WA 99164, USA 2 Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Pullman, WA 99164, USA 3 Department of Chemistry, Washington State University, Pullman, WA 99164, USA 196

219 Abstract: Spectroscopic analysis of chars has remained a challenging task due to the amorphous, heterogeneous nature of the material. While a variety of techniques have been employed to characterize structures, none offer the potential capacity for direct quantification of the full material as well as NMR. Previous efforts to analyze chars via NMR have employed costly direct polarization techniques and interpreted the results based on regular aromatic structures. While these results have been critical in understanding the development of cluster sizes within these materials, recent results obtained by Raman spectroscopy as well as Transmission Electron Miscopy have begun to highlight the importance of irregular structures within these materials. DFT simulation results performed here, suggest that larger irregular ring systems contribute strongly to asymmetry often observed in the aromatic peak near 140 ppm. By combining a recently developed cross-polarization pulse sequence designed for quantitative analysis of even low hydrogen containing materials with long range dipolar dephasing, the structure of a thermoseries of chars produced from cellulose is examined. These results demonstrate the consistent growth of cluster size with pyrolysis temperature, and examine for the first time the distribution of ether groups and defects within the cluster. The prevalence of oxygenated and defect carbon sites throughout the aromatic clusters highlights the need for additional characterization of these materials as these sites are likely to offer substantially different reactivity s and adsorption behavior compared to regular aromatic structures. Keywords: NMR, MultiCP, Char, Defects, CPMAS, Cross-polarization Magic-Angle Spinning 197

220 4.1 Introduction Carbonaceous materials formed from the pyrolysis of lignocellulosic materials are complex polyaromatic systems decorated with oxygenated functionalities [1-4]. A growing body of research has examined the reaction pathways associated with char formation for biomass [5-8] and purified constituents, such as cellulose [3, 9-13]). These results indicate that the initial stages of pyrolysis, temperatures up to approximately 330 o C for cellulose, consist almost entirely of dehydration and depolymerization reactions [2, 9, 11, 14-17]. As temperature increases a range of depolymerization, dehydration and crosslinking reactions occur leading to substantial mass loss from the solids and the initial formation of a range of aromatic ring systems [5-9]. At higher temperatures (over 500 o C) polycondensation becomes prevalent [2, 18-22] leading to aromatic systems with a higher degree of aromaticity[23, 24], though once crosslinked these structures typically resist the formation of crystalline regions [25]. While these results are critical to our understanding of how chars form, the underlying chemical structure remains poorly explored and is very often modeled using idealized systems [23, 24]. Combustion and thermogravimentric analysis of chars have been used to detail critical compositional information, including elemental composition and proximate composition. While the results provide little direct structural detail, these bulk properties are relatively simple to collect and essential to understanding the basic chemistry of chars. Additional structural information can be determined by spectroscopic techniques such as FT-IR [3, 26, 27] and X-ray Photoelectron Spectroscopy (XPS) [28-30], which can identify a wide range of elements and bonding patterns. Raman spectroscopy [31-35] and X-ray diffraction (XRD) [16, 36, 37] techniques also provide 198

221 excellent tools for the analysis of graphitic materials. However, the size analysis of the small aromatic clusters found in pyrolysis chars by these spectroscopic methods is uncertain. Several challenges arise due to the amorphous structure of the material that precludes clear crystallite peaks from XRD [38, 39]. These same structures, identified as a series of defects, result in a defuse defect region in the Raman signal between 1200 and 1400 cm -1 [4]. Similar defects have been more directly observed by transmission electron microscopy (TEM) [40, 41]. While these methods do provide sound tools for qualitative analysis, quantification by methods such as Raman are difficult due to varying vibrational intensities [42]. Nuclear magnetic resonance (NMR), by contrast offers a potentially quantitative method of analysis, since signal intensity from well-designed experiments are proportional to the distribution of spin states within the compound. NMR spectroscopy offers a unique method of analyzing these materials via rotational-echo, double resonance (REDOR) type experiments. This method relies on a series of pi-pulses spaced at 1 rotor period over the dephasing period to ensure decoupling heteronuclear interactions [43], and was successfully applied by Mao and Schmidt Rohr to selectively assess the aromatic region of humic material and chars [44]. This series is required, because at dephasing times greater than one rotor period magic angle spinning (MAS) can partially refocus heteronuclear interactions. This technique was successfully applied by Brewer et al. [23] to estimate average aromatic structures of slow, fast and gasification chars. The results of this study indicate cluster size of approximately 7 rings for fast pyrolysis chars produced 500 o C and 17 rings for gasification chars produced near 750 o C. These results are in good agreement with those of McBeath et al. [24] who predicted ring clusters of up to 13 rings with pyrolysis temperatures of o C, by analyzing the up field shift of sorbed 13 C labeled benzene [45]. 199

222 A fundamental limitation of the direct quantitative analysis of aromatic carbons has been the need to use direct polarization to provide equivalent polarization to all carbons within the aromatic systems. This polarization method requires substantial recycle delays, on the order of one to several minutes per scan to allow complete longitudinal relaxation (T1) of the polarized carbon [44]. While reasonable signal can still be obtained via cross-polarization (CP), which requires substantially shorter recycle delays due to the more rapid relaxation of hydrogen, tertiary and quaternary carbons do not achieve the same degree of polarization as primary or secondary carbons, eliminating this method as a quantitative tool [44]. A recent method published by Johnson and Schmidt-Rohr [46] overcomes this limitation through the use of multiple CP passes which successively build the polarization within the internal aromatic structure. The optimized contact time and CP passes is determined by comparison to direct polarization, and once determined allows for the collection of high resolution spectra in a fraction of the time required for DP experiments. This method was used for the analysis of humic acid, switch grass and low temperature pyrolysis char [46]. Though several studies have examined the average chemical structure of char by various NMR techniques, each assessment assumes a regular aromatic structure to interpret the results [23, 24]. Defects such as those identified by TEM and Raman studies have not yet been incorporated in the analysis of these spectra. These defects affect both the overall structure of the char by precluding the formation of planar regions, and the reactivity of the char though increased reactive defect and edge sites. Because of these effects, developing a clearer understanding of these materials is critical to understanding the behavior of chars in real systems. The literature on how the aromatic ring 200

223 structure grows as a function of pyrolysis conditions is also very limited. Thus, the main goal of this paper is to study the effect of pyrolysis temperature on cellulose char aromatic cluster size by quantitative multi cross-polarization 13 C NMR with long range dipolar dephasing. 4.2 Materials and Methods Avicel Cellulose purchased from Sigma Aldrich (LOT# BCBG9043V) was used for the production of a thermoseries of chars. Douglas fir (Pseudotsuga menziessii) wood (DFW) was provided by Herman Brothers Logging & Construction (Port Angeles, WA) from standard mill operations. A torrefied sample was utilized for method tuning. Perylene tetracarboxylic dianhydride (product# P11255) has been used as received as a reference compound to assess the NMR pulse sequences used here. Cellulose and Douglas fir wood (DFW) chars have been produced following the same methods previously described using a spoon reactor at WSU [3, 4]. Treatment time was 30 minutes at a specified fixed temperature (300, 400, 500, 600 and 700 o C for cellulose and 300 o C for DFW) with a constant nitrogen sweep of 300 ml/min. A preheated nitrogen sweep of 550 ml/min was employed in the reaction zone to minimize vapor residence time. The test chamber was purged for 10 minutes prior to pyrolysis to ensure an oxygen free environment. Samples were allowed to cool under nitrogen in a water-jacketed region of the reactor for 20 minutes to ensure sample temperatures of less than 25 o C were obtained prior to exposure to air. All samples were weighed immediately and stored in glass vials until testing. 201

224 4.2.1 X-ray Diffraction X-ray diffraction patterns have been collected using a Rikagu MiniFlex 600 benchtop X-ray defractometer. Diffraction spectra were collected between 2θ of 5 to 50 degrees at constant scan rate of 1 degree per minute. To ensure representative samples the sampling pan was rotated during acquisition NMR Spectroscopy Solid-state NMR data was collected at ambient temperature on a Bruker Avance DRX 400 spectrometer at MHz for 13 C using Chemagnetics 5mm and 3.2 mm probes. Rotors were filled completely and either Teflon or boron nitride spacers were used to constrict the sample to just the region of the coil. Samples were spun at either 7 KHz or 10 KHz for the 5mm rotor or at 10 KHz for the 3.2 mm rotor. To ensure flat baselines acquisition of all data was done using a Hahn-echo applied for 1 rotor period directly following the last cross polarization period or directly following the direct polarization pulse. For the 5mm probe the π/2 pulse widths were 4.0 and 4.7 μs for 1 H and 13 C respectively while for the 3.2 mm probe the π/2 pulse widths were 4.7 and 4.6 μs for 1 H and 13 C respectively. Decoupling during acquisition and during the Hahn-echo was accomplished using TPPM modulation and RF fields (γb1/2 π) 62.5 KHz and 60 KHz for the 5mm and 3.2 mm probes respectively. Cross polarization periods for 1 H were constructed using a 64 step linear ramp from 50 to 100% of amplitude. Recycle delays for cross polarization experiments were 4s whereas for direct polarization recycle delays were either 90 s or 135 s. Durations for the repolarization delay (Z) in the multi-cp sequences were either 500ms or 1s depending on the sample. Acquisition time for all experiments was 7.8 ms with a spectral width of 50,000 Hz. Data were apodized with 50 Hz of exponential line broadening and zero filled to 2K points prior to 202

225 Fourier Transform. For multi-cp based sequences a total of 2048 scans were acquired. For direct polarization sequences a total of 256 scans were acquired Direct Polarization Scheme Quantitative reference spectra for DFW chars and select cellulose chars have been collected. Direct polarization spectra were collected using pulse sequence B in Figure 1 with a 90 degree excitation pulse on 13 C with acquisition following a Hahn-echo and TPPM decoupling used throughout. Recycle delays of 90 seconds are used for all samples except C700 for which a recycle delay of 135 seconds was required. Recycle delays of 90, 180 and 420 seconds were also performed during the analysis of PTCDA. Spectra for DFW samples were collected using a 5mm rotor with a spin rate of 7K Hz. A very broad peak was observed within the aromatic region in the direct polarization spectra, which was attributed to Teflon components used in the construction of stater. This background persisted even when using boron nitride spacers and was corrected for by collecting a background signal using the same rotor packed with silica gel under identical pulse and acquisition parameters. To lessen background contamination during dephasing trials and to mitigate potential arcing in conductive samples (higher temperature chars) a smaller 3.2 mm rotor was used. A spin rate of 10K Hz was also employed for the 3.2 mm rotor to reduce side band contributions relative to the 7K Hz spin rate used initial. 203

226 MultiCP scheme The multiple cross polarization scheme (MultiCP) introduced by Johnson and Schmidt-Rohr [46] has been employed in this work to produce quantitative spectra approaching direct polarization results while significantly reducing the total time required for data collection. Data was collected using pulse sequence A in Figure 1 wherein a series of ramped cross polarization periods is employed to successively build polarization at carbon sites distant from any proton spin until a quantitative spectrum can be obtained. Contact times of 0.5 or 1.0 ms were used employing a 50 to 100% linear ramp of 64 steps on the 1 H channel. Both 1 H and 13 C magnetization is then stored on the Z axis which is followed by a delay Z that allows for restoration of 1 H magnetization from T1 relaxation processes while storing the 13 C enhanced polarization. The process is repeated n times after which a final CP read period is used to produce transverse 13 C magnetization that is detected following the Hahn-echo. Further details can be found in the figure legend Standard short-range dipolar dephasing To gauge the effect of strong dipolar interactions the cross polarization, multi-cross polarization and direct polarization sequences were modified with the introduction of a period during the Hahnecho whereby the 1 H decoupling was omitted allowing the strong dipolar coupling between close 1 H and 13 C spins to dephase the 13 C transverse magnetization prior to acquisition (Figure 1 C, D). For dipolar dephasing time less than 1 rotor period the 1 H spins were decoupled using continuous wave 1 H decoupling on either side of the 13 C π pulse. 204

