Automatic Generation of Detailed Kinetic Modelsfor Complex Chemical Systems

A Dissertation Presented

By

Fariba Seyedzadeh Khanshan

to

The Department of Chemical Engineering

In partial fulfillment of the requirementsFor the degree of

Doctor of Philosophy

In the field of

Chemical Engineering

Northeastern UniversityBoston, Massachusetts

January 29 2016

Acknowledgements

I would like to thank to my PhD advisor, Professor Richard H. West, for supporting me

during this journey. He’s the nicest advisor and one of the smartest people I know. He has

been supportive and I’m very grateful for his advice, guidance, patience, and friendship

over the past four years. He has provided insightful discussions about my research and I

am thankful for having his scientific suggestions.

My sincere thanks and appreciation also go to my PhD committee members, Profes-

sor Sunho Choi from the Department of Chemical Engineering, and Professors Hamed

Metghalchi and Yiannis Levendis from the Department of Mechanical and Industrial En-

gineering for their helpful inputs and insightful comments.

I would also like to thank Dr. Robert Low, Dr. Clive Giddis, and Dr. Andrew Sharratt,

from Mexichem Fluor Ltd, for providing scientific suggestions and discussions during my

chlorination modeling research.

I would like to show my appreciation to all the present members of the CoMoChEng

group. I am grateful to Pierre Bhoorasingh and Belinda Slakman who have been my good

friends during these four years. I know I will miss your company.

I would like to acknowledge all of the RMG developers and Green group members at MIT.

I’m glad I had this opportunity to work with them. Their comments and discussions al-

ways have been a great help to me in RMG development.

I am deeply thankful to my parents, brother, and sister for their unconditional love, care,

and encouragement. I love them so much, and I would not have made it this far without

them. My father, to whom this dissertation is dedicated to, has been my best friend all

my life and I love him dearly and thank him for all his advice and support.

I would also like to thank the Department of Chemical Engineering of Northeastern Uni-

versity for funding and supporting my research.

i

I dedicate this thesis to the memory of my beloved father

Yaghoub Seyedzadeh Khanshan

I miss you every day and thank you for everything

I love you dearly forever

ii

Abstract

Detailed chemical kinetic mechanisms represent molecular interactions that occur when

chemical bonds are broken and reformed into new chemical compounds. Many natural

and industrial processes such as combustion of hydrocarbons, biomass conversion into re-

newable fuels, and synthesis of halogenated-hydrocarbon through halogenation reactions,

include reaction network with hundred of species and thousands of reactions. Recently,

the potential of such processes is leading to rapid industrial expansion and facing some

technical drawbacks. Among various tools, detailed kinetic modeling is a reliable way

to improve the scientific understanding of such systems and therefore optimize process

conditions for desired production plans. Detailed chemical kinetic modeling is sensitive

to the system chemistry, and sometimes too complex to model by hand. For example,

utilizing predictive theoretical models by hand for biomass thermal conversion, which in-

clude a wide variety of heavy cyclic oxygenated molecules, alcohols, aldehydes, ketones,

ethers, esters, etc., is tedious.

It is preferable to teach our chemistry knowledge to computers, and generate detailed

chemical models automatically. To generate comprehensive detailed models, an extensive

set of reaction classes, which would define how species can react with each other, should

be implemented in mechanism generators. In this thesis, Reaction Mechanism Genera-

tor (RMG), an open-source software, has been used to build detailed kinetic models for

complex chemical systems.

This thesis presents several significant contributions in the area of predictive automatic

kinetic mechanism generation for biofuels thermal conversion and reactions of many chlo-

rinated hydrocarbons. The first section of this thesis describes significant contributions

in detailed kinetic modeling of bio-oil gasification for syngas production using RMG. The

major challenge in modeling bio-oil gasification is the presence of a wide range of cyclic

iii

oxygenated species and several progress has been made in RMG to improve the automated

chemical modeling of this process. RMG-built models were evaluated by comparison to

available published data and to improve the understanding of such detailed models, dif-

ferent types of analysis such as sensitivity analysis were performed.

The second section of this thesis presents a theoretical study of the gas-phase unimolec-

ular thermal decomposition of heterocyclic compounds via single step exo and endo ring

opening reaction classes. Quantum chemical calculations were performed for a smaller

set of reactants belonging to the endo and exo reaction classes and data were used to

inspect the ’rate calculation rules’ method. To study the e↵ect of the direct ring open-

ing reactions in the automated detailed kinetic model generation, the bio-oil gasification

mechanism, from Chapter 1, was updated after updating RMGs kinetic database with

these new single step ring opening reaction classes and associated rate rules.

The third section of this thesis provides significant contributions toward facilitating the

automatic generation of predictive detailed kinetic models for 1,1,2,3- tetrachloropropene

(1230xa) production and other hydrocarbon chlorination processes. In order to enable

RMG to model chlorinated hydrocarbon conversions, the chlorine (Cl) chemistry has been

added into the the Python version of the software. A model has been generated in RMG

for 1230xa production with known associated thermodynamic and kinetic parameters. For

model evaluation, reaction flux analysis and sensitivity analysis were performed to reveal

the important reaction channels in the RMG-built model and several improvements to

thermodynamic estimates were discussed.

