ECI Digital Archives. Engineering Conferences International. Matthew W. Smith Washington State University, USA

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1 Engineering Conferences International ECI Digital Archives Biochar: Production, Characterization and Applications Proceedings Novel bio-char characterization strategies and their use to study the chemical and morphological evolution of material derived from xylan, cellulose and lignin Matthew W. Smith Washington State University, USA Manuel Garcia-Perez Washington State University, USA Follow this and additional works at: Part of the Engineering Commons Recommended Citation Matthew W. Smith and Manuel Garcia-Perez, "Novel bio-char characterization strategies and their use to study the chemical and morphological evolution of material derived from xylan, cellulose and lignin" in "Biochar: Production, Characterization and Applications", Franco Berruti, Western University, London, Ontario, Canada Raffaella Ocone, Heriot-Watt University, Edinburgh, UK Ondrej Masek, University of Edinburgh, Edinburgh, UK Eds, ECI Symposium Series, (2017). This Abstract and Presentation is brought to you for free and open access by the Proceedings at ECI Digital Archives. It has been accepted for inclusion in Biochar: Production, Characterization and Applications by an authorized administrator of ECI Digital Archives. For more information, please contact

2 Novel Bio char Characterization Strategies and their use to Study the Chemical and Morphological Evolution of Carbonaceous Materials Derived from Xylan, Cellulose and Lignin Manuel Garcia Perez, Matt Smith, Waled Suliman Conference: Bio char: Production, Characterization and Applications Engineering Conference International August Hotel Calissano, Alba, Italy

3 Outline Introduction Section I: Characterization Methods Challenges and Modifications Raman XPS NMR Section II: Production and Analysis of Chars from Primary Components Conclusions and Recommendations

4 Goals and Objectives: To improve the analysis by and interpretation of spectra from Raman, XPS and NMR To analyze the changes to the chemical structure of chars from primary biomass components associated with treatments Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016, Smith MW, Helms G, McEwen J-S, Garcia-Perez M: Effect of pyrolysis temperature on aromatic cluster size of cellulose char by quantitative multi cross-polarization 13C NMR with long range dipolar dephasing. Carbon, 116, 2017, Smith M, Scudeiro L, Espinal J, McEwen JS, Garcia-Perez M: Improving the deconvolution and interpretation of XPS spectra from chars by ad initio calculations. Carbon, 110, 2016, Smith MW, Pecha M, Helms G, Scudeiro L,Garcia-Perez M: Chemical and morphological evaluation of chars production from primary biomass consitituents: Cellulose, xylan and lignin. Biomass and Bioenergy 104, 2017, 17-35

5 Introduction:

6 Introduction: Fullerene grouping of fullerene like units McDonald-Wharry et al McDonald-Wharry J S, Manley-Harris M, Pickering K L. Reviewing, Combining, and Updating the Models for the Nanostructure of Non-Graphitizing Carbons Produced from Oxygen-Containing Precursors. Energy and Fuels 2016.

7 Introduction: Where are the deficits in Understanding? Challenges to Characterization (problem to be solved) Spectroscopic interpretation methods are based on clean systems Raman interpretation is based on graphite Deconvolution of C1s peaks are seldom self consistent with corresponding O1s peaks NMR requires excessively long acquisition times for quantitative analysis Improving the analysis and application of these techniques will provide superior information on the morphology and formation of chars Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016, Smith MW, Helms G, McEwen J-S, Garcia-Perez M: Effect of pyrolysis temperature on aromatic cluster size of cellulose char by quantitative multi cross-polarization 13C NMR with long range dipolar dephasing. Carbon, 116, 2017, Smith M, Scudeiro L, Espinal J, McEwen JS, Garcia-Perez M: Improving the deconvolution and interpretation of XPS spectra from chars by ad initio calculations. Carbon, 110, 2016, Smith MW, Pecha M, Helms G, Scudeiro L,Garcia-Perez M: Chemical and morphological evaluation of chars production from primary biomass consitituents: Cellulose, xylan and lignin. Biomass and Bioenergy 104, 2017, 17-35

8 Section I Characterization Methods Challenges and Modifications Raman Spectroscopy Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016,

9 SI Methods: Raman Spectroscopy - Introduction Literature Fit Results 2 peak model used by Ferrari, suable for graphite Method of Hu et al. attempts to analyzes shoulder and valley Method of Li et al. used to analyze coal samples with 1064 nm laser?????? Regions of Uncertainty: (1) Shoulders observed in the defect (D) band ( cm -1 ) (2) High intensity Valley between the D and graphitic (G) band ( cm -1 ).