227 Long range dephasing To probe the effects of longer range dipolar interactions between 1 H and 13 C spins the pulse sequence in Figure 1 E was used. For dephasing times longer than 1 rotor period the C-H dipolar interaction can be refocused under MAS conditions necessitating the use of a REDOR style recoupling of the interaction using π pulses on the 1 H channel at the midpoint of every rotor period flanking the 13 C π pulse to refocus chemical shift [44]. 205

228 Figure 1. Pulse sequences used for this study, all signal acquisitions were taken on a Han Echo with TPPM decoupling on the 1 H channel. (A) MultiCP with standard acquisition (B) DP with standard acquisition (C) MultiCP with dipolar dephasing and continuous wave decoupling around the dephasing period (D) DP with dipolar dephasing and continuous wave decoupling around the dephasing period (E) drop in long range dephasing sequence used with both MultiCP and DP experiments. A detailed explanation of each sequence is given in Appendix C section C1. \ 206

229 4.2.3 Density Functional Theory Calculations Density functional theory calculations have been performed using the Gassuian 09 computational software suite [47]. All calculations have been run using a Beck three parameter functional with a Lee Yang Parr correlation (B3LYP) [48]. A triple zeta Pople type basis set and with d and p shell augmentation (6-311G (d,p)) [49] was used to optimize the geometry of each compound. NMR specta are calculated from the optimized geometry using Gauge Independent Atomic Orbital method [50, 51]. All spectra have been corrected based on the theoretical shielding of tetramethylsilane (TMS), equal to ppm. 4.3 Results The bulk properties for the cellulose chars examined here, including elemental analysis and surface area, have been previously reported [52]. A Van Krevelen plot of the C:H and C:O ratios of each materials is given in Figure 2. Vectors associated with CO and methane loss are given by solid black lines for various initial compositions, while the dehydration line is given by a solid line highlighted with a dashed arrow below. H:C ratios are found to decrease sharply from 1.8 for the native cellulose (close to the theoretical value of 1.67) to 0.26 after treatment at 700 o C. Likewise the O:C ratio decreases from 0.89 (theoretically 0.83) to 0.06 at 700 o C. During the first stages of pyrolysis, up to 300 o C, dehydration of the material remaining in the solid (or liquid intermediate) is clearly the dominate pathway. Other oxygen decomposition processes and polycondesation reactions, which proceed through the removal of hydrogen (CxHy, and CxHyOz) compounds, become increasingly prominent at temperatures of 400 o C and higher. Previous analysis by XPS and FT-IR has indicated that much of the remaining oxygen content after treatment at 400 o C and 207

230 higher is confined to ether and lactone groups with substantial loss of both hydroxyl and carboxylic charter at these temperatures [52]. Much of the oxygen loss has been accomplished by 600 o C, further heating results in a sharp drop in the H:C ratio when pyrolysis at 700 o C is examined with relatively little change in O:C, consistent with continued polycondensation. The progression of polycondenstation reactions, mixed with continued oxygenated group removal, result in increasingly condensed aromatic systems with a strong reduction, though not elimination, of oxygen content as treatment temperature increases to 700 o C. Figure 2. Van Krevlen plot of atomic H:C and O:C ratios from combustion analysis. Solid lines represent theoretical vectors for the loss of CO and CH4 and various initial compositions. The central black line represents the theoretical change associated with dehydration reactions. 208

231 Though the elemental analysis provides strong support for the increasing aromaticity of the char with pyrolysis temperature, little information can be determined regarding the degree of aromaticity. Previous work using XPS and Raman spectroscopy [4, 52] have also revealed significant structural information regarding the chemical state of cellulose pyrolysis chars, however the overall average cluster size and distribution also cannot be directly determined by these methods. Analysis by X-ray diffraction, shown in figure 3, reveals only mild destruction of the original cellulose crystalline structure when treatment of 300 o C are used, consistent with the hypothesis that at low treatment temperatures mostly intramolecular dehydration occurs to the material (mostly the amorphous cellulose through the formation of a liquid intermediate) remaining in solid phase to any great extent. The amorphous signal, present between 2θ of approximately 15 and 25 degrees increases moderately during treatment, does suggest some loss of crystallinity. At higher temperatures of 400 o C and above, the crystalline cellulose peaks are replaced by a very broad amorphous carbon signal centered near 22 degrees. Interpretation by the Scherrer equation for both cellulose and cellulose chars has been performed for qualitative reference, (the defective, crosslinked surface causes sufficient broadening to make quantitative analysis by this equation impossible [25, 53]) with the results displayed in Figure 3. The results do not show any significant deviation for chars produced between 500 and 700 o C, they do however, indicate that any crystallites that do form are likely to be extremely small, on the order of 1-2 nm even for chars produced at high temperatures. 209

232 Figure 3. XRD spectra for cellulose and cellulose derived chars, the FWHM of the 002 peak for each material is listed adjacent to each spectra with the estimated crystallite size calculated by the Scherrer equation, assuming a shape factor of Tuning and Method Validation Because the cluster sizes determined by XRD are small, more accurate analysis methods are needed. To achieve these measurements, NMR spectroscopy with long range dipolar dephasing has been examined. In order to achieve this in reasonable time, a recently proposed quantitative cross polarization (CP) method is employed [46]. Here multiple CP periods are used to ensure full polarization of even carbons several bonds removed from hydrogen. To ensure adequate polarization, a series of tests have been performed in large 5 mm rotors using an increasing number 210

233 of CP periods with varying contact time. DFW processed at 300 o C has been chosen for this analysis rather than any cellulose char because it contains strong aromatic and aliphatic signals, allowing for the comparison of relative intensities. These results are presented in figure 4A and 4B. Using contact times of both 0.5 and 1.0 ms spectra equivalent to those obtained from direct polarization could be obtained given a sufficient number of passes, 8 for 1.0 ms contact time and 12 for 0.5 ms contact time. Additional passes do not improve the signal intensity for any carbons present in the system. The maximized signals obtained compare well to a corrected DP spectrum collected using the same rotor and pack (see figure 4C and 4D). These signals originally contained a significant Teflon background peak. This peak was removed by subtraction of a spectrum collected using the same rotor and caps packed with silica gel. 211

234 A B C D Figure 4. Effect of contact time and passed on the spectra obtained for DFW300. (A) A series of multicp scans using a ramped contanct of 1.0 ms per pulse and (B) 0.5 ms per pulse. Blue line gives a reference CP spectrum obtained with a 1.0 ms pi pulse, green line is a single ramped CP period, the red line is 8 passes and black line is 12 passed. Figure C shows a comparison of the spectrum collected after 8 passes using a 1.0 ms ramped CP period (red line) with the background corrected spectrum obtained by DP (black line) (D) compares the spectrum obtained by 12 passes using a 0.5 ms ramped CP period (red line). 212

235 Because of the residual Teflon signal in the available 5mm stater, and to avoid potential arcing with chars produced at high temperatures [23] a smaller 3.2 mm rotor is used for the remainder of the tests. A higher spin rate of 10K is also employed to improve side band separation. To confirm that tuning parameters established for the 5 mm rotor remain valid, initial and dephased DP and multicp spectra for the C700 char are compared in Figure 5. The direct polarization spectra are the result of 256 scans compared to 2048 for the multicp and so have been scaled using the same factor for direct comparison. The sensitivity by MultiCP was found to be higher than for DP, requiring a correction of 11X rather than the expected 8X to obtain a reasonable match between the initial spectra. While significantly noisier, the results for both polarization methods are extremely consistent, and show the same dephasing behavior, indicative of equivalent polarization of even distant carbons by each method. 213

236 Figure 5. C700 with dephasing. Black lines represent MultiCP signals from 2048 scan scaled by exactly 1/11. Red lines represent DP signal collected after 256 scans. Total acquisition time for MultiCP experiments was 6.5 hrs while DP experiments required 9.6 hrs Analysis of reference compound (PTCDA) To confirm the efficacy of the multicp approach with dipolar dephasing for both accurate quantification and accurate determination of equivalent bond distances (rc-h), perylene tetracarboxylic dianhydride (PTCDA) has been evaluated, the resulting spectrum as well as two spectra for simulated conformations are presented in figures 6A-D. Because of the ridged bonding patters of this compound, relaxation times are excessively long, in excess of 7 minutes, when attempting direct polarization (See figure 6B). Because of this no comparable scan has been 214

237 produced to compare the multicp scans. Instead, a series of experiments was conducted with an increasing number of CP passes to confirm maximum signal intensity (not shown). As before, 8 passes with a contact time of 1.0 ms was found to produce the maximum intensity. Integration of total peak area, including side bands also supports this conclusion. A B C D Figure 6. (A) MultiCP spectrum for PTCDA collected form 2048 scans, relative integration areas are provided above each distinct peak within the main spectra and the side bands. (B) DP spectra for PTCDA using 1.5 (red), 3 (black) and 7 (blue) minute recycle delays, spectra for 1.5 and 7 minutes are a composite of 32 scans while the spectrum for 3 minute delays is a composite of 512 with the background normalized to the other spectra. (C) Comparison of MultiCP spectrum (black line) to calculated spectrum for isolated PTCDA (red line) (D) comparison of MultiCP spectrum to calculated spectrum for the central molecule of a 6 molecule PTCDA cluster. 215

238 Table 1. Integrated intensities for PTCDA peaks, see figure 6A for corresponding assignments, and quantification of C associated with each peak compared to the theoretical values. Position Assignment Primary peak High side band Low side band Total Equivalent distribution Theoretical distribution B C, F, D E,G A Relative peak areas and positions are given in Table 1. The sum total peak area divided by 24 is used as the quantification reference. These results indicate good signal reproduction for all peaks, though intensity between 130 and 125 ppm, appears to be slightly under represented, while the peak for sites adjacent to the carboxyl groups are slightly overrepresented, even when corrected for side band intensity. This effect is attributed to convolution of slightly different signals from PTCDA molecules within the crystals structure and along the edge. The result of this effect is a percentage of signal from carbon site F being shifted toward 118 ppm. This effect can be seen by examining the shielding parameters of the F site carbons in the peripheral molecules included in supplementary Figure C1 (Appendix C section C2). The total shifts are mild, approximately 10-15%, and not expected to greatly influence the dephasing behavior after the first ms. 216

239 Figure 7. Dephasing plots for Tetracarboxylic perylene The dephasing results for PTCDA are presented in figure 7. These results demonstrate near total signal suppression within 1 ms (10 rotor periods), with total signals only just detectable above the background noise. The initial 74 us dephasing period is clearly sufficient to eliminate the majority (>95%) of C-H signal while leaving the remaining signal largely intact. Still, approximately 10-25% of each remaining peak was attenuated even after this time period. Signal attenuation after 400 μs was sufficient to reduce side band intensity to near background levels. By 800 μs the signal from internal carbons, 3 bond length s removed for hydrogen, are the strongest remaining signals. To analyze these dephasing results the total reduction in signal intensity as dephasing is increased from 74 μs to 600 μs is analyzed via a first order kinetic model, equation 1, as discussed by Mao 217

240 and Schmidt-Rohr [44]. 74 μs was chosen as the initial point to obtain clear separation of the C and D carbon peaks as well as avoid contamination for the C-H peaks. K C H = Ln(I 0.60 ) Ln(I ) 0.6 ms ms Eq. 1 Where: It is the signal intensity at time t This kinetic rate was compared to the distance between various carbon and hydrogens (rc-h in Å) by use of an F factor, equation 2. F = 1 (r C H ) 3 or, when more than 1 H is present F = 1/(r C Hi) 6 i 1 Eq. 2 A B Figure 8. Dephasing results individual carbons in PTCDA (A) dephasing over time for carbons A-E with the theoretical rate for A and C+D given as dashed line (B) comparison of experimental dephasing rate with F value, black line denotes empirical equation proposed by Mao and Shmidt- Rohr [44]. 218