The ability to automatically generate these models for such complex chemical systems

demonstrates the predictive capability of detailed chemical modeling. The impact of

such models significantly improves the scientific understanding of two industrial chemical

processes, bio-oil gasification and chlorination.

iv

Contents

1 Developing Detailed Kinetic Models of Syngas Production From Bio-OilGasification Using Reaction Mechanism Generator (RMG) 11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Critical Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2.1 Bio-oil gasification experiments . . . . . . . . . . . . . . . . . . . . 31.2.1.1 Low temperature bio-oil gasification . . . . . . . . . . . . 41.2.1.2 High temperature bio-oil gasification . . . . . . . . . . . . 5

1.2.2 Chemical modeling of bio-oil gasification . . . . . . . . . . . . . . . 71.2.2.1 Cellulose kinetic modeling . . . . . . . . . . . . . . . . . . 81.2.2.2 Lignin kinetic modeling . . . . . . . . . . . . . . . . . . . 91.2.2.3 Hemicellulose Kinetic modeling . . . . . . . . . . . . . . . 11

1.3 Computational Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121.3.1 Reaction Mechanism Generator . . . . . . . . . . . . . . . . . . . . 13

1.3.1.1 Molecular Representations . . . . . . . . . . . . . . . . . . 141.3.1.2 Data Hierarchy in RMG . . . . . . . . . . . . . . . . . . . 14

1.3.1.2.1 Thermodynamic Database . . . . . . . . . . . . . 151.3.1.2.2 Thermochemistry Estimation . . . . . . . . . . . 161.3.1.2.3 Kinetic Database . . . . . . . . . . . . . . . . . . 19

1.3.1.3 Rate-Based Model Enlarger . . . . . . . . . . . . . . . . . 221.3.1.4 Pressure Dependence in RMG . . . . . . . . . . . . . . . . 231.3.1.5 Output from RMG . . . . . . . . . . . . . . . . . . . . . . 24

1.3.2 Cantera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251.3.3 Model Verification and Validation . . . . . . . . . . . . . . . . . . . 261.3.4 Bio-oil gasification modeling . . . . . . . . . . . . . . . . . . . . . . 27

1.3.4.1 Bio-oil Composition . . . . . . . . . . . . . . . . . . . . . 271.3.4.2 Simulating syngas production . . . . . . . . . . . . . . . . 29

1.3.5 Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301.4 Results and Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

1.4.1 Influence of model size . . . . . . . . . . . . . . . . . . . . . . . . . 301.4.2 Influence of pressure and pressure-dependent kinetics . . . . . . . . 321.4.3 Comparison with experiments . . . . . . . . . . . . . . . . . . . . . 341.4.4 Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 361.4.5 Poor Thermochemistry For Cyclic Molecules . . . . . . . . . . . . . 38

v

1.4.6 Missing Pathways in RMG Generated Mechanisms . . . . . . . . . 401.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 421.6 Recommendations for future work . . . . . . . . . . . . . . . . . . . . . . . 45

1.6.1 Improve RMG thermochemistry estimation . . . . . . . . . . . . . . 451.6.2 Add more reaction families to the RMG database . . . . . . . . . . 461.6.3 Improve memory management in RMG . . . . . . . . . . . . . . . 46

1.7 Supporting material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

2 Rate calculation Rules for Automated Generation of Detailed KineticModels for Heterocyclic Compounds 472.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472.2 Critical literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

2.2.1 Specific reaction classes for acyclic components of biofuels . . . . . 492.2.1.1 Unimolecular initiations . . . . . . . . . . . . . . . . . . . 502.2.1.2 Bimolecular initiations and H-abstractions . . . . . . . . . 512.2.1.3 Radicals decomposition by �-scission . . . . . . . . . . . . 522.2.1.4 Intramolecular isomerizations . . . . . . . . . . . . . . . . 53

2.2.2 Specific reaction classes for cyclic components of biofuels . . . . . . 542.2.2.1 Unimolecular initiations . . . . . . . . . . . . . . . . . . . 552.2.2.2 Endocyclic and exocyclic ring-opening in cyclic radicals . . 56

2.2.3 Reaction rate calculation for biofuel compounds . . . . . . . . . . . 572.2.3.1 Quantum chemistry . . . . . . . . . . . . . . . . . . . . . 572.2.3.2 Statistical mechanics . . . . . . . . . . . . . . . . . . . . . 582.2.3.3 Transition State Theory . . . . . . . . . . . . . . . . . . . 59

2.2.4 Reaction rate estimation methods . . . . . . . . . . . . . . . . . . . 612.2.4.1 Linear Free Energy Relationship (LFER) . . . . . . . . . . 612.2.4.2 Evans-Polanyi correlation . . . . . . . . . . . . . . . . . . 622.2.4.3 Reaction Class Transition State Theory (RC-TST) . . . . 622.2.4.4 Rate calculation rules . . . . . . . . . . . . . . . . . . . . 63

2.3 Computational Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 642.4 Results and Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

2.4.1 Case study: E↵ect of new reaction families on Bio-oil gasification . 782.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 802.6 Supporting material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 812.7 Recommendations for future work . . . . . . . . . . . . . . . . . . . . . . . 82

2.7.1 Expand the e↵ect of the functional groups . . . . . . . . . . . . . . 822.7.2 Add more reaction families with associated data to the RMG database 82

3 Automatic Reaction Mechanism Generation for Producing 1,1,2,3-tetrachloropropane 843.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 843.2 Critical Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

