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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 

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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)

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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!

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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.

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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

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 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

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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

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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

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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)

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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.

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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

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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

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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

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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

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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!

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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

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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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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.

Example:Reactant

Computer Says:155 PossibleLow-energyProductChannels

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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!

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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

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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

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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)

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Methanol’s Amplifier: H2O2 (1 HO2 in, 3 HO2 out)

O2+CH3OH

HO2

CH2OH

CH2O

O2

HOOH

Fuel

OH

Fuel

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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

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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)

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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)

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Stage 2: HO2+Fuel H2O2 causes chain branching, tempered by HO2 + HO2

Stage 1A

Stage 1A

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

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Methanol, Stage 2HO2+HO2 short-circuits chain-

branching

HO2

CH2OH

CH2O

O2

HOOH

Fuel

OH

Fuel

HO2HCO

HOOH

CO

O2

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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

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