241 The dephasing results (Figure 8B) compares the reduction of intensity over long range dephasing with the signal intensity found after 74 us dephasing. This point was chosen over the initial spectrum to obtain better separation of the internal carbon peaks at 125 and 130 ppm. The rate of T1 dephasing is estimated by simple first order kinetics, as shown in equation 1. Plotting these results for each of the 5 unique carbons in tetracarboxylic perylene against the F factor yields results that agree exceptionally well with the empirical equation previously published by Mao and Shmidt-Rohr [44] based on several different reference standards. The only outlier to this plot is the carboxylic carbon. These have been found to dephase much more rapidly than would be expected when considering only intramolecular carbon spacing. When the lower intermolecular spacing due to planar hydrogen bonding present in the crystalline structure shown in figure 4C is considered much shorter rc-h are found. Properly accounting for this spacing allows for much more accurate determination of the dephasing kinetics. In figure 8B we demonstrate that first order kinetics using the empirical rate constant can accurately predict the dephasing behavior for each carbon site in PTCDA Effect of cluster size, shape and defects on NMR spectra (DFT studies) To determine the influence of cluster size and irregular structures within aromatic systems on the chemical shifts observed via NMR, a series of simulated compounds have been evaluated via DFT. The results of these simulations are presented in Figure 9 and demonstrate that carbons within ring systems larger than 6 carbons show chemical shifts between ppm for approximately half of the carbons in the system (See figures 9D and 9E), though this is not universal and can break down with complex defects near edge sites (see figure 9F). 5 carbon ring defects alone do not present substantial shifts compared to more familiar aromatic sites, both presenting between

242 and 140 ppm (See figure 9A-C). The results also demonstrate that carbons near oxygen defects have present somewhat lower chemical shifts, between 100 and 120 ppm (Figures 9H and 9I). The position of ether, carboxyl, lactone and carbonyl groups are within the range typically reported (Figure 9G-I). The positions of aliphatic carbons are also well established and are found to be present within the expected range for carbons that lack any double bond. Based on these results a deconvolution strategy is proposed to more specifically assign the aromatic region to both regular and defective (non-hexagonal) sites. An important ring system not model here but presented elsewhere is that of furans. The ether bonded carbons in this ring system have chemical shifts of approximately 142 ppm while the other carbons (2 bonds removed from oxygen) have shifts of approximately 115 ppm. Though the ether shifts are somewhat lower than typically assigned, the shifts associated with carbons two bonds removed from oxygen are consistent with the simulated results of larger ring systems. These results are summarized in Table

243 Figure 9. Theoretical spectra for 9 compounds (A) pentacene (B) coronene (C) circumpyrene (D) cyclopentane centered ring system (E) cycloheptane centered ring system (F) coronene with Stone-Wales defect (G) conenene with added carboxyl group (H) coronene containing lactone group (I) coronene with single point defect closed by ether group and carbonyl group. All compounds containing carbon at shifts less than 120 ppm and greater than 140 ppm have been assigned alphabetic labels that correspond to each respective figure. New labels are used for peaks separated by more than 3 ppm. 221

244 Table 2. Peak assignment table Chemical Shift Assignment 5-50 ppm Aliphatic CHx ppm (slow dephasing) Aliphatic CR ppm (110 for double) Aliphatic ether ppm Aromatic C near Oxygen defects ppm Aromatic5 and 6 member rings and olefins ppm Contribution for ether bonded carbon in furans and ~ ½ of carbons in larger non oxygenated rings ppm Aromatic linked ethers ppm Carboxylic/Lactone/ester ppm Carbonyl While accurate analysis of the initial peak positions and intensities is essential for proper structural assignment, this data cannot be applied without information regarding position within the structure. To determine the relative number of carbons positioned at various distances from hydrogen, dephasing behavior for a variety of carbon sites has fist been estimated using apparent bond distances calculated by equation 2 in conjunction with the first order kinetic model from equation 1 to provide additional reference curves. 222

245 Figure 10. (A) Theoretical dephasing for various carbons within circumpyrene at different apparent distances from hydrogen (1.9 A < rc-h < 3.8 Å) (B) Composite dephasing for various polyaromatic structures of increasing size (squares rylene, diamonds = coronene, triangles = circumpyrene, and circles = circumcoronene). The red line denotes an S/So value of 0.05 as an approximate minimum quantification level. The theoretical dephasing plots are shown in Figure 10A, and have been generated for carbons set at specific distances from a single hydrogen, assuming the first order kinetics remain valid for at least 2.5 ms and that KC-H = 32F is a reasonable approximation of this rate. By assuming additive behavior for each carbon, the dephasing behavior of several aromatic structures are estimated and given in Figure 10B. Here the rc-h value used is the apparent distance, calculated from the nearest two sets of hydrogen (based on bond number separation). The dephasing for C-H groups is markedly faster than predicted by the empirical equation due to direct coupling. To account for this, C-H carbons are considered to have a dephasing rate of KC-H = 75 ms -1 to achieve 95% signal reduction by 0.04 ms based on previous dephasing results set at this time [44]. 223

246 Table 3. Assorted Polyaromatic structures with number of carbons C-(-X)-H bond distances specified Linear r C-H (Å) Benzene Napthalene Anthracene Tetracene Pentacene Hexacene C H C:H C-H C-C-H Layer 2*2 (Pyrene) 3*2 4*2 5*2 6*2 C H C:H C-H C-C-H C(-2)-H circular and 3*3 4*5 5*5 6*7 7*7 semicircular (coronene) circumpyrene (circumcoronene) C H C:H C-H C-C-H C(-2)-H C(-3)-H C(-4)-H C(-5)-H C(-6)-H Table 3 provides structural information on a range of regular aromatic structures ranging from linear aromatic chains (Benzene through hexacene) to circular and oval like structures such as coronene and circumpyrene. Larger structures are denoted by the number of aromatic rings along the x and y axis (eg coronene is 3*3, while circumpyrene is 3*4). The H:C ratio and the distribution 224

247 of rc-h distances are presented for each material. These compounds can be used to provide initial guesses for the unknown chars, with approximate compounds used to bracket the dephasing behavior and the introduction of oxygenated groups and defects used to interpolate between the idealized structures Application to a series of Cellulose Chars A series of cellulose chars produced at o C was analyzed using the multicp technique with a 2048 scan composite. The full series, including unaltered cellulose is presented in figure 11. These results are consistent with the XRD data and show that relatively little structural change occurs with treatment at 300 o C, though some dehydration is apparent. The lack of peak development between 100 and 150 ppm suggests that dehydration reactions involve the formation of anhydrosugar units such as levoglucosan and cross-linking of glycosidic units. When pyrolysis temperatures are increased to 400 o C drastic changes are observed in the spectra. The cellulose character has been completed destroyed, replaced by an amorphous aromatic region between 100 and 170 ppm. A residual aliphatic contribution is also observed between 0 and 60 ppm. This contribution is strongly reduced at pyrolysis temperatures of 500 o C and eliminated at 600 o C. The aromatic region becomes sharper and more clearly defined as pyrolysis temperature increases revealing a distinct ether bonded region between 150 and 160 ppm and a slightly asymmetric aromatic region between 100 and 147 ppm. This asymmetry has been attributed to contributions from defect carbon as discussed in section

248 A B Figure 11. Changes in Char spectra with temperature, Deconvolution scheme shown for C

249 A weakly constrained deconvolution has been performed on the initial spectra for each material. This deconvolution allowed for a free floating G:L ratio, full width half maximum (FWHM) as well as intensity. Position was monitored to ensure that only a single curve was used for each position discussed in table 2. Side band position was fixed as the position of the aromatic peak +/- 100 ppm (based on rotor speed of 10K Hz). The results of this deconvolution are presented in Table 4. The aliphatic region is estimated as the total contribution between 0 and 60 ppm minus the contribution between 200 and 250 ppm. This was done assuming symmetric side band contributions to remove aromatic signal from the aliphatic region. Though this is not exactly accurate, this is expected to give a reasonable estimation of the aliphatic contribution. While these results differ mildly from those obtained by integration of the predefined regions in table 2 (not shown), these variances are minor when the defect and aromatic regions are considered a single peak. Table 4. Composition of material based on NMR Specta (%) Sample carbonyl Carboxyl/lactone ether defect Aromatic aliphatic C C C C Margin of error is estimated at 2% 227

250 Figure 12. Plot of NMR spectrum and dipolar dephasing spectra for C500. All spectra have been collected using 2048 scans. 228

251 Figure 13. S/So plots for C400 (squares) C500 (diamonds) C600 (triangles) and C700 (circles) the solid red line represent the theoretical dephasing for coronene based on first order kinetics and the black line for circumpyrene. The insert shows an expanded view of the dephasing plot between 0.3 and 1.1 ms for clarity. The dephasing results for the combined aromatic and defect region ( ppm) are given in Figure 13. Based on the dephasing results, the structures of C400-C700 are estimated to range between approximately that of coronene and circumpyrene based on cluster size. An interesting result is that C400 contains relatively few aromatic hydrogens, indicating that much of the hydrogenated carbons exist as aliphatic sp 3 sites. Both C500 and C600 show similar dephasing after 0.8 ms, however C600 shows improved stability at longer dephasing times suggesting a 229

252 higher fraction of carbons exist 3 or more bonds from a hydrogen. In each case initial dephasing results at ms show lower intensity loss than predicted for the model compounds, indicating substitution and intercluster linkages at the edge sites. These substitutions do not result in any substantial increase in carbons 3 or more bonds removed from hydrogen indicating that the cluster sizes cannot be substantially larger than circumpyrene tested or that substantial hydrogenated internal defects are present within the cluster. To estimate the approximate contributions of each site type the dephasing data for the aromatic + defect peak, the ether peak, and the aliphatic peak (C400 only) were fitted by a least squares methods using estimated dephasing rates for C-H bond distances of 1.9, 2.15, 3.4, 3.9 and 4.9 Å. Directly coupled C-H were assumed to dephase by the first data point at ms. The results of this procedure are summarized in table 4. These results show an increase in overall C-H contribution to the aromatic cluster with increasing pyrolysis temperature indicating removal of substituted oxygen from edge sites as well as reduced bonding between clusters. This is coupled with a continuous reduction in carbons 2 bonds removed from a hydrogen ( Å). Interestingly no significant change is observed at the 3 bond position ( Å), however an increase in carbons 4 bonds removed is observed. Ether groups are found to have markedly different behavior than aromatic carbons in terms of dephasing. Directly coupled C-H sites show a sharp decrease is observed at temperatures greater than 500 o C with no appreciable content being determined for C600 and C700. Ether carbons 2 bonds removed from a H show an initial decline as temperature increases from 400 to 500, shifting toward directly coupled at 3 bond removed, before increasing sharply at higher pyrolysis temperatures. The increase in ether carbons 2 bonds removed at C600 and C700 result in decreasing total contribution from those at 3 and 4 bond 230

253 distances as well as those directly coupled to hydrogen. This behavior indicates that ether bonded carbons should be relatively constrained to edge or defect sits at higher temperatures. These groups may provide the necessary reactive sites for cluster growth, their removal explaining the drastic reduction in reactivity for material produced at temperatures greater than 700 and relatively stable structures obtained at this and higher temperatures. Table 5. Estimated contribution of various C-H bond distances for chars produced at o C based on dephasing results (%) Aromatic and defective aromatic carbons Ether/hydroxyl bonded carbons Aliphatic C-H C-X-H C(-2)-H C(-3)-H C-H C-X-H C(-2)-H C(-3)-H C-H C-X-H C < < C < <1 100 N/A C <1 N/A N/A C N/A N/A Margin of error is estimated as 5% To illustrate the changes in cluster size and composition a graphical representation of the data presented in tables 4 and 5 is given in figure 14. Because chars are heterogeneous 3 dimensional structures no single planar, or semi-planar structure can adequately depict the complexity of the material. While these clusters are designed to closely mimic the data presented they are not necessarily exact, nor do they depict the only viable solutions. These figures do however illustrate the destruction of the original cellulose structure through crosslinking and polycondensation and the formation of increasingly regular structures within the char as pyrolysis temperature is increased. 231