3.2.1 Proposed pathways from published patents . . . . . . . . . . . . . . 863.2.2 Thermodynamics of chlorinated hydrocarbons . . . . . . . . . . . . 91

vi

3.2.3 Kinetics of chlorinated hydrocarbons . . . . . . . . . . . . . . . . . 933.2.3.1 Initiation steps . . . . . . . . . . . . . . . . . . . . . . . . 943.2.3.2 Propagation steps . . . . . . . . . . . . . . . . . . . . . . 943.2.3.3 Termination steps . . . . . . . . . . . . . . . . . . . . . . 99

3.3 Computational Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 993.3.1 Chlorine (Cl) atom type in RMG . . . . . . . . . . . . . . . . . . . 1013.3.2 Thermodynamics of chlorinated hydrocarbons in RMG . . . . . . . 101

3.3.2.1 Species thermochemistry libraries . . . . . . . . . . . . . . 1013.3.2.2 Group-based methods . . . . . . . . . . . . . . . . . . . . 1023.3.2.3 Quantum chemistry calculation . . . . . . . . . . . . . . . 104

3.3.3 Chlorination reaction families in RMG . . . . . . . . . . . . . . . . 1053.3.4 Kinetics estimation for chlorinated hydrocarbons in RMG . . . . . 106

3.3.4.1 Training Set . . . . . . . . . . . . . . . . . . . . . . . . . . 1063.3.4.2 Quantum chemistry . . . . . . . . . . . . . . . . . . . . . 1083.3.4.3 Rate rules . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

3.3.5 Model evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1093.4 Results and Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

3.4.1 Thermodynamics evaluation . . . . . . . . . . . . . . . . . . . . . . 1113.4.2 Reaction flux analysis . . . . . . . . . . . . . . . . . . . . . . . . . 1143.4.3 Sensitivity analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1183.6 Supporting material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1193.7 Recommendations for future work . . . . . . . . . . . . . . . . . . . . . . . 120

3.7.1 Improve accuracy of kinetics estimates . . . . . . . . . . . . . . . . 1203.7.2 Liquid-phase chlorination modeling . . . . . . . . . . . . . . . . . . 1203.7.3 Investigating the concerted E2 elimination reaction vs. Sn2 substi-

tution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1213.7.4 Expand 1230xa modeling to fluorination reactions . . . . . . . . . . 122

4 References 123

Appendices 134

A The largest mechanism for bio-oil gasification generated in RMG-Java 135

B Transition State Geometries of Heterocyclic Compounds Reactions 136

C RMG-Py generated mechanism for 1230xa 149

vii

List of Figures

1.1 Syngas production from bio-oil gasification at di↵erent temperatures, reproducedfrom Zhang et al. [1]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.2 E↵ect of temperature on composition of gas products in bio-oil gasification ex-periment, reproduced from Chhiti [2]. . . . . . . . . . . . . . . . . . . . . . . 6

1.3 Three proposed main pathways for LG thermal decomposition, reproduced fromZhang et al. [3]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.4 Model for the lignin � -O-4 linkage [4] . . . . . . . . . . . . . . . . . . . . . . 91.5 Proposed reaction pathways for initial decomposition of PPE from di↵erent stud-

ies [4–7] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.6 Proposed thermal decomposition pathways for xylopyranose [8]. . . . . . . . . . 121.7 Molecules are represented as 2-dimensional graphs in RMG . . . . . . . . . . . 141.8 Groups tree structure for H-abstraction family, reproduced from RMG docu-

mentation [10]. Indented text and schematics show the used syntax in RMG torepresent the parent and children nodes. . . . . . . . . . . . . . . . . . . . . . 15

1.9 Group additivity approach to estimate isobutylbenzene standard enthalpy offormation and comparison with the NIST reported value. . . . . . . . . . . . . 17

1.10 On-the-fly Quantum-chemical (QMTP) calculation steps (reproduced from RMGdocumentation [10]) toward thermochemical properties calculations in RMG. . . 18

1.11 General template and reaction recipe for H-abstraction reaction family in RMG. 201.12 Reactants kinetic trees (reproduced from RMG documentation [10]) for H-

abstraction reaction and reaction matched template. . . . . . . . . . . . . . . . 211.13 Falling up to the more general parent nodes from the exact match nodes to find

data, reproduced from RMG documentation [10]. . . . . . . . . . . . . . . . . 211.14 RMG explores paths with high reaction rates and will move them into the model

’core’. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231.15 The Chemkin file showing the list of species, thermochemistry, and reaction

information as RMG’s output. . . . . . . . . . . . . . . . . . . . . . . . . . . 251.16 Steps toward building reliable detailed kinetic models using RMG. . . . . . . . 271.17 Work-flow of the reaction mechanism modeling for bio-oil gasification using RMG

and Cantera. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291.18 Syngas production varying with incomplete model size from a CSTR with

residence time 5 sec. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

viii

1.19 Mole fraction of four major gases at exit of a CSTR with residence time 5 secondsat a range of temperatures and pressures, according to kinetic models built byRMG- Java. (a) without pressure-dependence calculations (b) with pressure-dependent reaction networks calculated by modified strong collision approximation. 33

1.20 Distribution between four major gas components as a function of temperature,(a) from experimental work by Zhang et al.[1] at 100 C intervals from 600 to1000 C, (b) from Chhili et al.[2] at 100 C intervals from 1000 to 1400 C, (c) fromCantera simulations (this work) at 100 C intervals from 600 to 1400 C . . . . . 34

1.21 Distribution between four major gas components as a function of temperaturefrom high acid model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

1.22 Sensitivity analysis for (a) CO2 at T=700C, (b) CO2 at T=1400C,, (c) CO atT=700C,, (d) CO at T=140C,. See text for model details. . . . . . . . . . . . 37

