RECENT ADVANCES (& CONTINUING CHALLENGES) IN COMBUSTION CHEMISTRY WILLIAM H. GREEN Co-Authors: Shamel S. Merchant 1 , Aaron G. Vandeputte 1 , Connie W. Gao 1 , Nick M. Vandewiele 1,2 , Nathan W. Yee 1 , Marko R. Djokic 2 , Kevin M. Van Geem 2 , & Guy B. Marin 2 1) Department of Chemical Engineering, MIT 2) Laboratory for Chemical Technology, UGent, Ghent, Belgium $$$: DOE, AFOSR, FWO, BAEF, Flanders Methusalem, US Navy 1
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RECENT ADVANCES (& CONTINUING CHALLENGES) IN COMBUSTION CHEMISTRY WILLIAM H. GREEN Co-Authors: Shamel S. Merchant 1, Aaron G. Vandeputte 1, Connie W. Gao.
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RECENT ADVANCES (& CONTINUING CHALLENGES) IN COMBUSTION CHEMISTRY
WILLIAM H. GREEN
Co-Authors: Shamel S. Merchant1, Aaron G. Vandeputte1, Connie W. Gao1, Nick M. Vandewiele1,2, Nathan W. Yee1, Marko R. Djokic2, Kevin M. Van Geem2, & Guy B. Marin2
1) Department of Chemical Engineering, MIT 2) Laboratory for Chemical Technology, UGent, Ghent, Belgium
$$$: DOE, AFOSR, FWO, BAEF, Flanders Methusalem, US Navy
2
Combustion is Critically Important• Provides about 80% of our energy
– Transportation, heating, electricity production…– …Will still be main energy source in 2040. – Crucial to Economy! GDP scales with energy use.
With current technology,Developed countries burn100 GJ/y per person.
1010 people * 1011 J/y = a lot of combustion!
GDP/person ($)
Ener
gy/p
erso
n (G
J/y)
3
Combustion is Biggest Source of Greenhouse Gases
We need to keep [CO2] < 550 ppm to have reasonable chance ofavoiding catastrophic climate change. Need to drastically reduce slope of this graph very soon!
4
Epidemiology is clear: Soot KillsM
orta
lity
Rate
6-Cities Study, USADockery et al.N Engl J Med 1993
Particulate Level in Air
5 years lessLife expectancyNorth of river
Yuyu Chen et al. PNAS 2013;110:12936-12941
Huai River policy: coal burners north ofriver, no heat south of river. Life spanmuch shorter on north side of river. Health impacts significantly slow economic growth.
Strong correlation between Deaths and Particulates, seen repeatedly in many differentlocations & situations.
5
What is needed?• Big Increases in fuel-to-work efficiency!
– Reduces CO2 emissions and fuel cost– Less fuel burnt: reduces other emissions– Major approach: premixed low-T combustion
• Avoid fuel-rich pyrolysis forming soot• Low T: Less heat losses, less NOx formation• But sensitive to ignition delay & flame extinction
• Renewable (i.e. non-fossil) fuels – How to make them cheaply, in huge volumes…– … and predictions of their performance
• Ways to reduce Soot (Particulate) emissions– Based on understanding of soot formation/oxidation
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Where are we with soot?
• Existing soot formation models include irreversible reactions… …something is fundamentally wrong.
• See e.g. Hai Wang, Proc. Combust. Inst. (2011)
• Existing soot oxidation models are extremely simplistic. • More work is needed!• Soot burn-out is usually incomplete: why?
Good progress on early steps of polycyclic formation And graphene-sheet edge chemistry, e.g. P23 See talks by Klippenstein & Ross, PES calculations by Mebel
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C5H5+C5H5 naphthalene (C10H8) …how?
Many models say C5H5+C5H5 C10H8 + H + HBut this is too slow
Instead:
C5H5 + C5H5 = C10H10C10H10 + R C10H9 +RHC10H9 C10H8 + H See poster by Marko Djokic for relevant expts
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Where are we with Flame Extinction?
• Crucial in turbulent flames– Flame-holding, stability– Acoustic noise, pressure oscillations–Maybe important in soot break-through?
• Some understanding of strain-induced flame extinction [e.g. S.H.Won et al. Combust. Flame (2012) ]…
…but so far we haven’t demonstrated we can predict flame extinction for new fuels
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For the rest of this talk, I’ll focus on
Methodology for Predicting (non-sooting, unstrained) Combustion Chemistry of new fuels
and on
Low-T Ignition
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Combustion Chemistry Mechanisms are Huge
Use computer to build the model!