254 Cellulose (C12H20O10) C300 (C12H18O9) C400 (C22H10O5) R R C500 (C24H9O4) R C600 (C32H12O3) R C700 (C37H12O3) R R R R R R Figure 14. Example char structures based on composition shown in Table 4 and C-H distance and quantity from table 5 for C300-C Conclusions In this work we have successfully applied a quantitative cross-polarization technique for the rapid analysis of aromatic carbons. This technique, combined with long range dipolar dephasing was successful in estimating apparent C-H bond distances for a range of materials, including PTCDA and cellulose chars produced between 300 and 700 o C. A series of theoretical structures was analyzed via density function theory to provide shift references for analysis. Dephasing behavior 232

255 was successfully estimated as based on first order kinetics where the rate constant was proportional to the inverse of the distance between carbon and hydrogen cubed. These results clearly show an increase in cluster size with heating temperature, but also demonstrate that substantial defect regions are present in each char. Through the use of dipolar dephasing the approximate location of these defects within the cluster was estimated, as was the position of ether groups throughout the material. These results indicate that defects and ethers tend to be located towards the periphery of the cluster, suggesting that cluster growth is likely mediated by reactions at these sites, resulting in a more ordered internal structure. These results demonstrate the complexity of the chemical structure of pyrolysis chars, and highlight that estimation as a regular aromatic system is insufficient in the explanation of char structure. Acknowledgement: Dr. Garcia-Perez and Mr. Smith are very thankful for the financial support provided by the US National Science Foundation (CBET , CAREER CBET ), the Agricultural Research Center (NIFA-Hatch-WNP00701), the Washington State Department of Agriculture (Appendix A) and the Northwest Advanced Renewable Alliance (NARA) (USDA-NIFA grant No: ). 233

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262 Appendix C Supplemental Material for Chapter 4 C.1. Detailed pulse sequence description Figure 1) Pulse Sequences A) Multi-Cross polarization sequence (multi-cp). Black rectangles represent /2 pulses whereas narrow open rectangles represent pulses. Longer open rectangles represent 13 C cross polarization periods and 1 H decoupling periods. The CP period along with the 1 H longitudinal magnetization recovery delay Z (~ 2 * 1 H T1, 0.5 or 1.0s in this work) is repeated n times to successively build 13 C polarization prior to a final CP period (which can be of a different contact time duration). Total CP duration is then given by n * CP contact 1 + CP contact time 2. Acquisition follows a 1-rotor period Hahn-echo to allow for distortion free baselines. 1 H decoupling field strengths can be varied for the Hahn-echo period vs. the acquisition period. ph2 = ph13 = ph3 = ph14 = ph15 = ph31 (rec) = B) Direct polarization sequence. Black rectangles represent /2 pulses whereas narrow open rectangles represent pulses. Acquisition follows a 1-rotor period Hahn-echo to allow for distortion free baselines. ph2, ph3 and phrec as in A. 240

263 C) Multi-Cross polarization short-range dipolar dephasing sequence. Parameters follow from A (multi-cp block) with the exception that for dipolar dephasing times less than 1 rotor period (tr) the 1 H decoupling is set to continuous wave for periods flanking the 13 C pulse in the 1-tr Hahn-echo period. 1H decoupling is turned off for the desired dephasing time. D) Direct polarization short-range dipolar dephasing sequence. Same as for C with the exception that direct polarization resulting from a single 13 C /2 pulse is used in place of the multi-cp block. E) Multi-Cross polarization / Direct polarization long-range dipolar dephasing sequence. Initial polarization blocks follow parameters for A and B. Long-range dipolar dephasing is accomplished by a REDOR style arrangement of 1 H pulses set at tr/2 periods. Total dephasing time is given by 4tr * m where m is the number of loops through the sequence. Phases for the pulses are as follows: ph7 = ph8 = all other phases follow sequences A and or B. 241

264 C.2. NMR Shielding for PTCDA Cluster Figure C1. Shift in NMR shielding for carbon F (see figure 6A in chapter 4 for primary labels) when comparing molecules within the cluster (labeled as sites A here only) to those at the edge (labeled as sites B-D here only). Similar patterns are also observed for carbon G (again see figure 6A), however those shifts do not result in contamination of a second peak. 242

265 Chapter 5: Chemical and Morphological Evaluation of Chars Produced from Primary Biomass Constituents: Cellulose, Xylan, and Lignin To be submitted to Biomass and Bioenergy Matthew Smith 1,2, Michael Brennan Pecha 1,2, Greg Helms 3, Louis Scudiero 3, Manuel Garcia- Perez 1 1 Department of Biological Systems Engineering, Washington State University, Pullman, WA 99164, USA 2 Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Pullman, WA 99164, USA 3 Department of Chemistry and Materials Science and engineering Program, Washington State University, Pullman, WA 99164, USA 243

266 Abstract: Although the production of char from lignocellulosic materials is an area of great scientific and technical importance, our current knowledge of the relative contribution of cellulose, hemicellulose and lignin to the chemical and morphological properties of resulting materials is still poorly known. The main objective of this paper is to study how the individual biomass components (cellulose, hemicellulose and lignin) and the pyrolysis temperature used impact the bulk, surface and morphological properties of the resulting chars. Chars were produced from the pyrolysis of cellulose, xylan and lignin at temperatures between 300 and 700 o C. Raman, XPS and NMR schemes, are employed with scanning electron microscopy, surface area analysis and chemical analysis to characterize the resulting material. Both the macro and microscopic properties of the thermoseries showed wide differences in surface area, aromatic ring formation, aromatic condensation and cluster shape. Formation of aromatic rings was found to be prevalent at 400 o C for both cellulose and MWL chars, and showed development at 300 o C for xylan. Aromatic condensation of these structures increased slightly with heating to 500 o C, but was largely stable until treatment at 700 o C. The sharp drop in oxygen content, as well as the formation of ether like groups for residual single bonded carbon confirms that oxygen is a primary reaction component for preliminary crosslinking and poly condensation. As pyrolysis temperature increase these ether groups are found to be distributed further from hydrogen within the aromatic structure, indicating that non-reacted edge sites are gradually incorporated into the internal cluster. Despite the considerable ring growth at 700 o C for all chars, only very mild loss of oxygen is identified from elemental analysis. This suggests that C-C bonds are forming without oxygen mediation. The increased broadness of the NMR peak and the Raman G band, suggest that at these temperature the increase in ring size occurs largely in a 3 dimensional manner rather than planner. The intensities in these regions having been linked to non-hexagonal rings and out of plane distortion. 244

267 By comparing the NMR dephasing data to the I(D)/I(G) ratio an approximate relation between this Raman data and cluster size has also been derived. The variances highlighted here have strong implications regarding the reactivity and adsorption potential of chars from each constituent, highlighting the importance of both feedstock selection and pyrolysis conditions on the final form of chars. Keywords: Chars, NMR, Raman, XPS 245

268 5.1 Introduction Chars generated from biomass have been found to have positive agronomic impacts. These materials are obtained as a result of complex thermochemical reactions that occur when lignocellulosic materials are heated over 300 o C in the absence of oxygen. This process is typically known as pyrolysis and provides a route for both biofuel production and mineral nutrient recycle [1-3]. Chars formed by high temperature pyrolysis contain large fractions of highly stable aromatic compounds, similar to high grade coals, that are resistant to microbial attack [2], providing a proven mechanism for carbon storage. In addition, historical anthrosols show evidence that charlike materials have substantially altered physical and chemical properties in Terra Preta soils [4, 5], leading to long lasting carbon storage and improved crop production. While char has significant potential as a soil amendment, the relationships between biomass composition-pyrolysis conditions-char bulk and surface properties and its performance as a soil amendment are still poorly known [6]. To understand how chars can be applied, it is necessary to understand the varied physical properties of these materials and how they are formed. The three main polymers forming lignocellulosic materials are cellulose, hemicellulose and lignin, and the distribution of these polymers in lignocellulosic material is a critical factor controlling the products from pyrolysis [7, 8]. Cellulose is a polymeric chain form from a single monomer units linked by β-1-4 glycosidic bonds [9]. Cellulose tends to form large crystalline strands supported by inter-chain hydrogen bonding. These chains are arranged in microfibrils with varying orientation throughout the cell wall of plants 246

269 [10]. By contrast both lignin and hemicellulose are amorphous polymers comprised of several unique monomer units. Lignin is formed from three different phenyl-propanoid monomers (coniferyl, sinapyl and p-coumaryl alcohol), and serves as a continuous matrix and structural support for plant cell walls surrounding the cellulose fibrils and filling the intercellular space in the xylem structure. Softwood lignin (e.g. Douglas fir) contains guaiacyl and p-hydroxyphenyl units, while hardwood lignin (e.g. Hybrid poplar) contains guaiacyl and syringyl units. These monomers are linked by a variety of relatively weak inter-unit ether ( -O-4, -O-4 and 4-O-5) and strong carbon-carbon bonds ( -1, -5, 5-5, - ) to form a three dimensional structure [11]. Hemicellulose is formed by both pentose and hexose monomers, specifically; D-xylose, D- mannose, D-glucose, D-galactose, and L-arabinose [12]. While this polymer does contain a substantial degree of β 1-4 glycosidic bonds, the structure also contains significant branching at other sites that prevents the formation of large, linear changes [13, 14] Hemicellulose is primarily located within the microfibril structure, surrounding individual cellulose bundles [10]. Carbonization of lignocellulosic material proceeds initially via depolymerisation, dehydration, cross-linking and condensation reactions [15-18]. Volatile compounds formed by the initial primary reactions may also undergo secondary heterogeneous reactions with char along the diffusion path out of the particle [19, 20]. The liquid intermediate formed by the depolymerisation of cellulose, hemicellulose and lignin also undergo secondary reactions to form a final highly stable polyaromatic material known as char [21]. The carbonization of cellulose competes with both depolymerisation [22-25] and fragmentation reactions [15, 16, 22, 26-29]. A recent mechanism proposed by Wang hypothesizes the formation 247

270 of char proceeding through four distinct regimes. Initially the crystalline form begins to degrade between 250 and 300 o C, forming an active cellulose phase (crystalline depolymerized cellulose) by the cleavage of weak glycosidic bonds every glucose units [22, 26, 30-34]. Next this active cellulose begins to form a molten phase. NMR studies by Pastrova suggest that by this stage in pyrolysis a variety of rearrangement and fragmentation products are also present, including furans, hydroxyaromatics, unsaturated hydrocarbon chains, and new oxygenated groups including carboxyls and carbonyls. This molten phase then undergoes a variety of dehydration, cross-linking, and fragmentation reactions resulting in volatile release and heavily cross-linked structures in the solid phase [33, 35]. Finally, the crosslinked solids poly-condense to form the familiar aromatic carbon structures typical of charcoal [7, 8, 31, 36-38] Pastorova et al. [39] provides a detailed explanation of the crosslinking mechanism of cellulose. In this model the active or molten cellulose products are hypothesized to react through aldol type reactions with ring fragments and cleaved rings, causing randomized three dimensional growth of the condensed phase. In addition to aldol condensation, at temperatures above 200 o C, ESR studies have identified the formation of radical sites from homolytic cleavages [40]. These free-radicals further promote crosslinking and condensation reactions. Charcoal formation mechanisms form lignin have also received considerable attention in the literature. Cleavage of lignin bonds during pyrolysis is predicted to proceed via homolytic cleavage, substitution, and hydrogen transfer induced bond-scission reactions [41, 42]. These reactions tend to favor decomposition of the ether bonds, as demonstrated by Kawamoto [43]. Model compounds studies have shown that groups containing phenolic structures are considerably 248