2.1 Calculated bond dissociation energies (in kcal/mol) in ester, ether, and alcoholmolecules by Tran et al. [9]. . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

2.2 Rate of the initiation and radical recombination reaction of butanol in RMG [10]. 512.3 General reaction template of H-abstraction reaction family. . . . . . . . . . . . 512.4 The general template of the �-scission reaction and formation of free radical

upon this reaction class. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 532.5 The general template of intramolecular H and OH migration reaction families

and formation of free radical upon these reaction classes. . . . . . . . . . . . . 542.6 Proposed detailed mechanism of (a) ethylene,(b) 1-pentene, and (c) 1-hexene

formation by Sirlean et al. [11] from the primary decomposition of the cyclobu-tane, cyclopentane, and cyclohexane and by considering di↵erent conformers ofC4, C5, and C6 biradicals, respectively. . . . . . . . . . . . . . . . . . . . . . 55

2.7 Exo and endo ring-opening reactions for Cyclobutylcarbinyl radical and Cy-clobutyl radical. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

2.8 The general template of the exocyclic tautomerization ring-opening reaction fam-ily. The example is shown for the primary ring-opening reaction of xylose, a typeof sugar from wood. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

2.9 The general template of the endocyclic tautomerization ring-opening reactionfamily. The example is shown for the endocyclic ring-opening reaction of lev-oglucosan, a derivative of cellulose pyrolysis. . . . . . . . . . . . . . . . . . . . 65

2.10 Hierarchical tree for (a) exocyclic and (b) endocyclic ring-opening reaction families. 662.11 High pressure limit rate coe�cients within the temperature range of 300-2000 K

for exocyclic ring opening test set reactions to investigate the rate calculationrules. (a) results for the five, six, and seven membered carbon rings (b) resultsfor the five, six, and seven membered oxygen rings. . . . . . . . . . . . . . . . 69

2.13 Rate coe�cient of the four, six, and seven membered rings across the C, N, and O

heteroatoms in exocyclic test set reaction at T= 1100 K. . . . . . . . . . . . . . . . 712.14 Potential energy diagram for bicyclo-octane isomerization to 3-ethylcyclohexene

calculated at the CBS-QB3 level through single step-endo ring-opening vs. two-steps pathway with a diradical intermediate. . . . . . . . . . . . . . . . . . . . 73

ix

2.15 High pressure limit rate coe�cients within the temperature range of 300-2000 Kfor endocyclic ring opening test set reactions to investigate the rate calculationrules. (a) results for the five, six, and seven membered carbon rings (b) resultsfor the five, six, and seven membered oxygen rings. . . . . . . . . . . . . . . . 75

2.18 Rate coe�cient of the four, six, and seven membered rings across the C, N, andO heteroatoms in endocyclic test set reaction at T= 1100 K. . . . . . . . . . . 77

2.19 Distribution between four major gas components as a function of temperature,(a) from experimental work by Zhang et al.[1] at 100�C intervals from 600 to1000 �C, (b) from Chhili et al.[2] at 100�C intervals from 1000 to 1400 �C ,(c) RMG-built model at 100�C intervals from 600 to 1400 �C before updatingRMG’s kinetic database (d) after updating RMG’s kinetic database with newreaction families. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

2.20 The general template of ene reaction with an example. . . . . . . . . . . . . . . . . 83

3.1 Reaction and products from 1,2,3-trichloropropane liquid phase chlorination inthe presence of azobisisobutyronitrile catalyst proposed by Smith [12]. . . . . . 87

3.2 1230xa formation reaction channels via 1,1,1,2,3- and 1,1,2,2,3-pentachloropropanes dehydrochlorination and 2,3,3,3-tetrachloropropaneisomerization to 1230xa proposed by Smith [12]. . . . . . . . . . . . . . . . . . 88

3.3 1230xa formation reaction channels by reacting ethylene with carbon tetrachlo-ride from the work of Woodard [13, 14]. . . . . . . . . . . . . . . . . . . . . . 89

3.4 1230xa formation reaction channels from 1,2,3 trichloropropane proposed byMukhopadhyay et al. [15] and Wilson et al. [16]. . . . . . . . . . . . . . . . . 90

3.5 Non-catalytic gas phase reaction channels proposed by Nose et al. [17] for 1230xaformation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

3.6 The correction in the enthalpies of formation for accounting the e↵ect of interac-tion as function of number of chlorine atoms for multichloro alkanes and alkenes,reproduced from [18]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

3.7 Initiation, propagation and termination free radical reaction steps in methylchloride production via methane chlorination. . . . . . . . . . . . . . . . . . . 94

3.8 The general template of the H-abstraction reaction via chlorine atom. . . . . . . 953.9 Evans-Polanyi plot for H-abstractions from C1 and C2 chlorinated hydrocarbons

by Senkan et al. [19]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 963.10 Comparison of SAR predictions with experimental data fro H-abstraction of chlorinated

hydrocarbons by chlorine radical by Senkan et al. [19]. . . . . . . . . . . . . . . . . 973.11 The general template of the Cl-abstraction reaction family. . . . . . . . . . . . 973.12 Obtained correlation by Bryukov et al. [20] between activation energies and enthalpies

of reactions for (Cl,H)-abstraction from chlorinated methanes by H atom attacks. . . . 983.13 Predicted Evans-Polanyi plot by Louis et al. [21] for (H,Cl,F)-abstraction reac-

tions via H radical attacks for chlorinated methanes. . . . . . . . . . . . . . . 993.14 Radical recombination reaction family general reaction template . . . . . . . . 993.15 Main proposed reaction channels to produce 1,1,2,3-tetrachloropropene (1230xa)

