Combustion Chemistry of a New Biofuel: Butanol

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Lorraine Butler
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1 Combustion Chemistry of a New Biofuel: Butanol William H. Green, D.F. Davidson, F. Egolfopoulos, N. Hansen, M. Harper, R.K. Hanson, S. Klippenstein, C.K. Law, C.J. Sung, D.R. Truhlar, & H. Wang

2 Assessing Alternative Fuels: The Challenge of Predicting Performance Hundreds of possible alternative fuels: What do we want? We can specify the fuel composition Sometimes precise control: bioengineering, catalysis from H2 Which fuels give special performance advantages? Do any enable advances in engine technology? Performance gain could help biofuel enter market. Predict performance of a new fuel in a new engine? or do we need to experimentally test every possible engine/fuel combination? Computer simulations of combustion becoming practical. Rate constants, thermo from quantum calculations Validate predictions with experiments

3 CEFRC s First Test Case: Butanol Why Butanol? Bio butanol is about to be commercialized Strong demand for an accurate computer model Butanol has some advantages over ethanol More soluble in gasoline Can be used at higher blending ratios Can be shipped in gasoline pipelines Lower vapor pressure: less smog When CEFRC started, very few data or models available on butanol combustion Small molecule, but big enough Simpler chemistry than e.g. diesel range fuels Feasible to do high accuracy quantum chemistry Experimentally convenient: easy to vaporize Interesting: Several isomers with quite different chemistry

4 Dozens of Center members all studying butanol in parallel Tied together by connections with the MIT team assembling the kinetic model As examples, here we show data and calculations from these groups: C.K. Law (Princeton) flame speeds, flame ball F. Egolfopoulos (USC) flame speeds, extinction Nils Hansen (Sandia, ALS) species in flames S. Klippenstein (Argonne) quantum chemistry Ron Hanson (Stanford) ignition delays, species C.J. Sung (Connecticut) ignition delays Other data and calculations not shown because of the time

Equivalence Ratio Propane n-propanol iso-butanol tert-butanol

5 Flame Speeds for Different Fuels: Not Intuitive. Need a Model! Methanol sec-butanol n-butanol Ethanol Flame Speed n-butanol Equivalence Ratio Propane n-propanol iso-butanol tert-butanol Butanone iso-propanol Acetone Measured in Egolfopoulos lab (USC). Air, 1 atm.

6 Different Reaction Paths Important at different combustion conditions Big consequences: ignition, soot-formation, toxic emissions

7 Thermal Decomposition of C 4 H 9 O radical critical in n butanol combustion n butanol Isomerization β radical H abstraction by H, OH, O, α radical γ radical Decomposition: 1 butoxy β scission, cyclization, C C, C O bond fission δ radical

8 Quantum Chemistry allows us to compute rates k(t,p) of all C 4 H 9 O Decomposition Reactions epoxybutane + H 19.8 cyclopropymethanol + H methyl-oxetane + H 18.6 methylcyclopropanol + H C 4 H 8 +OH vdw cyclobutanol + H butenol + H butenol + H butenol + H tetrahydrofuran + H butanal + H -4.3 ethylene + ethanol radical CH propen-1-ol propene + CH 2 OH ethyl + ethenol pentyl + CH 2 O CH 3 CH 2 CHCH 2 OH CASPT2 (3e,3o)/ADZ CH 2 CH 2 CH 2 CH 2 OH CH 3 CH 2 CH 2 CH 2 O CH 3 CH 2 CH 2 CHOH CH 3CHCH 2 CH 2 OH B3LYP/ G(d,p) Calcs by S. Klippenstein (Argonne)

Combustion has been studied for a long time, but still quite challenging Current CEFRC Chemistry Model: 334 species reacting via 7113 reactions 4288 of the reactions have complicated non-arrhenius

9 Combustion has been studied for a long time, but still quite challenging Current CEFRC Chemistry Model: 334 species reacting via 7113 reactions 4288 of the reactions have complicated non-arrhenius k(t,p) Photograph of a Butanol/Air flame in internal combustion engine conditions (measured in C.K. Law s lab, Princeton) Numerical issues in solving the model, but possible to do it. Tricky to know true boundary conditions in many combustion experiments.

10 Most important fuel performance property: ignition Gasoline Octane Number Diesel Cetane Number Small changes in fuel make big changes in ignition: sensitive to molecular structure! New engines under development are even more sensitive to ignition Potential for big gains but only if the fuel ignition delay time matches engine requirements

11 Stanford Shock Tube Measurements: Butanol Ignition Delay Time N Butanol Butanol Isomers K 1250 K P = 1.5 atm, = 1 P = 3.0 atm, = 1 P = 19 atm, = P = 19 atm, = 1 P = 43 atm, = P = 43 atm, = 1 Lines = Grana et. al. (2010) 1111 K 1.5 atm 3.0 atm 19 atm 43 atm 1000 K K 1471 K 1316 K 1190 K 1-butanol 2-but 2-butanol i-butanol t-butanol Lines - Grana et. al. (2010) 1-but t ign [us] 100 4% O 2 /Ar t ign [us] 100 t-but i-but 4% O 2 /Ar 1.5 atm /T 5 [1/K] /T 5 [1/K] Ignition delay time database provides wide coverage of pressure and temperature Tert butanol has significantly longer ignition delay times than other isomers