0
500
1000
1500
2000
2500
3000
3500
4000
4500
0 1 2 3 4 5 6 7 8 9
Carbon Number
Num
ber
of R
eact
ions
0
200
400
600
800
1000
Num
ber
of S
peci
es
hydrogen
iso-octane(Curran et al.)
n-heptane(Curran et al.)
n-butane(ENSIC Nancy)
propane(Marinov)methane
(GRIMech3.0)
PRF(Curran et al.)
Never enough experimental data to determine all the k(T,P): must work in predictive mode, based primarily on quantum chemistry.
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SimulationequationsdY/dt = …
Interpreter(CHEMKIN,
Cantera, KIVA, GTPower)
Very longlist of
reactionswith rate
parameters
Simulation predictions
Commercial software can solvelarge kinetic simulations……if one can supply thereaction mechanism.
Diff. Eq. solver
12
How we construct chemistry models
SimulationequationsdY/dt = …
Interpreter(CHEMKIN,
Cantera, KIVA, GTPower)
Very longlist of
reactionswith rate
parameters
Simulation predictions
Unambiguousdocumentation of assumptions
about how molecules react
Chemistry knowledge
Diff. Eq. solver
High-accuracy quantum calculations on sensitive parameters
Sensitivity Analysis
13
RMG method: computer builds the kinetic model, based on first-principles.
represent species unambiguously determine reactions that species undergo
estimate rates from quantum chem determine which species belong in model
14
RMG software has several advanced features, all automatically & consistently applied
pressure-dependent kinetics estimation solvation thermochemistry , some kinetics
Sulfur chemistry (and Nitrogen too) automatic quantum chemistry for cyclics
15
Chemical Kinetic Modeling Challenges• Identify all important reactions & species
– But not unimportant species & reactions: how to distinguish?
• Compute all reaction rate coefficients (and properties, e.g. thermochemistry) to sufficient accuracy.
– We use Functional Group extrapolations & Quantum Chemistry
• Large models pose numerical and computer problems– Very challenging for humans to handle, interpret, debug… …SO WE TRY TO AUTOMATE EVERYTHING
We build on prior efforts by large research community, e.g. Thermochemical Kinetics (1974)
Comprehensive Chemical Kinetics 35 (1997)Advances in Chemical Engineering 32 (2007)Cleaner Combustion: Developing Detailed Models (2013)
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RMG algorithm: Faster pathways explored further, growing the model
Open-Source RMG software.Download from rmg.sourceforge.net
“Current Model” inside.RMG decides whetheror not to add species tothis model. Final model typically~500 species, 8000 rxns
After:
Before:
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Rate-Based Algorithm is Sensitive to Errors in Rate & Thermo Estimates
• Particularly Important to get the Thermo Right: In Combustion typically many species are in partial equilibrium with each other
Hcorrected =
Hquantum
+ correctionfor each C-C bond,each C-O bond, etc.
DFT (B3LYP)
CBS-QB3
CCSD(T)-F12/TZ
CCSD(T)-F12/QZ
Error (Expt(ATcT) – Quantum) 2 kcal/tick mark
Quantum Enthalpy Predictions Improve a Lot withEmpirical Bond-Additivity Corrections (BAC)
18
BAC (mostly) fix enthalpies, but leave discrepancies in computed barrier heights
Compute slightly different Barrier dependingon which directionyou computethe reaction.Significant atRoom T.
In this case the inconsistency is ~0.6 kcal/mole: = 35% error at 1000 K, factor of 2.7 at 300 K. 19
Kinetic Model Predictions Rely on Quantum Chemistry for Rates: These are not Perfect!
• Functional Group approximation– Compute a few examples of each reaction type with quantum, then use same barrier, A factor for analogous reactions.
• Most of our calculations at CBS-QB3 level– Geometries, Vibrational Frequencies from DFT– Single point energies at stationary points at higher level– Extrapolation to Basis Set Limit
• Recent calculations use F12 methods – Explicit dependence on distance between every pair of electrons– Much faster basis set convergence
• Most calculations rely on several common approximations– Rigid-Rotor Harmonic-Oscillator approximation – Conventional Transition State Theory (dividing surface at saddle point) – Simple corrections for internal rotors and tunneling– Modified Strong Collision approx. for k(T,P)
Are computed thermo, rates accurate enough?? 20
Are computed thermo, rates accurate enough??• Conventional Quantum Chemistry methods have errors:
a few kcal/mole in energiesa few cal/mole-K in entropies and heat capacitiesperhaps a factor of 2 due to internal rotor approximationsabout a factor of 2 due to TST approximations
• Several different errors, each about factor of 2 uncertainty• Lucky if a computed rate is within a factor of 2 of the truth• Can we live with a factor of 2 uncertainty in each of 104 rate
coefficients?• Fortunately, most sensitivities d(ln(observable))/d(ln(k)) are
0.5 or less – many uncertainties are uncorrelated so they might “average out”.
