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
1
Combustion is Critically Important
• Provides about 80% of our energy
With current technology,
Developed countries burn
100 GJ/y per person.
1010 people * 1011 J/y
= a lot of combustion!
Energy/person (GJ/y)
– Transportation, heating, electricity production…
– …Will still be main energy source in 2040.
– Crucial to Economy! GDP scales with energy use.
GDP/person ($)
2
Combustion is Biggest Source of
Greenhouse Gases
We need to keep [CO2] < 550 ppm to have reasonable chance of
avoiding catastrophic climate change.
Need to drastically reduce slope of this graph very soon!
3
Epidemiology is clear: Soot Kills
Mortality Rate
6-Cities Study, USA
Dockery et al.
N Engl J Med 1993
5 years less
Life expectancy
North of river
Particulate Level in Air
Strong correlation between
Deaths and Particulates, seen
repeatedly in many different
locations & situations.
Yuyu Chen et al. PNAS 2013;110:12936-12941
Huai River policy: coal burners north of
river, no heat south of river. Life span
much shorter on north side of river.
Health impacts significantly slow
economic growth.
4
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
5
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
6
C5H5+C5H5  naphthalene (C10H8) …how?
Many models say C5H5+C5H5  C10H8 + H + H
But this is too slow
Instead:
C5H5 + C5H5 = C10H10
C10H10 + R  C10H9 +RH
C10H9  C10H8 + H
7
See poster by Marko Djokic for relevant expts
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
8
For the rest of this talk, I’ll focus on
Methodology for Predicting (nonsooting, unstrained) Combustion
Chemistry of new fuels
and on
Low-T Ignition
9
Combustion Chemistry Mechanisms are Huge
4500
PRF
(Curran et al.)
4000
800
3000
n-heptane
(Curran et al.)
2500
600
2000
400
hydrogen
1500
1000
methane
(GRIMech3.0)
propane
(Marinov)
200
n-butane
(ENSIC Nancy)
500
0
0
0
1
2
3
4
5
6
7
8
9
Carbon Number
Never enough experimental data to determine all
the k(T,P): must work in predictive mode, based
primarily on quantum chemistry.
10
Number of Species
iso-octane
(Curran et al.)
3500
Number of Reactions
Use
computer
to build the
model!
1000
Commercial software can solve
large kinetic simulations…
…if one can supply the
reaction mechanism.
Simulation
predictions
Diff. Eq. solver
Very long
list of
reactions
with rate
parameters
Interpreter
(CHEMKIN,
Cantera, KIVA,
GTPower)
Simulation
equations
dY/dt = …
11
How we construct chemistry models
Sensitivity
Analysis
Chemistry
knowledge
Unambiguous
documentation
of assumptions
about how
molecules react
Simulation
predictions
High-accuracy
quantum
calculations on
sensitive
parameters
Diff. Eq. solver
Very long
list of
reactions
with rate
parameters
Interpreter
(CHEMKIN,
Cantera, KIVA,
GTPower)
Simulation
equations
dY/dt = …
12
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
13
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
14
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)
15
RMG algorithm: Faster pathways explored
further, growing the model
Before:
“Current Model” inside.
RMG decides whether
or not to add species to
this model.
Final model typically
~500 species, 8000 rxns
After:
Open-Source RMG software.
Download from
rmg.sourceforge.net
16
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
17
Quantum Enthalpy Predictions Improve a Lot with
Empirical Bond-Additivity Corrections (BAC)
Hcorrected =
DFT (B3LYP)
CBSQB3
CCSD(T)-F12
/TZ
CCSD(T)-F12
/QZ
Error (Expt(ATcT) – Quantum) 2 kcal/tick mark
Hquantum
+
correction
for each
C-C bond,
each C-O
bond, etc.
18
BAC (mostly) fix enthalpies, but leave
discrepancies in computed barrier heights
Compute
slightly
different
Barrier
depending
on which
direction
you compute
the reaction.
Significant at
Room 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 energies
a few cal/mole-K in entropies and heat capacities
perhaps a factor of 2 due to internal rotor approximations
about 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
Testing Accuracy of Model Predictions vs.
Experiment: Extensive Data available on
Pyrolysis, Combustion, Oxidation of Butanols
flow reactors
RCM
With collaborations from
other institutes
e.g. Univ. Ghent, NIST.
Pyrolysis
(shock tube)
Flame
Speeds
MBMS
Shock
tube
Flame
Speed
Rare Situationswhere detailed data
available at many different conditions!
22
We used RMG to build a mechanism for
butanol pyrolysis and combustion.