271 more reactive than groups without, showing increased yields of both char (from polycondensation) and guaiacol (from β-ether cleavage) [43]. A proposed decomposition pathway presented by Zhou [44] assumes two discrete pathways depending on the number of monomer units linked by C-C bonds. This model was created to explain the formation of volatile products. Clusters of between 1-5 units are proposed to pyrolyze by passing through a melt phase. Once in this state clusters either depolymerize or cross-link, increasing the molecular weight of each cluster [45-48]. Larger aromatic structures (6 or more units linked by C-C bonds) are considered too large to enter the melt phase. Both these structures, and the cross-linked structures formed in the melt are hypothesized to polycondense via reaction of the propanol chain and methoxy groups, leaving the aromatic ring intact and producing a stable aromatic char structure. [49]. Cross linking of lignin compounds has been hypothesized to proceed via a similar mechanism as that of cellulose, namely through a series of aldol condensation [41] and radical induced crosslinking [50]. The decomposition of hemicellulose is the least studied of the primary biomass components [51]. Degradation is often assumed to follow similar reaction pathways as that of cellulose; however, the amorphous nature of the polymer facilitates more rapid decomposition, as shown Wang et al. in their investigation of the effect of crystallinity on cellulose pyrolysis [52]. Thermogravimetric studies have demonstrated that primary decomposition begins at temperatures as low as 250 o C and is nearly complete by 350 o C [53, 54], with only mild mass loss associated with further heating to 700 o C. These results indicate that far more extensive crosslinking occurs in the hemicellulose structure, stabilizing much of the residual char structure, even before polycondensation occurs. 249

272 Analysis of the products from hemicellulose pyrolysis indicate substantially higher furanic type compounds than typically obtained from cellulose [51]. There are very few studies in the literature on the differences in composition of the chars produced from cellulose, hemicellulose and lignin. Previous analyses of the pyrolysis of mixed components has shown that while substantial deviation in the yield of both liquids and gases occurs when assuming a non-interacting model, char yields are highly predictable by the additive contribution of each of the polymers in the feedstock [7] What is not known, is if the composition of each of the biomass constituents contributes separately to form distinct structures. The main objective of this paper is to study how the individual biomass components (cellulose, hemicellulose and lignin) and the pyrolysis temperature used impact the bulk, surface and morphological properties of the resulting chars. To achieve this, recently proposed Raman [55], XPS [56] and NMR schemes [57], are employed with scanning electron microscopy, surface area analysis and chemical analysis to better define the char structures that form from a thermoseries of each material. 5.2 Materials and Methods Avicel Cellulose and Xylan Avicel Cellulose was purchased from Sigma Aldrich (LOT# BCBG9043V) and used as received for all studies. xylan, produced from birchwood and used as a surrogate for hemicellulose, was also purchased from Sigma Aldrich and used as received. 250

273 5.2.2 Milled Wood Lignin Purification Milled wood lignin (MWL) was produced from hybrid poplar wood following a modifie Bjorkman Method [58]. In this method ~ 200g of wood are first extracted using a 9:1 acetone water solution followed by a 2:1 ethanol benzene mixture. Each extraction is performed for a minimum of 8 hours using a Soxhlet extraction system. The extracted wood fiber is then dried at 80 o C overnight. Dried wood fiber was then milled for 50 hours using an Across International ball mill with alumina jars and zirconia balls. Milling was performed at 600 RPM with a 15 minute on/15 minute off cycle. After milling, the wood flour was extracted using a 96% dioxane solution, and solids were separated by centrifugation and re-extracted. A total of 3 extractions were performed on the wood four. To obtain the crude wood lignin the dioxane was evaporated using a rotary evaporator. To reduce the carbohydrate content of the crude lignin, it was dissolved again in 9:1 acetic acid:water and reprecipitated into cold water. The precipitate was again centrifuged and the liquid decanted. This precipitate was dehydrated using 3 washes of 95% ethanol, followed by centrifugation and decanting. The dehydrated precipitate was then dissolved using a minimal quantity of a 2:1 dichloroethane:ethanol mixture. This mixture was then added dropwise to anhydrous diethyl ether to precipitate. The final precipitate was washed 3 times with ether and stored in a brown glass bottle at 2-4 o C until use. Total yield of MWL was approximately 4% of the initial material Pyrolysis A series of five chars have been produced from each of the primary constituents; cellulose, xylan and MWL. These chars are produced with a final set temperature of 300 to 700 o C using a spoon pyrolysis reactor, and following same methods as previously described [52, 59]. All experiments 251

274 are conducted under a N2 gas (99%). A nitrogen stream flowing at approximately 300 ml/min is used to purge the reactor for 10 minutes prior to each experiment and allowed to run during pyrolysis to avoid contamination from air leaks. A secondary preheated nitrogen sweep gas, flowing at approximately 550 ml/min, is employed in the reactor zone to carry the vapors out. All pyrolysis experiments have been carried out for 30 minutes. Following treatment samples are allowed to cool to temperatures below 25 C under the N2 sweep before exposure to air Morphological and Surface Area Evaluation Scanning electron micrographs were collected using an FEI SEM Quanta 200F scanning electron microscope. All samples were prepared by coating with 3 nm of platinum to enhance resolution using a Cressiongton Hi-Res Sputter Coater. The images were collected under vacuum with a chamber pressure below 0.01 Pa. The accelerating voltage was set at 30 kv for all samples, for pure samples and those prepared at 300 o C it was on occasion necessary to reduce the accelerating voltage to 20 kv to reduce charging effects at low magnification. Surface area has been determined based on gas adsorption isotherms collected on a micromeritics Tristar physisorption analyzer. Isotherms for all chars have been collected using CO2 with a specified 75 point isotherm between partial pressures of and A geometric distribution towards low partial pressures was used. Surface area was determined using the Dubinin-Radushkevich method [60, 61]. Average pore size was estimated based on the estimated characteristic binding energy as described elsewhere [62]. 252

275 5.2.5 Elemental and Proximate Analyses Proximate analysis has been conducted using a Metler Toledo thermogravimetric analyzer. Each analysis has been conducted in triplicate using 5 ± 0.5 mg of sample. The heating protocol used is based on the ASTM method D for coal and is summarized in table 1. Lower temperatures are used for the volatile matter and ash determination due the less condensed nature of biomass polymers and their chars. The dry weight is determined as the stable weight at 110 o C. Volatile matter is determined as the mass lost after stabilization at 800 o C. Fixed carbon is calculated as the stable fraction at 800 o C minus the ash content as determined at 600 o C under oxygen. Table 1. Heating protocol for proximate analysis Step Initial Temperature ( o C) Final Temperature ( o C) Heating rate ( o C / min) Hold time (min) Carrier gas Drying N2 Volatiles N2 Cooling N2 Ashing O2 The carbon, nitrogen and hydrogen content of each cellulose and xylan based material has been determined in triplicate using a LECO elemental analysis system using approximately 150 mg run. Due to limited material analysis of MWL, these samples were analyzed using 50 mg of sample in duplicate. Calibration was performed by analysis of a cellulose standard (deviations of less than 1%). 253

276 5.2.6 Spectroscopic Characterization (XRD, XPS, NMR, Raman) X-ray diffraction patterns of cellulose, hemicellulose and lignin were collected using a Rikagu MiniFlex 600 benchtop Xray defractometer. Diffraction spectra were collected between 2θ of 5 to 50 degrees at constant scan rate of 1 degree per minute. To ensure representative samples the sampling pan was rotated during acquisition for cellulose and xylan chars. Due to limited sample volume, MWL samples were analyzed using a shallow glass sample holder which could not be rotated. The X-ray photoemission spectra of each cellulose, xylan and MWL char in the thermoseries has been evaluated using an AXIS-165 manufactured by Kratos Analytical Inc. (Spring Valley, NY, USA). Scans are conducted for xylan and MWL chars using an achromatic X-ray radiation of 1486.X ev (AlKα). Because results obtained for cellulose chars [56] using a Mg Kα source at ev revealed ghost peaks related to Al Kα x-rays, the higher energy source was utilized to avoid this contamination. A total of 5 passes using a pass energy of 40 ev and spot size of approximately 120 µm was used for the collection of each spectrum. The spectrometer was previously calibrated against both the Au 4f7/2 peak at 84.0 ev and the Ag 3d5/2 peak at ev. Survey scans are recorded using a step sizes of 1 ev to estimate chemical composition. Fine scans, using a step size of 0.15 ev have been collected of primary peaks (O 1s, C 1s and Na 2s) to determine the associated bonding of each element. Deconvolution of the XPS spectra has been performed using a recently proposed combined O 1s: C 1s analysis routine [56]. The peak parameters used are given in Table

277 Table 2. Peak assignments and parameters for the interpretation of O1s and C1s spectra of chars [56] Peak Assignment BE (ev) FWHM (ev) G:L (0-1) O-C(1) O-C(2) O=C (H2O) C-C low C-C Primary C-C High C-O C=O COO Pi-Pi* Ether and hydroxyl groups bonded to aromatics Ether and hydroxyl groups bonded to aliphatics & carbonyl shake-up In carbonyl, lactone and carboxylic groups Absorbed water/oxygen, sub monolayer Cyclopentane ring atoms within cluster Primary C-C/C-H peak C in cycloheptane or larger rings within clusters, C in small clusters containing C=O bonds, sp3 bonded carbons Ether and hydroxyl bonded C, C associated with ether bond in lactone/esters Carbonyl groups and carbons attached to two ether/hydroxyl groups Carboxyl, lactone and ester groups HOMO-LUMO transition for primary C-C peak Dispersive Raman spectra were collected using a Horiba LabRAM HR microscope equipped with a 250-mW, 532-nm wavelength laser (Ventus LP 532). This laser was operated at 90% and utilized a 1% transmittance filter at an objective of x50. The focused spot size is approximated as an ellipse with a major axis of 25 μm and minor axis of 20 μm, giving an average power of 229 W/cm 2 applied to the surface. Samples were prepared as a 5% mixture in spectroscopic grade KBr to reduce sampling heating. Duplicate analysis of the initial spot was performed after a five minute 255

278 cooling period to ensure a consistent signal was obtained. Spectra were collected in from of a minimum of three separate points on each sample with four scans per replicate. Raman spectra are interpreted based on the analytical methods previously established [55], and given in Table 3. Table 3. Summary of peak assignments [55] Position (cm -1 ) Peak Shape Assignment SL Gaussian Breathing modes for small aromatic regions, secondary breathing mode for 7+ membered ring S Gaussian breathing mode for rings containing 7+ carbons with Kekulé modes in adjacent benzene rings, benzene ring breathing modes adjacent to heteroatom defects DS Gaussian Assorted Breathing modes for most PAHs D Gaussian Combined breathing/kekulé vibrations for PAHs. Larger more symmetric systems show peaks near 1350 cm -1, while peaks for smaller systems move towards 1400 cm A1 Gaussian Breathing mode for 5-membered rings with Kekulé vibrations in adjacent 6-membered rings and near pure Kekulé in small ring systems and moieties A2 Gaussian Mixed breathing and asymmetric stretch vibrational modes for sp 2 carbons near defects causing out of plane deformation. Heteroatom defects tend to cause greater red shift GG Gaussian Distributed asymmetric vibrations for distribution of small PAHs GL Lorentzian Standard E2g mode for large PAHs D Gaussian Double resonance activated breathing mode *weak: E2g mode near ether inclusions C Gaussian Carbonyl stretching mode, very weak * New peak observed in this study, interpretation from figures presented previously. Nuclear magnetic resonance spectra have been collected using a quantitative multiple pass ramped cross-polarization scheme as described elsewhere [57]. The scheme is based on the original method proposed by Johnson and Schmidt Rohr [63]. A long range dipolar dephasing scheme 256