Need to test if this really works out OK!21
Pyrolysis(shock tube)
flow
rea
ctors
RCM
Shock tube
MBMS
Rare Situation where detailed data available at many different conditions!
With collaborations from other institutes
e.g. Univ. Ghent, NIST. FlameSpeed
s
FlameSpeeds
Testing Accuracy of Model Predictions vs.Experiment: Extensive Data available on Pyrolysis, Combustion, Oxidation of Butanols
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We used RMG to build a mechanism for butanol pyrolysis and combustion.
Shamel S. Merchant, E.F. Zanoelo, R.L. Speth, M.R. Harper, K.M. Van Geem and William H. Green, Combustion & Flame (2013)
Octane number = 86 Octane number = 98 Octane number = 100
More reactive Less reactive
RMG considered about 30,000 possible species, selected as important:• 372 chemical species• 8,723 reactions
Sensitive k’s computed with highest-level quantum chemistry we could manage; others from group additivity
n-butanol iso-butanol sec-butanol tert-butanol
Four isomers, very different octane numbers.
23
RMG model quantitatively predicts formation of alkenes and 1-ring aromatics from iso-butanol (some via rather complicated reaction sequences)
1,3-cyclopentadiene
Data from K. Van Geem, Ghentpyrolysis of iso-butanol ~1000 K, 2 atm, 2 seconds. Merchant et al. (2013) 24
• Synchrotron measures dozens of species in n-butanol flame, all predicted accurately
Dozens of additional species traces, variety of flames: all show comparably good agreement.For isobutanol we worked in predictive mode, with similar level of agreement with expt.
Species profiles in butanol flame confirm
predictive capabilities for small molecules, high T
25
Data from Veloo & Egolfopoulos (343 K) , and W. Liu et al. (353 K), both in Proc Combust Inst (2011).
ModelPrediction
Can also predict chemistry + flow quantities, such as zero-strain flame speeds
26
Data measured by Stranic et al., Combust. Flame, 2012, 159 (2), 516-527.
Model quantitatively predicts high-T ignition delays for all butanol isomers & conditions
27
And it is not just small molecules like the butanols. For example, the computer (RMG or Genesys) can build models for JP-10 (exo-tricyclodecane, C10H16) pyrolysis and combustion.
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CH3+ +++
+R8R6R5R4
2CC4EBO
Aromatization
Radical chainreactions
JP-10
Radical chain initiation
Predicted major pathways for steam-cracking of exo-tricyclodecane (C10H16, “JP-10”)
H
H
H
H
H
H
HH
H
H
H
H
TCDR5
exo-TCD
TCDR4BR1
C•
H
H
H
H
MA110
R
RH
TCDR8 TCDR6
H
RRH RRH
26%14% 9%33%8%
R RH
R RH R RH
R RH
H2
R RH
H2
RRH
H
H
tricyclo[5.2.1.02,6]-
dec-4-ene
2-norbornene
1,4-pentadiene
1-ethenyl-cyclopentene
3-ethenyl-cyclopentene
CH•
H
R RH
R RH
H2
R
-H-fulvenyl
H
R RH
R
RH
R RH
H2
RH
R
RH
R
RH
R
RH
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Steam-cracking of exo-tricyclodecane experiment vs. model predictions
C2H4
CH4
H2
C3H6
cycloC5H6
cycloC5H8
Similar level of agreement for many other species See Vandewiele et al. Energy & Fuels (2015).
For model & expts with JP-10 + O2, see Gao et al. Combust. Flame (2015)
T~1000 K, P~2 bar
30
At this point we are feeling very good:
Computer-constructed model based on quantum chemistry can predict many observables quantitatively for several high T C,H,O gas phase systems!
31
Expts:τ ~ [O2]-1.5
We don’t know everything: model less accurate below ~900 K, and completely misses [O2] sensitivity of low-T ignition delay of iso-butanol!