[12, 14–17] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

x

3.16 RMG’s thermochemistry database was updated with new chlorinated functionalgroups. As an example, comparison between the chloroethene thermochemistryestimation via GA approach and NIST reported value shows a good agreement. 103

3.17 Hydrogen Bond Increment (HBI) calculations for chlorinated species. . . . . . . 1043.18 More HBI calculation to consider the e↵ect of the chlorine atom on its adjacent

C-H bond. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1043.19 The general template of the (a) H-abstraction reaction, (b) radical recombination

reaction family. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1053.20 The general template of the (a) Cl-abstraction reaction, (b) Cl2/HCl addition

into the double bond reaction family. . . . . . . . . . . . . . . . . . . . . . . 1063.21 Batch reactor simulation of 1230xa (product) and 240db (feedstock) concentra-

tion profiles from RMG-built model. . . . . . . . . . . . . . . . . . . . . . . . 1103.22 Batch reactor simulation of 1230xa (product) and 240db (feedstock) concentration pro-

files from RMG-built model after including HBI corrections for thermochemistry esti-

mation of chlorinated radical species. . . . . . . . . . . . . . . . . . . . . . . . . 1143.23 Reaction flux analysis result to reveal the important reaction channels in the

RMG-built model for 1230xa production. . . . . . . . . . . . . . . . . . . . . 1153.24 The published patent confirms the reaction flux analysis fom RMG-built model

for 1230xa production. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1163.25 Sensitive reaction channels for 1230xa production in RMG-built model at (a)

T=550 C and (b) T=350 C. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1173.26 Reaction phath for concerted E2 elimination vs. Sn2 substitution. . . . . . . . . . . 1213.27 One step closer to understanding the production of fluorocarbons refrigerants from chlo-

rinated feedstocks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122

xi

List of Tables

I Elemental composition and physicochemical properties of Chhiti’s bio-oil (wt.%)[2]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

II Supported quantum chemistry packages and levels of theory in the QMTP, re-produced from RMG documentation [10]. . . . . . . . . . . . . . . . . . . . . 18

III Composition of surrogate bio-oil used in modeling. . . . . . . . . . . . . . . 28IV Elemental composition of bio-oil from experiment II (ref [2]) and RMG model . 29V RMG-built model sizes in core and edge . . . . . . . . . . . . . . . . . . . . . 31VI Comparison of RMG estimated thermochemistry from both Group Additivity

(GA) approach and Quantum Mechanics (QM) calculations of some species toRanzi’s biomass model [22] and other published literature where available. . . . 39

VII Some missed reactions in RMG for bio-oil primary thermal decomposition. . . . 41

I Example of �-scission reaction’s barrier heights for oxygenated compounds. . . . 53II Arrhenius rate constant parameters for exocyclic ring-opening reactions from

CBS-QB3 calculations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68III Arrhenius rate constant parameters for endocyclic ring-opening reactions from

CBS-QB3 calculations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

I The results obtained from the reactor outlet for 1230xa production in non cat-alytic gas-phase reaction according to the Nose et al. [17] method. . . . . . . . 91

II Used activation energy (cal/mol) and pre-exponential factor (l/mol.sec) as atraining set reactions in RMG from the work of Goldfinger et al. [23] for theH-abstraction reaction by chlorine atom for chlorinated C1 and C2 hydrocarbons.107

III 240db conversion (%) for 1230xa production from Nose et al. [17] patent andRMG-built model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

IV RMG estimated thermodynamics for some chlorinated stable species. . . . . . . 111V RMG estimated thermodynamics for some chlorinated radical species. . . . . . 112VI Group Additivity estimates improved when using HBI corrections for chlorinated

radical compounds thermochemistry. . . . . . . . . . . . . . . . . . . . . . . . 113VII 240db conversion (%) for 1230xa production from Nose et al. [17] patent and

RMG-built models before and after adding HBI corrections. . . . . . . . . . . . 114

xii

Chapter 1

Developing Detailed Kinetic Models

of Syngas Production From Bio-Oil

Gasification Using Reaction

Mechanism Generator (RMG)

1.1 Introduction

Bio-oil composition is mostly carbon, oxygen, and hydrogen. Gasification of bio-oil is

a desirable process to produce syngas as a renewable resource with no net greenhouse

gas emissions. Production of syngas from bio-oil is usually a high pressure and high

temperature process. Optimizing the process conditions (temperature, pressure, residence

time, etc.) requires an improved understanding of the chemical kinetics of the thermal

cracking reactions involved in bio- oil gasification. However, thermal conversion of bio-

oil is very sensitive to the fuel chemistry, and sometimes too complex to model by hand,

especially for heavy cyclic oxygenated molecules. It is preferable to teach fuel chemistry to

computers, and generate detailed chemical models automatically. In this study, Reaction

1

Mechanism Generator (RMG), an open-source software, has been used to build detailed

kinetic models for bio-oil gasification.