10 SI Methods: Raman Spectroscopy - Methods Experimental Spectra of PAH collected on 1064 nm FT-Raman System Compared experimental to theoretical spectra obtained from DFT calculation [B3LYP 6-31G(d)] Assorted defect structures examined for patterns in available vibrational modes Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016,

11 SI Methods: Raman Spectroscopy Modeling Comparison of Theoretical and Real Raman Spectra Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016,

12 SI Methods: Raman Spectroscopy - Introduction Major Carbon Breathing Modes D-Band the A1g breathing mode Kekulé G-Band the E2p Mode Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016,

13 SI Methods: Raman Spectroscopy Modeling Raman spectrum of cyclopentane and cycloheptane centered cluster Band moved Two new bands Primary A1g like modes are highlighted for each structure Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016,

14 SI Methods: Raman Spectroscopy Modeling Effect of single point defects Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016,

15 SI Methods: Raman Spectroscopy Results Summary of fit parameters 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 Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016,

16 SI Methods: Raman Spectroscopy Results Mixed breathing Breading modes for systems with more than 7 membered ring Breading modes for 5 members rings with Kekule vibrations Smith MW, Dallmayer I, Johnson TJ, Brauer C.S., McEwen J-S, Espinal JF, Garcia-Perez M: Structural analysis of char by Raman Spectroscopy: Improving band assigments through computational calculations from first principals. Carbon 100, 2016,

17 Section I Characterization Methods Challenges and Modifications X-ray Photoelectron Spectroscopy Smith M, Scudeiro L, Espinal J, McEwen JS, Garcia-Perez M: Improving the deconvolution and interpretation of XPS spectra from chars by ad initio calculations. Carbon, 110, 2016,

18 SI Methods: XPS Introduction Literature based deconvolution methods for C1s C-C (symatric and asymmetric), C-O, C=O, and COO Secondary C-C peak commonly shifted by ev from the first is variously attributed to defect structures and sp 3 carbon. The defective peak assignment near 284 ev is also assigned to defective carbon structures.

19 SI Methods: XPS Introduction Quantification of oxygen from C1s spectrum Three quantification schemes were use to quantify total oxygen content from C1s New C1s deconvolution 2 Eq. 1a Eq. 1b Eq. 1c Most common method: Sum of intensities of C-O, C=O and twice COO Assumes that C-O bonds are evenly distributed between C bound hydroxyl groups and ethers by assigning a sensibility factor of 0.75 to the C-O bonds. Assumes that the enterity of the C- O signal results from ether bonds ad lactones. 1 2 Eq. 2 DHE: 0 for all hydroxyl and 1 for all ethers, DCL: 0 for all carbonyl and 1 for all lactone Smith M, Scudeiro L, Espinal J, McEwen JS, Garcia-Perez M: Improving the deconvolution and interpretation of XPS spectra from chars by ad initio calculations. Carbon, 110, 2016,

20 SI Methods: XPS Introduction C1s and O1s spectra for cellulose chars C1s O1s

21 SI Methods: XPS Introduction Symmetric Deconvolution Results XPS Deconvolution Peaks (% of total peak area) Calculated C:O distribution (deviation from C1s: O1s) Method C-C C-C C-C Sample low high 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%)