12 Model accurately predicts Stanford high-t ignition delays Ignition delay / s CH 3 H 3 C OH H 3 C = 1.0 = 0.5 Ignition delay / s OH = 1.0 = 0.5 = K / T = K / T 10 3 HO CH OH H 3 C CH 3 Ignition delay / s 10 2 CH 3 = 1.0 = 0.5 Ignition delay / s 10 2 CH 3 = 1.0 = 0.5 = 0.25 = K / T K / T

Engines Sensitive to Ignition at High Pressure and Low Temperature Rapid Compression Machine Investigation of low-temperature, highpressure autoignition is relevant to many emerging engine

13 Engines Sensitive to Ignition at High Pressure and Low Temperature Rapid Compression Machine Investigation of low-temperature, highpressure autoignition is relevant to many emerging engine technologies GCMS sampling results prior to experiments confirm mixture composition preparation procedure when handling liquid fuels Gas samples from the reaction chamber for GC-MS/FID analysis allow identification and quantification of important species during autoignition C.J. Sung group, U. Conn.

14 Autoignition Studies of Butanol Isomers at High Pressure and Low Temperature Pressure, bar n-butanol/o 2 /N 2, =1.0, P C =15 bar Butanol/O 2 /N 2, =1.0, P C =15 bar T C 839 K 816 K 784 K 758 K 737 K 725 K Ignition Delay, ms Non-Reactive Case tert-butanol iso-butanol sec-butanol n-butanol O 2 : N 2 = 1 : Time, ms /T C, 1/K O 2 : N 2 = 1 : 3.76 n-butanol ignition is much faster than the other butanol isomers for T< 900 K Measured in C.J. Sung lab (U.Conn.)

15 Big Discrepancy: Model did not predict the fast n butanol ignition observed at T < 900 K! Model was built automatically using computer expert system Due to mistake in rate database used by expert system, model wildly mis-estimated barrier for HO2 + C-H reactions.

16 Big Discrepancy: Model did not predict the fast n butanol ignition at T < 900 K! Model was built automatically at MIT using computer expert system Due to mistake in rate database used by expert system, model wildly mis-estimated barrier for HO 2 + C-H reactions. After correcting that big mistake, current CEFRC model is much closer but still not quite right at lowest temperatures. Work continues

17 Multi Species Time Histories Provide Stronger, More Informative Tests of Model: n Butanol Pyrolysis OH H 2 O CH 2 O OH [ppm] Measured LLNL (Curran) U of Toronto (Sarathy) MIT (Harper) Italy (Grana) RPI/France (Moss) 1% n-butanol in Ar T = 1342 K P = 1.51 atm time [ s] H 2 O [%] Measured LLNL (Curran) U of Toronto (Sarathy) MIT (Harper) Italy (Grana) RPI/France (Moss) time [ s] 1% n-butanol in Ar T = 1342 K P = 1.51 atm CH 2 O [%] 0.4 Measured 1% n-butanol in Ar LLNL (Curran) T = 1352 K U of Toronto (Sarathy) P = 1.48 atm MIT (Harper) 0.3 Italy (Grana) RPI/France (Moss) time [ s] Current status: Stanford species time history measurements for OH, H 2 O and CH 2 O Next step: laser absorption measurements of CO and C 2 H 4 All models underpredict formaldehyde and H 2 O formed in high T n butanol pyrolysis

Advanced Light Source allows direct detection of dozens of species including

analyzed with molecular beam time of flight mass spectrometry Photoionization

$species by mass by ionization energy Experimental mole fraction profiles are$

18 Advanced Light Source allows direct detection of dozens of species including key radicals Photoionization Molecular Beam Mass Spectrometry Flames are analyzed with molecular beam time of flight mass spectrometry Photoionization with tunable synchrotron generated VUV photons allows identification of species by mass by ionization energy Experimental mole fraction profiles are compared with flame model predictions and reaction path and sensitivity analysis are performed

$Advanced Light Source (ALS) Flame Data: Detailed Test of the Model s Predictive Capabilities Mole fraction profiles of the major species are predicted accurately A more powerful test is provided by$

19 Advanced Light Source (ALS) Flame Data: Detailed Test of the Model s Predictive Capabilities Mole fraction profiles of the major species are predicted accurately A more powerful test is provided by comparing modeled and experimental profiles of intermediate species Profiles have not been shifted Oßwald et al. flame data need to be shifted for better agreement Only a few of the many data traces shown here most show good agreement

20 One big discrepancy identified between model and ALS data: C 4 H 4 and C 3 H 3 overpredicted Sensitive to C 4 H 5 Thermochemistry Simulations of the flames studied by ALS are sensitive to the enthalpy of formation of i C 4 H 5 (CH 2 =CH C=CH 2 CH 2 CH=C=CH 2 ). None of the other available experimental data are sensitive to this number. This radical s enthalpy value was incorrect in the MIT database. Correcting to the accepted literature value largely resolved the discrepancy. Now investigating origins of smaller discrepancies

21 Conclusions Teams can move fast! In less than 2 years, went from zero to quite good model for butanol combustion, comprehensively validated by many different types of experiments. Contrast: sequential single investigator model building and comprehensive validation usually takes decades. Certainly we can do it even faster next time through Very promising for other alternative fuels: do you have a fuel we should model? Focus on the discrepancies (models vs. expts, and expts vs. expts.): that is where there is an opportunity to learn something! Don t be shy: expose the discrepancies to your EFRC teammates!

Detailed chemistry models for butanols based on ab initio rate coefficients, and comparisons with experimental data

Detailed chemistry models for butanols based on ab initio rate coefficients, and comparisons with experimental data William H. Green, Michael Harper, Mary Schnoor, & Shamel Merchant CEFRC Annual Meeting