The influence of the operational conditions and RMG parameters on the model gener-

ation has been investigated. Also, as the size of the model is important, the performance

of RMG-generated models with di↵erent sizes were compared. To provide more realistic

simulations of bio-oil gasification, RMG-built kinetic models have been simulated with

Cantera in zero-dimensional batch reactor assuming constant volume and adiabatic con-

dition, and simulation results are compared with literature. There are some agreements

and disagreements between RMG-built models and literature, showing the importance

of the detailed chemical modeling for such systems, also revealing the importance of the

kinetics and thermodynamics accuracy in detailed chemical model generation. Further,

to generate a comprehensive mechanism, it is important to have all reaction classes for

bio-oil thermal decomposition, and the major challenge is the presence of wide range of

cyclic oxygenated species in the model. In particular, more attention should be paid in

looking at specific reaction classes for decomposition of levogucosan, xylopyronase, and

lignin that are crucial steps during bio-oil gasification. Three reactions classes for bio-oil

gasification that have been missing in RMG’s kinetic database, were investigated.

In this thesis chapter, the challenges involved in using RMG to build a comprehen-

sive model for bio-oil gasification, and how they may be overcome are introduced. Fur-

thermore, several ideas for next work in order to improve RMG for bio-oil gasification

modeling are explained. These ideas include some thoughts on updating RMG’s current

reaction families and reaction rates, as well as improving thermochemistry estimations

particularity for cyclic molecules.

2

1.2 Critical Literature Review

Global warming due to greenhouse gas emissions, increasing energy demands, and de-

creasing fossil fuel resources have increased interest in renewable fuels. Bio-oil, a carbon

neutral and renewable fuel, results from the fast pyrolysis of biomass in the absence of

oxygen. Biomass can be found as forest residue, animal waste, wood chips, and municipal

solid waste [24]. The major products of biomass fast pyrolysis under high temperature

and pressure are liquid bio-oil, hydrogen, carbon monoxide, carbon dioxide, light hydro-

carbons, and solid bio-char [25, 26]. The major components of bio-oil are organic acids,

ketones, furans, levoglucosan, phenolic, and cyclic oxygenate molecules [27–29]. Bio-oil

contains di↵erent amounts of these components depending on the initial source of the

biomass [30, 31]. Bio-oil can be either used directly as a fuel supply or further converted

to syngas. The expense of transporting biomass, a low density, bulky, polluting material,

and problems with direct conversion of biomass to syngas, makes processing of biomass

to bio-oil, followed by bio-oil high temperature gasification, a suitable alternative [32]. A

literature review that discusses published information regarding bio-oil gasification exper-

imentally and theoretically, is presented in the current section.

1.2.1 Bio-oil gasification experiments

There is no complete detailed chemical model for bio-oil gasification to date but there are

several experimental studies in the bio-oil gasification field. Lotfi et al.[32] investigated

syngas production from bio-oil gasification through thermal and catalytic reactions in a

pilot plant bubbling fluidized bed at moderate temperature and atmospheric pressure.

Catalytic gasification of bio-oils in their micro reactor revealed that a syngas with desired

yield can be produced from bio-oil gasification with a suitable catalyst and optimal oper-

ating conditions. Van Rossum et al.[33] also studied the bio-oil gasification in a fluidized

3

bed reactor over a wide temperature range (523–914 �C) with and without the use of

nickel-based catalysts. For both cases, initial activity of syngas (H2 and CO) production

had been shown at T > 700�C. Further, Adjaye et al.[34] worked on kinetic modeling

of non- catalytic conversion of bio-oil in a fixed-bed reactor. They calculated yields of

products as a function of temperature based on their proposed lumped kinetic model

from previous biomass studies and they did not provide a complete kinetic model for the

process.

Two non-catalytic experiments, one at lower temperature and one at higher temper-

ature range, were chosen to evaluate RMG-built model for bio-oil gasification, which will

be explained in further detail in the following section.

1.2.1.1 Low temperature bio-oil gasification

Zhang et al. [1] investigated the influence of the temperature and N2 flow rate on syngas

production in a fixed bed reactor at atmospheric pressure and temperature from 600�C to

1000�C. Thermochemical conversion of bio-oil leads to partially decomposition to other

forms of oxygenated molecules (CmHnOk) and some permanent gases and coke. The

overall bio-oil decomposition can be expressed as:

CnHmOk ! CxHyOz + gases(H2,H2O,CO2,CO,CH4, ...) + coke

They analyzed the gas products using a micro gas chromatograph and because of the high

content of the element oxygen in bio-oil, the gasification was carried out in the absence of

oxygen. They observed that by increasing temperature the content of CO decreased until

850�C but then increased with increasing temperature. CO2 increased with temperature

which they say is mainly because bio-oil contained a large amount of carboxylic acid and

carboxylic decomposition is the main source of CO2, although they didn’t mention their

primary bio-oil composition or the carboxylic content of the sample. Figure 1.1 shows

the four major syngas production at di↵erent temperatures.

4

PEER-REVIEWED ARTICLE bioresources.com

Zhang et al. (2010). “Bio-oil pyrolysis/gasification,” BioResources 5(1), 135-146. 142

Effect of Temperature in Fixed Bed The properties of gaseous products from bio-oil gasification at 600, 700, 800, 900 and 1000°C are shown in Fig. 6. The syngas mainly contained CO, H2, CO2, CH4, and the C2 fractions in gas phase were a very minor proportion. It can be seen that the content of syngas changed with increasing temperature. With increasing pyrolysis temperature from 800 to 900°C, the content of hydrogen reached a maximum at about 25% (In syngas). But the H2 content decreased as the temperature increased to 1000°C. This result was expected, since it could be seen that bio-oil at high temperature would lead to complete decomposition. Hydrogen reacted with oxygen-containing groups, leading to the formation of water. With increasing temperature, the content of CO decreased, it reached a minimum at 850°C, and then it increased with further increase in temperature. The carbon dioxide increased with increasing temperature. This was mainly because the bio-oil contained a lot of organic carboxylic acids, in which carboxyl decomposition was a main source of CO2. The content of CH4 increased, and at 700°C it reached a maximum, and then decreased with increasing in temperature.