279 based on the work of Mao and Schmidt-Rohr [64] has been used to estimate approximate apparent distances between carbons and hydrogen. This method was applied to chars by Brewer et al. [65]. All spectra have been collected using a Bruker 400 Avance with a carbon channel at MHz. Samples were packed in 3.2 mm rotors and spun at 10K Hz at the Magic Angle (MAS) to minimize side bands using a Chemagnetics 3.2 mm probe. Quantitative cross-polarization was achieved by apply a train of 8 ramped CP periods with a 1.0 ms duration and % slope achieved in 64 uniform steps. Preceding and following each period a π/2 (4.7 and 4.6 μs for 1 H and 13 C respectively) pulse was used to couple and decouple C-H interactions, and a 4 s relaxation period allowed relaxation of the H. This period is sufficiently short to minimize carbon relaxation. Following polarization spectra are recorded on a Han-Echo with decouple achieved using TPPM modulation with RF fields of 60 KHz. To generate C-H free spectra standard gated decoupling is applied with a 74 us dephasing time. For dephasing longer than one rotor period (100 us) long range dipolar dephasing is employed using a REDOR type pulse train, applying π pulses on the hydrogen channel every half rotor period to decouple C-H interactions that are refocused by MAS. Full details and diagrams of these sequences are given by Smith et al. [57]. A summary of peak assignments used to quantify carbon sights is given in Table

280 Table 4. Peak assignment table Chemical Shift Assignment 5-50 ppm Aliphatic CHx ppm (slow dephasing) Aliphatic CR ppm (110 for double) Aliphatic ether ppm Aromatic C near Oxygen defects ppm Aromatic5 and 6 member rings and olefins ppm Contribution for ether bonded carbon in furans and ~ ½ of carbons in larger non oxygenated rings ppm Aromatic linked ethers ppm Carboxylic/Lactone/ester ppm Carbonyl 5.3 Results The pyrolysis of each component in the spoon reactor yielded vastly different char products. Figure 1 shows the picture of cellulose, hemicellulose and lignin chars obtained after pyrolysis at 700 o C in the spoon reactor. Cellulose forms a compact plug resembling the core of the original sample load, pulling away from the spoon wall. By contrast, xylan appears to have formed a liquid like melt phase. Substantial forming also occurs, with the final char products rising substantially above the spoon. MWL shows similar melt phase effects, however, due to the use of only half the sample mass used for either cellulose or xylan and less intense foaming, does not expand above the spoon. 258

281 Figure 1. Examples of reactant loads and product yields obtained during pyrolysis of pure components (A) example load of 1.0 grams Avicel cellulose (B) char produced from 1.0g cellulose at 700 o C (C) char produced from 1.0 g xylan at 700 o C (D) Char produced from 0.5 g of MWL at 700 o C. The temperature profiles obtained for the pyrolysis of each constituent provide additional information on the behavior of each material during treatment. Cellulose is seen to develop a strong endothermic region near 300 o C for all chars produced. This results in a plateau in the temperature vs time plot given in Figure 2A. The duration of the plateau is directly linked to the treatment 259

282 temperature, becoming less pronounced as the temperature is increased. Following this plateau temperature increases rapidly to o C (or the final set temperature, whichever is greater). Xylan, Figure 2B, shows a similar though less pronounced endothermic region. The temperature spike that follows occurs at between 300 and 400 o C, resulting in substantial deviation from a smooth curve profile. Following this sharp increase is a brief cooling period. In contrast to both the cellulose and xylan profiles, those from MWL (figure 2C) show few unusual features, rapidly heating when first inserted into the reactor and then more slowly approaching the set point temperature. No clear endothermic or exothermic regions are visible. Mild deviations are observed in the MWL 600 signal, however because of the melt form surrounding the thermocouple, these may simply be due to the formation of gas pockets around the thermocouple tip. 260

283 Figure 2. T vs time plots obtained for center of samples in spoon reactor trials respectively for (A) cellulose (B) xylan and (C) MWL 261

284 The final char yields for each constituent are given in Figure 3. MWL and cellulose both show only moderate loss (less than 30%) with heating at 300 o C, while pyrolysis of xylan at this temperature resulted in nearly 65% mass loss. As heat continues MWL shows a consistent and regular reduction in mass, while cellulose shows a rapid loss at 400 o C followed by weak but steady loss at higher temperatures. Pyrolysis of xylan resulted in additional mass loss until 400 o C, but the char structure appears to be stable after this point. Showing no significant additional mass loss up to 700 o C. Figure 3. Char yields for each of the components studied The effect of temperature on the chemical composition of char is largely predicable based on the char yields, see Table 5. Both cellulose and lignin show consistent increases in carbon content 262

285 associated loss of hydrogen and carbon as temperature increases. Xylan shows similar changes up to 400 o C, after which the composition is stabilized. Both the cellulose and lignin chars show increased FC/VC ratios with temperature, consistent with the reduced yields and increasing carbon content. Xylan however does not show a significant increase in this ratio after 400 o C. This is also consistent with the stagnation observed in char yield, however the FC/VC ratio is significantly lower than would be expected given the low oxygen content at higher pyrolysis temperatures. This effect is attributed to the high ash content catalyzing the degradation of carbon at the hold temperature of 800 o C. 263

286 Table 5. Elemental composition and FC/VC ratio for all chars (wt. %) (Dry material) Sample C H N O Ash FC/VC Cellulose Cellulose 42.8 (0.14) 6.4 (0.03) 0.06 (0.01) 50.8 (0.01) < C (0.05) 6.1 (0.05) 0.03 (0.01) 49.4 (0.09) < C (0.28) 3.9 (0.02) 0.08 (0.01) 21.5 (0.28) < C (0.17) 3.5 (0.06) 0.11 (0.02) 15 (0.13) < C (0.37) 2.7 (0.02) 0.24 (0.01) 9.3 (0.4) < C (0.11) 2.0 (0.02) 0.36 (0.01) 7.5 (0.12) <0.1% 9.70 Xylan Xylan 40.2 (0.35) 5.6 (0.07) 0.0 (0.07) 47.3 (0.37) 7.0 (0.11) 0.19 X (0.09) 4.1 (0.05) 0.1 (0.06) 16.2 (0.14) 18.3 (0.11) 1.12 X (1.46) 3.0 (0.06) 0.1 (0.07) 15.1 (1.46) 24.5 (0.11) 1.77 X (0.17) 1.9 (0.09) 0.1 (0.06) 11.1 (0.21) 24.4 (0.11) 1.73 X (0.93) 1.1 (0.06) 0.1 (0.05) 8.0 (0.93) 27.6 (0.11) 1.88 X (0.48) 1.0 (0.08) 0.1 (0.05) 7.1 (0.50) 30.3 (0.11) 2.41 Milled Wood Lignin MWL 59.8 (0.61) 3.0 (0.47) 0.2 (0.09) 37.0 (0.78) 0.0 (0.09) 0.37 MWL (0.21) 3.9 (0.47) 0.1 (0.12) 27.4 (0.54) 0.1 (0.13) 0.72 MWL (1.24) 2.1 (0.12) 0.1 (0.12) 25.1 (1.26) 0.3 (0.13) 2.10 MWL (1.12) 1.6 (1.14) 0.1 (1.12) 20.8 (2.25) 0.2 (1.12) 3.06 MWL (2.40) 1.3 (0.86) 0.2 (0.82) 10.9 (2.80) 1.1 (0.82) 7.83 MWL (0.53) 0.8 (0.41) 0.3 (0.33) 6.9 (0.87) 0.5 (0.43) The behavior observed here suggests that both cellulose and xylan react in at least 2 distinct regions, the first an endothermic region between 300 and 400 o C for cellulose and 200 to 300 o C for xylan is assigned to depolymerization and volatilization of gas and vapor products. This region is associated with a sharp decrease in total oxygen content, with a comparable increase in solid carbon. The second region, appears to be an exothermic reaction which results in a temperature spike between 300 and 450 o C likely relates to initial polycondensation of the crosslinked solid structure. This region is associated with continued loss of oxygen and hydrogen content. The 264

287 steady progression of heating observed for MWL samples suggests that each of these reactions occurs in a far more distrusted series with depolymerization, volatization and polycondensation occurring slowly over a wide temperature region Morphology of chars by SEM and CO2 Physisorption Scanning electron micrographs taken of both the pyrolyzed cellulose and xylan samples did not reveal defined melt characteristics (Figure 4). Pyrolysis of cellulose, even at 700 o C (Figure 4C) did not substantially alter the fibrous structure, though smoothing of the individual fibers and the start of agglomeration of was observed, and suggests that the external surface formed some level of a melt. This behavior suggests that the crystalline structure of at least some of the cellulose fibers maintains integrity during pyrolysis, cross-linking and poly-condensing to form a stable structure before a true melt phase can form, at least for the core particles. This may be an effect of the strong endotherm near 300 o C allowing crosslinking in the center while cellulose near the wall fully volatizes. 265

288 Figure 4. Pyrolysis progress from Raw material, to 500 o C and 700 o C for (A-C) Cellulose and (D-F) xylan. All images are taken at 100X magnification except (D) which was taken at 50X due to charging at 100X magnification. 266

289 The overall structure of xylan char is substantially less well defined than those from cellulose. Here significant particle agglomeration does occur, but the randomized and course nature of the surface is not indicative of a true melt phase. This lack of a melt phase is most likely an effect of the high alkali metal content of the as received xylan. Both sodium and potassium are known to strongly catalyze crosslinking and fragmentation reactions. Such behavior can be expected to rapidly degrade any material entering the melt phase, prevent the formation of a uniform surface. Pyrolysis of as received and acid extracted xylan using a flash pyrolysis reactor at WSU have shown that after alkali extraction a clean melt phase can be extracted (see Appendix D figure D1, kindly provided by Brennan Pecha and awaiting publication at this time). In contrast, MWL samples clearly shown the effect of the melt phase formation (see Figure 5). While the original MWL sample is a finely divided powder, these discrete particles were not visible for any of the final pyrolysis chars. Instead heavy particle agglomeration was observed at 300 o C, and at higher temperatures only a single sheet of glassy carbon was obtained. The heavy particle agglomeration observed at 300 o C is shown in Figure 5B, where despite the clear loss of particle structure, a fully liquid state was not achieved. At 400 o C (Figure 5C) a clear melt phase has been formed, pyrolysis at higher temperatures also results in the formation of the phase (Figures 5D-F). In each case, a single solid carbon residue is obtained after pyrolysis, devoid of any particle form representative of the original material. The increased heating rate experienced at higher treatment temperatures results in increasingly aggressive boil and ejection behavior for the lignin. This effect is clearly visible from the diameter of bubbles formed in the melt. Those produced at 400 o C and 500 o C are large, on the order of 100 μm or more, while those formed at 600 o C and 700 o C are on the order of 10s of μm. 267

290 Figure 5. Melt and boil progression of lignin at different pyrolysis temperatures (A) untreated (B) 300 o C (C) 400 o C (D) 500 o C (E) 600 o C (F) 700 o C 268

291 Pyrolysis of cellulose at lower temperatures was found to yield a coarse surface structure (Figure 6A), similar that that of the original fibers, while at 700 o C (Figure 6B) these structures smooth considerably, showing signs of an external melt. Xylan shows a distinctly different trend, at lower temperatures, relatively smooth, flake surfaces are observed at high magnification (Figure 6C), however at 700 o C a more textured surface (Figure 6D), containing distributed, spherical sub micrometer structures are observed. Treatment of MWL at 700 o C results in the formation of similar spherical micro and nano droplets (Figure 6F). In contrast, at lower treatment temperatures, even at 600 o C exceptionally smooth surfaces are obtained at the micrometer level (Figure 6E). These smooth surfaces are maintained even on the rupture edges of bubbles from the melt phase (see Appendix D Figure D2). The formation of these droplets suggests rapid crosslinking and condensation in the melt phase, preventing reorganization at higher pyrolysis temperatures at heating rates. 269