22 SI Methods: XPS Methods A thermoseries of chars and PAH refereces were analyzed using a Kratos XPS with a Mg Kα source Theoretical BE were calculated assuming an initial state approximation based on core BE determined from NBO analysis [6-311G(d,p)] Broadening factors were determined empirically based on best fit with experimental specta Theoretical defects were broadened using the average parameters Smith M, Scudeiro L, Espinal J, McEwen JS, Garcia-Perez M: Improving the deconvolution and interpretation of XPS spectra from chars by ad initio calculations. Carbon, 110, 2016,

23 SI Methods: XPS Modeling Real vs. theoretical spectra C1s Pyrene Cellobiose PTCDA Cellobiose Smith M, Scudeiro L, Espinal J, McEwen JS, Garcia-Perez M: Improving the deconvolution and interpretation of XPS spectra from chars by ad initio calculations. Carbon, 110, 2016,

24 SI Methods: XPS Modeling (Effect of defects on C- C core electron binding energies) Example: Circumpyrene defect Effect of Stone-Wales defect on spectra (Full-width-at-half-maximum) FWHM =1.55 FWHM =0.55 Circumcoronene: C 54 H 18 Circumpyrene: C 42 H 16 Coronene: C 24 H 12 Smith M, Scudeiro L, Espinal J, McEwen JS, Garcia-Perez M: Improving the deconvolution and interpretation of XPS spectra from chars by ad initio calculations. Carbon, 110, 2016,

25 SI Methods: XPS Modeling Effect of edge site oxygen on binding energies Hydroxyl Carbonyl Carboxyl Lactone Smith M, Scudeiro L, Espinal J, McEwen JS, Garcia-Perez M: Improving the deconvolution and interpretation of XPS spectra from chars by ad initio calculations. Carbon, 110, 2016,

26 SI Methods: XPS Results SI Methods: XPS Results Summary of fit bounds and assignments 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 2 O) 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

27 SI Methods: XPS Results Proposed C1s-O1s combined deconvolution algorithm Demonstration Smith M, Scudeiro L, Espinal J, McEwen JS, Garcia-Perez M: Improving the deconvolution and interpretation of XPS spectra from chars by ad initio calculations. Carbon, 110, 2016,

28 Section I Characterization Methods Challenges and Modifications NMR Spectroscopy Smith MW, Helms G, McEwen J-S, Garcia-Perez M: Effect of pyrolysis temperature on aromatic cluster size of cellulose char by quantitative multi cross-polarization 13C NMR with long range dipolar dephasing. Carbon, 116, 2017,

29 SI Methods: NMR Introduction NMR is an extremely powerful tool for chemical structure characterization Quantification of solid carbons has typically required direct polarization with long relaxation times. Recently a sequential multi pass CP scheme has been proposed as a substitute to reduce acquisition time Long range dipolar dephasing has been proposed as a method to analyze the cluster size of carbons, but never used with a MultiCP scheme for quantification. Smith MW, Helms G, McEwen J-S, Garcia-Perez M: Effect of pyrolysis temperature on aromatic cluster size of cellulose char by quantitative multi cross-polarization 13C NMR with long range dipolar dephasing. Carbon, 116, 2017,

30 SI Methods: NMR Introduction Effect of multiple CP passes Polarization Building with multi-cp Comparison with DP Smith MW, Helms G, McEwen J-S, Garcia-Perez M: Effect of pyrolysis temperature on aromatic cluster size of cellulose char by quantitative multi cross-polarization 13C NMR with long range dipolar dephasing. Carbon, 116, 2017,

31 SI Methods: NMR Modeling Theoretical NMR shifts Smith MW, Helms G, McEwen J-S, Garcia-Perez M: Effect of pyrolysis temperature on aromatic cluster size of cellulose char by quantitative multi cross-polarization 13C NMR with long range dipolar dephasing. Carbon, 116, 2017,

32 SI Methods: NMR Results 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 Region assignments Smith MW, Helms G, McEwen J-S, Garcia-Perez M: Effect of pyrolysis temperature on aromatic cluster size of cellulose char by quantitative multi cross-polarization 13C NMR with long range dipolar dephasing. Carbon, 116, 2017,