In AirModel predicts[fuel] dependencereasonably well
Model:No [O2]dependence
Const. [Fuel]
Data measured by B. Weber and C.J. Sung32
33
Possible causes of this Discrepancy• Low T: Energy errors more important • Internal Rotors: Intramolecular H-bonding causes large coupling between rotors– See e.g. Sharma et al. J.Phys.Chem. A (2010)– As Don Truhlar showed, conformations can be non-intuitive
• Omissions or inaccuracies in the reaction mechanism– Computer-built models are not infinite, can omit reactions– Reminder: Computed rates are not perfect!– See talk by Samah Mohamed later this morning
• New peroxy reaction types (not known when reaction mechanism was generated)
Missing some peroxy chemistry?
• Still discovering new peroxy reactions, e.g.– Welz et al., J. Phys. Chem. Lett. (2013)– Jalan et al., J. Am. Chem. Soc. (2013)– Judit Zador’s talk on Monday
• How can we discover new (unexpected) reactions? • Can we make a computer do it automatically?
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35
Are we missing other important reactions? RMG can list allthe low-energy species with same number of atoms as reactant. Many potential products unreachable by any known reaction.
We Automated Search for New Reactions(Freezing String, followed by Berny TS search)
Program automaticallyfound new saddle pointsconnecting reactantto 7 of the 155 possiblelow-energy products
7 completely new reactions!
We don’t know how manythe computer missed……a lot of work still to be done on automatic discoveryof new chemistry!
36
37
Suppose our model already includes all the important reactions, just has the wrong rate coefficients for some of them. Which of the 8,723 rate coefficients in the model should we carefully check? Which are really important??
Let’s be Optimistic:
Suppose our model already includes all the important reactions, just have the wrong rate coefficients for some of them. Which of the 8,723 rate coefficients in the model should we carefully check? Which are really important??
A quick primer on what is Important in Low-T ignition chemistry
38
Typical Ignition Delay Curves show 3 parts:High T (>900 K) and Low T (<700 K) are near-Arrhenius, plus something in between
10 bar, f=1 in air, adiabatic
Ign
itio
n D
elay
(lo
g p
lot)
1000/T39
Multiple Stages of Ignition, each with different dominant chemistry.
Hot “Second-Stage” ignition “1st-stage Ignition”
Propane
Methanol
ExponentialGrowth inConcentrations
40
The Low-T “QOOH” Amplifier:1 OH in, 3abg OH out
• Reactive Intermediate Concentrations rapidly rise ~5 orders of magnitude: chemical amplifier
• If abg=1, l ~ sqrt(2kdecompkROO=QOOH)
g
S.S. Merchant et al., Combust. Flame (accepted)
41
Methanol’s Amplifier: H2O2 (1 HO2 in, 3 HO2 out)
O2+CH3OH
HO2
CH2OH
CH2O
O2
HOOH
Fuel
OH
Fuel
42
This is why HO2 + fuelis important: it is oftena key chain-branchingpathway
Exponential-Growth Stage (“1A”)Linear kinetics, an eigenvalue > 0
Stage ends when HO2 + HO2 becomes significant
Stage 1A
Stage 1A
Propane:• OH amplified by QOOH cycle
Methanol:• HO2 amplified by H2O2 cycle
43
QOOH cycle continues to amplify despite HO2+HO2 during Stage 1B
Stage 1A
Stage 1A
Propane during stage 1B:• HO2 in QSS due to self reaction• OH gain from QOOH cycle
Stage 1B
Stage 1B ends when QOOH cycle gain drops to 1 (mostly due to T increase)
44
Can write down analytical formulas for Stage 1 ignition delays
• Dotted lines are from the analytical formulas.
• Depends on 10 rate coefficients (a lot less than the 8,723 in the butanols model!)
Propane:• QOOH chemistry continues, but OH gain < 1; coupled with H2O2 cycle
Stage 1BStage 2
Stage 2
Methanol:• HO2 amplified by H2O2 cycle• Product (H2CO) more reactive
46
Methanol, Stage 2HO2+HO2 short-circuits chain-
branching
HO2
CH2OH
CH2O
O2
HOOH
Fuel
OH
Fuel
HO2HCO
HOOH
CO
O2
47
Typical 2nd Stage Chemical Amplifierfor hydrocarbons
alkene
HO2
HOOH
R
OH
Fuel
Fuel
O2Ox
O2
Coupled loops.Different fuelsgive different yields of HO2 and OH from R+O2
Complicated,but not impossible. 48
Summary• We know a lot of combustion chemistry
– Can quantitatively predict many experiments– But we need very large models to do it!
• Still some important things we don’t know– Soot formation/oxidation– Flame extinction chemistry– Some aspects of low-T ignition
• We have important tools in hand, though all need improvement....– Quantum Chemistry for thermo & rates– Automated /Systematic Mechanism Generation– Ways to analyze complex models, focus on key issues– Automated search for new chemical reactions