292 Figure 6. Surface morphology of chars from Cellulose (A) 500 o C (B) 700 o C, Xylan (C) 500 o C (D) 700 o C, and Lignin (E) 600 o C (F) 700 o C. All images are taken at 10000X magnification. 270

293 Table 6. Surface Area and average pore diameter of chars from each biomass component Sample Temperature ( o C) Cellulose SA(CO 2) W avg Xylan SA(CO 2) W avg MWL SA(CO 2) W avg Analysis of the microstructure by CO2 physisorption shows the effect of temperature on the microstructure of chars, Table 6. The surface area (SA) and average pore diameter (Wavg) of cellulose show consistent increases in surface area and reduced pore size, however an irregular trend with temperature is observed for both xylan and MWL chars at 700 o C. These trends are consistent with the behavior of xylan and MWL up to 600 o C. For xylan, extremely narrow micropores begin to form at temperatures of o C. The average estimated micropore for xylan produced at 600 o C is only approximately 30% larger than the interstitial spacing of graphite. At 700 o C this surface area collapses and larger pores on the order of 1 nm form. The same occurs with MWL chars, however average pore size formed at o C is larger, nm and the loss of surface area at 700 o C is less dramatic. This suggests that either the char formed at C was not able to a stable microporous region, or that degradation of the pore walls begins to occur above 600 o C. This may be due either to effect related to the heating rate or decomposition of the pore walls. The later may be a more likely explanation for xylan due to the presence of alkalis, which are known gasification catalysts Chemical structure of chars by spectroscopic methods X-ray diffraction analysis 271

294 Figure 7. X-ray diffraction patterns for (A) Cellulose, (B) Xylan and (C) Lignin Chars. FWHM and apparent crystal size from the Scherrer equation are given for cellulose, reproduced from Smith et al [57]. The ash free cellulose and MWL samples (Figures 7A and C), show no clear crystallographic peaks related to the carbon structures. In each case weak amorphous carbon signals can be seen near a 2θ of 25 o and relate to the (002) face of graphite, however the very broad nature of these peaks 272

295 preclude typical analysis. Application of the Scherer equation predicts discrete crystal sizes of less than 1.5 nm. Analysis of the xylan chars by XRD, Figure 7B, shows that the ash fraction varies significantly with pyrolysis temperature. Originally, no discrete ash form is present in the material, being bound primarily to organic fractions. However even at treatment temperatures as low as 300 o C the high reactivity and mobility of the K and Na is apparent, binding with Cl present in the system to produce crystalline KCl and NaCl structures. As pyrolysis temperature increase to 500 o C and higher, oxide mineral forms become prevalent, including chlorine oxides and carbon oxides XPS analysis Analysis of each char by XPS provides information on the surface chemical states for the thermoseries from each component. Both cellulose Figure 8A, and MWL, figure 8C, show clean spectra containing only C1s and O1s peaks. The wide scan spectra for the xylan series, figure 8B, by comparison shows strong contaminations of Na, K, and Cl. A clear Na 2s peak is visible near 75 ev with a strong Auger line near 500 ev. A weak associated Auger line also exists near 535 ev, contaminating the primary O 1s peak. A visible Cl peak is present near 200 ev while a doublet structure associated with the K 2p level is seen at 294 and 297 ev. The K 2p signal at 284 ev is partially contaminated by the Homo-Lumo transition associated with the C 1s peak. A second K peak, associated with the 2s level is visible near 380 ev. Approximate quantifications for each element are provided in Table

296 Figure 8. Survey scan progression for the thermoseries for (A) Cellulose (B) Xylan and (C) MWL char series. Cellulose series reproduced from material presented by Smith et al. [56]. The elemental composition of each xylan char has been estimated using line specific relative sensitivity factors for an Al Kα source. These factors are referenced to the carbon intensity. 274

297 Because of the overlap of the K2p and C 1s line, a combined integral was taken for this region and the contribution of K was estimated based on the K 2s line. This was done assuming a RSF for the combined K 2p line of The strong variation in the elemental composition of xylan chars with temperature are observed. These variances however do not show any consistent trend. Na and K vary by as much as 100% of the minimum detected quantity, while Cl shows stable content. The C and O content also show strong variation. Table 7. Approximate elemental composition from wide scan spectra of xylan (atomic %). Pyrolysis Temperature ( o C) Element Reference line RSF Na 2s Cl 2s C 1s K 2s O 1s Analysis of the Na 2s line reveals that at least 2 distinct phases exist in the pyrolysis chars, Figure 9A. The first, centered near 64 ev is in good agreement with literature values for NaCl, agreeing well with XRD data. The second peak, shifted 3-4 ev to ev is not assigned in the literature, however the association of this peak with increased intensity near 289 ev in the C 1s spectra and near 535 ev in the oxygen spectra strongly indicates the formation of carbonates, Figure 9B and 8C respectively. The distribution of these groups would suggest strongest formation of carbonates in X400 followed by X700, however this disagrees with the pattern identified by XRD, showing consistent increase in the relative intensity carbonate like peaks as pyrolysis temperature increased. The combination of inconsistent elemental composition within temperature, inconsistent variations in the form of the mineral matter and the rapid formation of crystallite forms suggests that the mineral content is heterogeneously distributed in the solid phase. 275

298 Figure 9. High resolution scans for the (A) Na 2s (B) C 1s (C) O 1s regions of the xylan spectra. Because of the uncertain mineralization of Na and K within the xylan char as well as the overlap of other spectral features within the O 1s and C 1s region, in-depth analysis of the chemical structures of these materials has not been performed. The analysis of Cellulose and MWL chars are presented in Table 8 and 9 respectively. The analysis of cellulose chars is reproduced from Smith et al. [56]. Example deconvolution of the C 1s and O 1s of MWL 600 are presented in Figure 10. Figure 10. Deconvolution of xylan 600 o C 1s and C1s regions 276

299 Deconvolution of the cellulose series shows a sharp drop in both low and high side defects for the primary C-C region. The results also demonstrate the need for a moderate asymmetry factor to properly fit the 600 and 700 o C char samples, 0.11 and 0.16 respectively. The decreases noted for the high and low defect bands are also mirrored by loss of C-O functionality with temperature. In contrast, a weak increase in C=O groups until 400 o C is observed, followed by very slow decline. Analysis of the distribution coefficients required to obtain good fit with the oxygen analysis shows that the distribution of ether groups increases consistently with treatment temperature up to 600 o C with a sharp drop at 700 o C. This drop is associated with a decreases in the C:O ratio determined from the overall scan, that is in opposition to the bulk C:O ratio determined by elemental analysis. As previously discussed, this effect has been attributed to adsorption of water/oxygen on the bare, reactive surface upon first exposure to the ambient atmosphere. 277

300 Table 8. Peak distribution and C:O ratios determined using proposed deconvolution scheme (reproduced from Smith et al. [56] Pyrolysis Temperature ( o C) Deconvolution peaks Cellulose C-C low (%) C-C Primary (%) TS (asym. factor) C-C High (%) C-O (%) O-C-O/C=O (%) O-C-O estimated COO (%) Pi-Pi* (%) C:O* O-C C=O DHE DCL The results from XPS analysis of the MWL series show a continuous increase in the overall C:O ratio as pyrolysis temperature increases for MWL, consistent with the results of cellulose. Also consist is a slight decrease in the C:O ratio for material produced at 700 o C compared to 600 o C. Because neither samples shows a related increase in bulk oxygen content, this suggests a fundamental variance in char properties that creates a more reactive surface for materials produced under nitrogen at this temperature. The high defect region of the C-C peaks also shows a continuous reduction with temperature. The low defect region, unlike cellulose shows a mildly parabolic trend, decreasing between chars 400 and 500 o C and increasing as temperature is increased above C. As with the cellulose samples, only at 600 and 700 o C was an asymmetric factor required for fitting. This factor was of similar intensity, 0.14 and 0.12 respectively. Both the carboxyl/lactone peak and the carbonyl peak were found to be stable between 400 and 700 o C 278

301 with a continuous increases in the lactone and ether character of the oxygenated groups. Unlike with cellulose chars, no decrease in this character was observed at 700 o C. Table 9. C 1s and O 1s group distribution in atomic %. Also included is the C 1s: O 1s Ratio (C:O) and the distribution coefficients denoting how the C-O and COO region are distributed between hydroxyl and ether like group and carboxyl and lactone like groups respectively. MWL Pyrolysis Temperature ( o C) Peak/property C-C low Defect C-C Primary TS C-C High Defect C-O C=O COO Pi-Pi* C:O ratio O-C O=C DEH DCL Raman Analysis The analysis of each char series by Raman spectroscopy, shown in Figure 11, highlights the highly varied structure of each material, and the significant effects that temperature and heating rate have on the underlying carbon structure. The char produced from lignin at 400 o C the cleanest separation of the D and G band regions near 1350 cm -1 and 1600 cm -1 respectively. The lack of strong intensity near 1500 indicates that only a minimum amount of cyclopentane like structures form and that 279

302 discrete polyaromatic clusters containing heteroatom defects are limited. By contrast both xylan and cellulose (show strong intensity within this region do to rearrangement and dehydration of sugar units. All chars studied contain moderate intensity near 1150 and 950 cm -1. These bands have been linked to the formation of larger rings (7+ carbons) within aromatic systems due to crosslinking between monomer units. This shoulder becomes increasingly pronounced for MWL chars as temperature increases, but shows less defined behavior for cellulose and xylan. 280

303 Figure 11. Raman Spectra progression for (A) Cellulose (B) Xylan and (C) MWL. The progression of the S, D, and G bands are highlighted by arrows for each series. The spectral series for cellulose is reproduced from Smith et al. [55] 281

304 Deconvolution of the peaks, following the method previously presented by Smith et al. [55], provides details on the position and intensity of the peaks. The contribution of various peaks to the A1g region are given in Figures 12A-C, while the E2g contributions are given by Figures 12D-F. Examining the A1g type region shows that the Ds peak, assigned to smaller aromatic ring systems, decreases continuously with increasing temperature for both cellulose and lignin. Xylan chars show a moderate decrease is the intensity of this band between 400 and 600 o C, but increases again for chars produced at 700 o C. The D band, assigned to larger ring systems, shows the opposite trend for all materials, increasing continuously for cellulose and MWL derived chars and showing a drop at 700 o C for xylan derived chars. The S bands, which have been assigned to ring systems containing 7 or more carbons were found to be largely stable at all temperatures studied for cellulose, but decreased weakly for xylan derived chars. This band increased strongly in MWL chars with temperature. The A1 band, assigned to rings with 5 carbons, increased weakly with temperature for cellulose chars, and decreased for xylan up to 600 o C. A sharp increase was observed for the xylan char produced at 700 o C. Little temperature dependence was observed for this peak in the MWL char. The total peak intensities observed for the E2g region show that the Gaussian character is largely reduced as temperature increases for all chars. This loss is offset by development of Lorentzian character within the peak structure. The A2 region, assigned to out of plane distortions, decreases with temperature for both cellulose and MWL chars and shows little dependence on temperature for xylan chars up to 600 o C. Both cellulose and xylan chars shows a strong increase in the relative intensity of this peak at 700 o C. 282