Four isomers, very different octane numbers.
n-butanol
iso-butanol
Octane number = 86
Octane number = 98
More reactive
sec-butanol
tert-butanol
Octane number = 100
Less reactive
RMG considered about 30,000 possible species, selected
as important:
• 372 chemical species
• 8,723 reactions
Shamel S. Merchant, E.F. Zanoelo, R.L. Speth,
M.R. Harper, K.M. Van Geem and William H. Green,
Combustion & Flame (2013)
Sensitive k’s computed with
highest-level quantum chemistry we
could manage; others from group additivity
23
RMG model quantitatively predicts formation of
alkenes and 1-ring aromatics from iso-butanol
(some via rather complicated reaction sequences)
Data from K. Van Geem, Ghent
pyrolysis of iso-butanol ~1000 K, 2 atm, 2 seconds. Merchant et al. (2013)
24
Species profiles in
butanol flame confirm
predictive capabilities for
small molecules, high T
• 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.
25
Can also predict chemistry + flow quantities,
such as zero-strain flame speeds
Data from
Veloo & Egolfopoulos (343 K) ,
and W. Liu et al. (353 K),
both in Proc Combust Inst (2011).
Model
Prediction
26
Model quantitatively predicts high-T ignition
delays for all butanol isomers & conditions
Data measured by Stranic et al., Combust. Flame, 2012, 159 (2), 516-527.
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.
Radical chain initiation
4EBO
Radical chain
JP-10
2CC
28
+
Predicted major pathways for steam-cracking of
exo-tricyclodecane (C10H16, “JP-10”)
29
Steam-cracking of exo-tricyclodecane
experiment vs. model predictions
T~1000 K, P~2 bar
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)
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
We don’t know everything: model less accurate
below ~900 K, and completely misses [O2]
sensitivity of low-T ignition delay of iso-butanol!
Const. [Fuel]
In Air
Model predicts
[fuel] dependence
reasonably well
Model:
No [O2]
dependence
Expts:
τ ~ [O2]-1.5
Data measured by B. Weber and C.J. Sung
32
Possible causes of this Discrepancy
• Low T: Energy errors more important
−𝐸𝑎
−𝐸𝑡𝑟𝑢𝑒 ±𝛿𝐸
−𝐸𝑡𝑟𝑢𝑒
∓𝛿𝐸
𝑅𝑇
𝑒
=𝑒
=𝑒
𝑒
• Internal Rotors: Intramolecular H-bonding causes large
coupling between rotors
𝑅𝑇
𝑅𝑇
𝑅𝑇
– 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)
33
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?
34
Are we missing other important reactions? RMG can list all
the low-energy species with same number of atoms as reactant.
Many potential products unreachable by any known reaction.
Example:
Reactant
Computer
Says:
155
Possible
Low-energy
Product
Channels 35
We Automated Search for New Reactions
(Freezing String, followed by Berny TS search)
Program automatically
found new saddle points
connecting reactant
to 7 of the 155 possible
low-energy products
7 completely new reactions!
We don’t know how many
the computer missed…
…a lot of work still to be
done on automatic discovery
of new chemistry!
36
Let’s be Optimistic:
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??
37
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
Ignition Delay (log plot)
Typical Ignition Delay Curves show 3 parts:
High T (>900 K) and Low T (<700 K) are nearArrhenius, plus something in between
10 bar, f=1 in air, adiabatic
39
1000/T
Multiple Stages of Ignition, each with
different dominant chemistry.
“1st-stage
Ignition”
Hot “Second-Stage” ignition
Propane
Methanol
Exponential
Growth in
Concentrations
40
The Low-T “QOOH” Amplifier:
1 OH in, 3abg OH out
g
S.S. Merchant et al.,
Combust. Flame (accepted)
• Reactive Intermediate Concentrations rapidly rise ~5
orders of magnitude: chemical amplifier
• If abg=1, l ~ sqrt(2kdecompkROO=QOOH)
41
Methanol’s Amplifier: H2O2
(1 HO2 in, 3 HO2 out)
This is why HO2 + fuel
is important: it is often
a key chain-branching
pathway
42
Exponential-Growth Stage (“1A”)
Linear kinetics, an eigenvalue > 0
Stage ends when HO2 + HO2 becomes significant
Propane:
• OH amplified by QOOH cycle
Methanol:
• HO2 amplified by H2O2 cycle
Stage 1A
Stage 1A
43
QOOH cycle continues to amplify
despite HO2+HO2 during Stage 1B
Propane during stage 1B:
• HO2 in QSS due to self reaction
• OH gain from QOOH cycle
Stage 1B ends when QOOH cycle gain
drops to 1 (mostly due to T increase)
Stage 1B
Stage 1A
Stage 1A
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!)
• Merchant et al.,
Combust. Flame
(accepted)
45
Stage 2: HO2+Fuel H2O2 causes chain
branching, tempered by HO2 + HO2
Propane:
• QOOH chemistry continues, but OH
gain < 1; coupled with H2O2 cycle
Methanol:
• HO2 amplified by H2O2 cycle
• Product (H2CO) more reactive
Stage 2
Stage 1B
Stage 1A
Stage 2
Stage 1A
46
Methanol, Stage 2
HO2+HO2 short-circuits
chain-branching
47
Typical 2nd Stage
Chemical Amplifier
for hydrocarbons
Coupled loops.
Different fuels
give 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
49