600 700 800 900 100010

15

20

25

30

35

40 H2 CH4

CO CO2

Com

pone

nt o

f gas

pro

duct

(vol

.%)

Temperature (oC)

Fig. 6. Properties of gas product from bio-oil gasification at different temperatures Yields of the main gaseous products are shown in Table 2. In this table a nitrogen balance method was introduced and used to calculate the absolute gas yield and the gasification efficiency. It can be seen that increasing temperature favored improving the yield of syngas. When the temperature was 600°C, the efficiency of gasification was about 20%. The highest gasification efficiency was 80% when temperature was from 600 to 1000°C. However, the evolution of H2 and CO was mainly associated with high grade fuel through biomass, CO2 was not utilizable, and CH4 required reforming to produce more H2 and CO. When considering these results with respect to maximum H2 and CO

Figure 1.1: Syngas production from bio-oil gasification at di↵erent tem-peratures, reproduced from Zhang et al. [1].

They suggested that the optimum temperature for this process in a fixed bed reactor

is 1073 K and the higher residence time did not increase the syngas yield.

1.2.1.2 High temperature bio-oil gasification

Chhiti [2] studied the influence of high temperature on non-catalytic bio-oil gasification

process over a wide temperature range from 1200 K to 1700 K in a laboratory scale High

Temperature Entrained Flow Reactor (HT-EFR). The objectives were to determine the

syngas yield and composition as a function of the temperature. The feedstock used in

their experiments was bio-oil produced from a mixture of hardwood (oak, maple, ash) in

an industerial-scale fluidized bed reactor. Table I summarized the elemental composition

and physicochemical properties of their used bio-oil.

Table I: Elemental composition and physicochemical properties of Chhiti’s bio-oil (wt.%) [2].

C H O N H2O Ash Solids42.9 7.1 50.58 0.1 26 0.057 2.344

They observed that in the operating temperature between 1000�C and 1300�C, bio-oil

mostly decomposed to H2, CO, CO2, and CH4. Figure 1.2 shows the mole fraction of the

5

gas products from the gasification process in their experiment.

�����

1000°C and 1300°C, bio-oil is mainly decomposed to H2, CO, CO2, CH4 and C2H2. Above

1300°C C2H2 disappears, while CH4 disappears above 1400°C. As the temperature rises, the

fraction of H2 increases monotonically at the expense of carbon monoxide, methane and

acetylene. Above 1300°C the hydrogen content remains almost stable. At 1400°C hydrogen

mole fraction reaches the maximum value of 64 mol% of the syngas.

Figure 3.�Composition of the produced syngas (dry basis and without N2) - effect of

temperature, at S/F=4.5

The reactions that may explain the increase of hydrogen with temperature are :

� The steam reforming of CH4 and C2H2 into H2 and CO (2)

� The water gas shift reaction CO + H2O  ↔  CO2 + H2 (3)

The water gas shift reaction can also explain the increase of carbon dioxide and the decrease

of carbon monoxide between 1000 and 1200°C. Above 1200°C, carbon monoxide slightly

increases. This may be explained by steam gasification of the solid carbon residue resulting

from the pyrolysis of oil droplets to yield carbon monoxide and hydrogen following the

reaction:

C + H2O  ↔CO  +  H2 (4)

and potentially following the Boudouard reaction which would explain the slight decrease of

CO2:

C + CO2 →  2CO                                                                         (5)

Figure 1.2: E↵ect of temperature on composition of gas products inbio-oil gasification experiment, reproduced from Chhiti [2].

They also reported that H2 increased with increasing temperature in the experiment,

which is due to two reactions:

1. The steam reforming of CH4 and C2H2 into H2 and CO

2. The water gas shift reaction CO + H2O = CO2 +H2

They reported that the water gas shift reaction can explain the increase of carbon dioxide

and the decrease of carbon monoxide between 1000 and 1200�C. Above 1200�C, carbon

monoxide slightly increases. This may be explained by steam gasification of the solid

carbon residue. They also concluded that the increase in the reaction temperature results

in higher hydrogen concentration and higher bio-oil conversion.

6

1.2.2 Chemical modeling of bio-oil gasification

The e�ciency of bio-oil conversion to syngas, through the high temperature and pressure

gasification process, is highly dependent on the operation conditions of the process. Op-

timization of the process conditions requires an improved understanding of the chemical

kinetics of the thermal cracking reactions involved in bio-oil gasification [35]. One of the

key di�culties in building detailed chemical models for such systems is the complexity

and varieties of biomass components. Considering only three major biomass constituents

(lignin, cellulose, and hemicellulose) as major components of the bio-oil, is not defin-

ing the system composition well enough. Each of these constituents are macropolymers

with ill-defined components and the composition may vary from di↵erent biomass sources.

Furthermore, each component of biomass is pyrolyzed at di↵erent rates by di↵erent mech-

anisms and reaction pathways [2] which makes building detailed kinetic models for such

systems even more challenging. To date, most of the proposed models for biomass ther-

mal decomposition are in gas phase and the three major constituents are used as a model

components [22, 36, 37]. For example, Ranzi et al. [22, 38, 39] built a detailed kinetic

model for biomass pyrolysis and validated their model against existing experimental data.