33 Section II Production and Analysis of Chars from Primary Components Smith MW, Pecha M, Helms G, Scudeiro L,Garcia-Perez M: Chemical and morphological evaluation of chars production from primary biomass consitituents: Cellulose, xylan and lignin. Biomass and Bioenergy 104, 2017, 17-35

34 SII Char analysis: Char Production Spoon Reactor Smith MW, Pecha M, Helms G, Scudeiro L,Garcia-Perez M: Chemical and morphological evaluation of chars production from primary biomass consitituents: Cellulose, xylan and lignin. Biomass and Bioenergy 104, 2017, 17-35

35 SII Char analysis: Char Production Heating profiles and final char for each component Cellulose Xylan MWL Initial Pack Xylan Cellulose MWL

36 SII Char analysis: Char Production Effect of temperature on char yield Smith MW, Pecha M, Helms G, Scudeiro L,Garcia-Perez M: Chemical and morphological evaluation of chars production from primary biomass consitituents: Cellulose, xylan and lignin. Biomass and Bioenergy 104, 2017, 17-35

37 SII Char analysis: Char Production Effect of temperature on surface area Sample Temperature ( o C) Cellulose SA(CO 2 ) W avg Xylan SA(CO 2 ) W avg MWL SA(CO 2 ) W avg Smith MW, Pecha M, Helms G, Scudeiro L,Garcia-Perez M: Chemical and morphological evaluation of chars production from primary biomass consitituents: Cellulose, xylan and lignin. Biomass and Bioenergy 104, 2017,

38 SII Char analysis: Spectroscopic Characterization XPS results Cellulose Xylan MWL XPS Smith MW, Pecha M, Helms G, Scudeiro L,Garcia-Perez M: Chemical and morphological evaluation of chars production from primary biomass consitituents: Cellulose, xylan and lignin. Biomass and Bioenergy 104, 2017,

39 SII Char analysis: Spectroscopic Characterization Deconvolution of Cellulose and Lignin XPS results 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 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 D EH D CL Smith MW, Pecha M, Helms G, Scudeiro L,Garcia-Perez M: Chemical and morphological evaluation of chars production from primary biomass consitituents: Cellulose, xylan and lignin. Biomass and Bioenergy 104, 2017, 17-35

40 SII Char analysis: Spectroscopic Characterization Raman spectra and deconvolution results Cellulose Xylan MWL Spectra A1g modes E2g modes 39

41 SII Char analysis: Spectroscopic Characterization NMR dephasing results Cellulose Xylan MWL Spectra Aromatic Dephasing Circle: 300 o C, squares: 400 o C, diamonds: 500 o C, triangles: 600 o C, spheres: 700 o C Smith MW, Pecha M, Helms G, Scudeiro L,Garcia-Perez M: Chemical and morphological evaluation of chars production from primary biomass consitituents: Cellulose, xylan and lignin. Biomass and Bioenergy 104, 2017, 17-35

42 SII Char analysis: Spectroscopic Characterization Example structures based on dephasing results

43 SII Char analysis: Spectroscopic Characterization Comparison of NMR dephasing and I(D)/(G T ) ratio 42

44 SII Char analysis: Conclusions Each component shows increasing cluster size as temperature increases At 700 o C disordered rings cause significant out of plane deformations Xylan was found to show significantly more rapid order-attributed to ash Lignin requires higher temperatures to develop non-hexagonal rings Cellulose develops largely isolated ring structures, while Xylan and Lignin clusters are more heavily crosslinked

45 ACKNOWLEDGEMENT We would like to thank the funding agencies supporting my Research Program WASHINGTON STATE UNIVERSITY AGRICULTURAL RESEARCH CENTER U.S. NATIONAL SCIENCE FOUNDATION WASHINGTON STATE DEPARTMENT OF AGRICULTURE SUN GRANT INITIATIVE, U.S. DEPARTMENT OF TRANSPORTATION, USDA WASHINGTON STATE DEPARTMENT OF ECOLOGY U.S. DEPARTMENT OF ENERGY

46 Thank you Questions?

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