305 These results indicate a general growth both aromatic condensation and general ordering of the chars with temperature increases up to 600 o C. At 700 o C each char series shows a strong deviation within the E2g band structure characteristic of a less ordered aromatic system. These distortions do not appear to reduce aromatic condensation however and are likely the result of out of plane deformation of the larger aromatic systems. The steady increase in D band intensity is indicative of increased aromatic condensation for all chars, as is the loss of Ds intensity, which has been assigned to smaller aromatic systems. That this trend is broken for xylan chars produced at 700 o C, suggests that small aromatic regions are being exposed, whether isolated from the clusters or as unsupported benzene rings (such as in benzoperylene). The lack of temperature dependence on the S band region for cellulose and xylan suggests that the carbon structures responsible for this region (assigned as 7/8 membered rings) form early during pyrolysis and are largely stable once formed. This region increases until 500 o C for lignin before stabilizing. It is proposed that these rings form as a result of cross linking reactions and stabilize through polycondensation at higher temperatures. The presence of the A1 band in MWL chars suggests that a portion of the 5 membered rings within the chars form during crosslinking, however the intensity is substantially less than is found in low temperature cellulose and xylan chars, indicating that the furanic structures formed from dehydration of the sugar monomers likely contribute to this peak. That this band decreases continuously for xylan, an effect that may be due to the catalytic effect of the mineral matter. 283

306 Figure 12. Intensity fractions for major peaks associated with A1g type modes for chars from (A) Cellulose (B) Xylan and (C) MWL and from E2g type modes for chars from (D) Cellulose (E) Xylan and (F) MWL. Associated peak labs are listed beside the 400 o C point. Lines are provided for visual reference only. Figures A and B are reproduced from Smith et al. [55] 284

307 The position of peaks, especially the D band, can also provide information on char structure, these are given along with the FWHM for each char in table 10. Each series shows a progressive red shift in the central position of the D band as pyrolysis temperature is increased suggesting increased cluster size. While xylan chars show the weakest shift, they also show the greatest increase the D/G ratio, indicating, along with the strong shoulder near 1550 cm -1, that highly aromatic systems form from the xylan that contain significant internal defects and out of plane deformations. The mild reduction the GG band position for lignin chars likely indicates a similar, though less pronounced effect. 285

308 Table 10. Peak position (and FWHM) for deconvolution peaks used to interpret the Raman spectra of primary component chars produced at o C. Cellulose peak parameters previously presented by Smith et al. [55]. Pyrolysis Temperature o C Peak Cellulose SL 1041 (72) 1072 (111) 1073 (105) 1058 (94) S 1171 (105) 1176 (89) 1175 (89) 1179 (111) DS 1278 (105) 1265 (102) 1253 (91) 1249 (75) D 1379 (109) 1368 (114) 1355 (120) 1339 (137) A (70) 1454 (83) 1457 (100) 1457 (121) A (63) 1510 (56) 1511 (52) 1532 (85) GL 1598 (66) 1605 (81) 1605 (74) 1605 (95) GG 1579 (111) 1580 (87) 1580 (84) 1577 (50) Xylan SL 1032 (61) 1033 (51) 1029 (55) 1034 (66) S 1165 (80) 1176 (99) 1161 (83) 1160 (93) DS 1265 (110) 1258 (96) 1243 (105) 1263 (119) D 1373 (109) 1366 (130) 1362 (169) 1365 (139) A (69) 1451 (66) 1448 (51) 1439 (20) A (64) 1509 (72) 1501 (92) 1510 (122) GL 1612 (22) 1607 (37) 1599 (55) 1602 (55) GG 1592 (91) 1590 (85) 1590 (115) 1603 (107) MWL SL 1033 (52) 1036 (77) 1046 (105) 1036 (94) S 1164 (71) 1165 (108) 1173 (106) 1169 (119) DS 1296 (150) 1254 (93) 1254 (82) 1243 (57) D 1376 (88) 1368 (152) 1355 (137) 1348 (184) A (62) 1468 (72) 1466 (99) 1481 (80) A (70) 1505 (48) 1509 (55) 1514 (34) GL 1610 (27) 1604 (73) 1604 (76) 1604 (59) GG 1599 (85) 1583 (107) 1581 (94) 1579 (123) NMR Analysis Analysis of chars by NMR allows for a more quantitative assessment of composition and ring size distribution and aromatic condensation. This data also provides a much more robust assessment 286

309 of aliphatic carbon. Figure 13 provides the NMR spectra for each thermoseries of char as well as the dephasing behavior for the aromatic, ether and aliphatic regions, as determined by a least squares fit to theoretical dephasing curves [57]. The curve derived composition of each char is summarized in Table 11. Previous analysis of a series of cellulose chars showed that very little degradation of the original structure occurs at 300 o C, giving way to rapid formation of aromatic rings at 400 o C with an increasingly well-defined aromatic peak developing near 129 ppm as temperature increases to 600 o C, with a slightly more dispersive peak observed at 700 o C. Xylan chars show strong formation of aromatic carbon systems at 300 o C. Compared to the increasingly regular peak structure of the cellulose char series, those produced from xylan show much larger dispersion within the aromatic region. The most regular spectra collected from this series is produced at 500 o C, which is consistent with the Raman data presented previously. At higher temperatures the intensity on either side of the primary aromatic peak begins to increase again. xylan chars also show an unexpectedly large peak near 175 ppm. While this is typically assigned to carboxyl or lactone like groups for ash free carbons, carbonates can also present in the same region. Because this peak is observed using a cross polarization technique, it is likely that this peak is primarily the result of bicarbonates. Analysis of the lignin series demonstrates that the methoxy groups (near 55 ppm) are relatively stable at 300 ppm. By contrast some of the ether linkages have begun to react, producing a tighter distribution, and likely contributing to the preliminary melt phase. The propyl chains have also reacted fully by this point. A slightly more defined aromatic region also starts to form. At 400 o C A well-defined aromatic region is formed and nearly all methoxy groups have been degraded. A 287

310 strong shoulder centered near 140 ppm is highly indicative of larger ring systems (C7+) which results from crosslinking of monomer units. This shoulder becomes less pronounced at higher pyrolysis temperatures, resulting in a more symmetric aromatic peak. A secondary shoulder is also present in the chars centered near 150 ppm. This region is assigned to aromatic carbons bound to ether and hydroxyl like groups. This peak also decreases sharply with increasing pyrolysis temperature. The progression of these features are largely similar to those observed for cellulose. The dephasing plots for cellulose, xylan, and MWL indicate strong variance in the degree of condensation. These results are summarized as the equivalent perecent of carbon X bond distances from a hydrogen in Table 12. While both the cellulose and MWL series show a maximum cluster size approximately equal to that of circumpyrene at 700 o C, xylan shows dephasing behavior consist with a cluster similar in size to circumcoronene. It is also important to note that the initial dephasing at ms for both xylan and lignin was substantially less severe at higher pyrolysis temperatures than has been observed for cellulose. This behavior indicates that the edge sites of clusters in these chars are more substituted than in cellulose. These substitutions may be oxygenated groups, minerals, radical sites, or bridging to other clusters. 288

311 Table 11. NMR results estimated functional group contributions (atomic %). Error is approximately 2%. Cellulose data previously presented by Smith et al. [57] Sample Carbonyl Carboxyl Ether/alcohol Aromatic Aliphatic C C C C X X X X X MWL MWL MWL MWL

312 Figure 13. NMR spectra progression for (A) cellulose (B) Xylan and (C)MWL with dephasing plots for (D) Cellulose (E) Xylan and (F) MWL for D, E and F, open circles are chars produced at 300 o C, squares are 400 o C, diamonds are 500 o C, triangles are 600 o C and circles are 700 o C. Results for cellulose are reproduced from Smith et al. [57] 290

313 Table 12. NMR results estimated bonding distances for groups based on dephasing results and approximate polyaromatic equivalent size. Cellulose data previously presented by Smith et al. [57] Aromatic Carbons Ether/hydroxyl bonded carbons Aliphatics Sample C-H C-C-H C(-2)-H C(-3)-H C(-4)-H C(-5)-H C-H C-C-H C(-2)-H C(-3)-H C(-4)-H C(-5)-H C-H C-C-H C < < C < <1 100 N/A C <1 N/A N/A C N/A N/A X < X < N/A N/A X N/A N/A 291 X < N/A N/A X < N/A N/A MWL < MWL < N/A N/A MWL N/A N/A MWL < N/A N/A

314 5.4 Discussion Comparison of results between techniques Among the more costly analyses performed for these materials was the long range dephasing for NMR experiments. Char samples required an additional 4-8 spectra each comprising 2048 scans to obtain reasonable resolution. While these tests are necessary to establish the char structure, and provide the most detailed information, analysis of the Raman spectrum has also been used as a useful empirical tool for these estimations. Previous studies of graphite have shown clear negative correlation between crystallite size and the ratio of peak intensities of the D and G bands. For amorphous carbons this correlation is known to be positive, however a definitive relationship for char has been lacking. By comparing the ratio of the total area of the D band to the sum of the GG and GL bands (I(D)/I(G) given above with the total non-dephased signal at 0.8 ms from the NMR tests, a clear positive correlation is found, Figure 14. The best fit line, in relation the the I(D)/I(G) ratio is represented by Eq. 1. The calculated dephasing can be compared to that predicted for aromatic carbons such as coronene (~ 0.09), circumpyrene (~ 0.17) and circumcoronene (~0.21) to estimate the size of clusters based only on the Raman da Signal after 0.8 ms dephasing = I(D) Eq. 1 I(G) Use of this method would not provide the same detailed information presented from NMR experiments however this can provide a quick, useful tool for the characterization of aromatic condensation from more accessible Raman spectra. 292

315 Figure 14. D band peak position vs cluster size 5.4 Conclusions The analysis presented here clearly demonstrate the strong variations in both the chemical and morphological structure of chars produced by different biomass constituents at various treatment temperatures/heat rates. Both the macro and microscopic properties of the thermoseries should wide differences in surface area, aromatic ring formation, aromatic condensation and cluster shape Formation of aromatic rings was found to be prevalent at 400 o C for both cellulose and MWL chars, and showed development at 300 o C for xylan. Aromatic condensation of these structure increased slightly with heating to 500 o C, but was largely stable until treatment at 700 o C. The sharp drop in oxygen content, as well as the formation of ether like groups for residual single 293

316 bonded carbon confirms that oxygen is a primary reaction component for preliminary crosslinking and poly condensation. As pyrolysis temperature increase these ether groups are found to be distributed further from hydrogen within the aromatic structure, indicating that non-reacted edge sites are gradually incorporated into the internal cluster. Despite the considerable ring growth at 700 o C for all chars, only very mild loss of oxygen is identified from elemental analysis. This suggests that C-C bonds are forming without oxygen mediation. The increased broadness of the NMR peak and the Raman G band suggests that at these temperature the increase in ring size occurs largely in a 3 dimensional manner rather than planar. The intensities in these regions having been linked to non-hexagonal rings and out of plane distortion. By comparing the NMR dephasing data to the I(D)/I(G) ratio an approximate relation between this Raman data and cluster size has also been derived. The variances highlighted here have strong implications regarding the reactivity and adsorption potential of chars from each constituent, highlighting the importance of both feedstock selection and pyrolysis conditions on the final form of chars. Acknowledgements Dr. Garcia-Perez and Mr. Smith are very thankful for the financial support provided by the US National Science Foundation (CBET , CAREER CBET ), the Agricultural Research Center (NIFA-Hatch-WNP00701), the Washington State Department of Agriculture (Appendix A) and the Northwest Advanced Renewable Alliance (NARA) (USDA-NIFA grant No: ). 294

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325 Appendix D Supplemental Material for Chapter 5 D.1. Effect of Ash on Xylan Melt Phase A B Figure D1. Example effect of Ash on morphology of xylan. Both samples have been pyrolyzed using a vacuum flash pyrolysis reactor at WSU, images taken at 2000x magnification (A) Xylan as received (B) acid washed using dilute HCl. Images kindly provided by Brennan Pecha, to be submitted to the Journal of Analytical and Applied Pyrolysis [1]. 303

326 D.2. Bubble Wall Texture of Lignin Pyrolysis Chars Figure D2. (A) Medium and (B) high magnification of the ruptured portion of a bubble in char from MWL. The sub-micron smooth sheets are a result of a complete melt of the initial MWL and suggest a higher degree of molecular organization than is possible in materials that do not form a complete melt. 304