In their modeling work, they characterized biomass in terms of cellulose, hemicellulose,

and lignin with elemental composition of C, H, and O. They also defined lumped chemi-

cal reactions for decomposition of each major component of the biomass with associated

reaction rate and stoichiometry parameters. The overall biomass model includes the com-

bination of all lumped chemical reactions of each biomass reference component. In this

section of thesis, a brief literature review of proposed kinetic models for biomass major

components is provided. Later in Section 1.4.6, these models and proposed pathways were

compared with RMG-built models for bio-oil gasification.

7

1.2.2.1 Cellulose kinetic modeling

Cellulose is one of the main components of biomass. During biomass thermal conversion,

cellulose decomposed to levoglucosan (LG) with the yield varying from 20 to 60% [3, 40],

depending on the initial source of the biomass. Levoglucosan can be used as the final

product or an intermediate to decompose to lower-molecular-weight (LMW) products.

Kawamoto et al. [41, 42] investigated the cellulose decomposition reaction mechanism

and observed that the levoglucosan (LG) is the primary product of the cellulose decom-

position and LMW products form later. Banyasz et al. [43, 44] proposed that cellulose

can decompose to either levoglucosan (tar) or hydroxyacetaldehyde, formaldehyde, and

CO via LMW intermediates. In their proposed kinetic model, they calculated the ac-

tivation energy of the levoglucosan and formaldehyde as 151 kJ/mol and 196 kJ/mol ,

respectively. Zhang et al.[45] studied the mechanism for levoglucosan (LG) formation

and proposed an energy barrier of 93 kJ/mol. They concluded that from woody biomass

resources, the LG is one of the main components of tar and bio-oil [46, 47]. Furthermore,

they performed density functional theory (DFT) calculations to propose a detailed chem-

ical reaction mechanism for levoglucosan thermal decomposition. They divided the LG

decomposition into three pathways: direct C-C bond breaking, direct C-O bond breaking

and LG dehydration. They concluded that the products from direct C-O bond break-

ing have a large contribution in the CO and H2O production, the main components of

the syngas. Figure 1.3 illustrates Zhang et al. three main proposed LG decomposition

chemical pathways.

8

Figure 1.3: Three proposed main pathways for LG thermal decompo-sition, reproduced from Zhang et al. [3].

In their theoretical study, they concluded that there are two possible pathways for

direct C-O bond breaking, one is exothermic and the other one endothermic. Furthermore,

the C-C bond breaking pathway is endothermic and the dehydration pathway is the more

feasible reaction channel for LG decoposition due to the lower barrier height. They also

came to the conclusion that the C-O bond breaking has lower barrier than the C-C bond

breaking reactions.

1.2.2.2 Lignin kinetic modeling

Lignin, another main component of biomass, is a valuable natural resource for biofuel

processing. Lignin chemical structure is complex and includes a variety of linkages such

as �-O-4 linkages, demonstrated in Figure 1.4.

Figure 1.4: Model for the lignin � -O-4 linkage [4]

The simplest proposed model for the � -O-4 linkage lignin is the phenethyl phenyl ether

9

(PPE) [5] and the thermal decomposition of the PPE has been studied by di↵erent research

groups. Britt et al. [5–7] conducted both fast and slow pyrolysis techniques such as Flash

Vacuum Pyrolysis (FVP) to study PPE primary unimolecular thermal decomposition

pathways such as bond scissions and intramolecular rearrangements pathways. Beste et

al. [4] used density function theories (DFT) to calculate bond dissociation enthalpies

(BDEs) of the O-C and C-C bonds in PPEs that were not experimentally available. They

concluded that the primary decomposition pathways for PPEs are mostly C-O bond

breakage and to some extent C-C bond breaking reactions. The reaction rate for both C-

O and C-C bond pathways depends on the BDE energies and are sensitive to the location

of the substituents. In their theoretical investigation, they showed that the C-O BDE

in PPE is 7.6 kcal/mol lower than the C-C BDE that confirms the lower percentage of

the products from C-C bond breaking experimentally. Four main primary decomposition

pathways for PPE were proposed, summarized in Figure 1.5.

Reaction 1:

Reaction 2:

Reaction 3:

Reaction 4:

Figure 1.5: Proposed reaction pathways for initial decomposition ofPPE from di↵erent studies [4–7]

Jarvis et al. [48] conducted an experimental investigation of the pyrolysis of PPE in

a hyperthermal nozzle in the temperature range of 300 to 1350�C to observe products for

reactions 1–4. They detected both radical and stable species such as phenoxy radical,

cyclopentadienyl radical, benzyl radical, styrene, and benzene which are the products

of the direct C-O and C-C bond breaking reactions (reactions 1 and 2). Furthermore,

detection of phenol and styrene species in their experiments, suggested pyrolysis through

10

the concerted reactions (reactions 3 and 4). They also performed quantum chemistry

calculations to support the experimental observations. They concluded that the C-O bond

breaking reaction (reaction 1) is significant at high temperatures (>1000 �C), whereas

the concerted reactions 3 and 4 are significant at lower temperatures. They had a similar

observation as previous studies regarding the minor influence of the C-C bond breakage

at both low and high temperature ranges.

1.2.2.3 Hemicellulose Kinetic modeling

Hemicellulose is a heteropolysaccharide constitute of monosaccharide such as xylose, glu-

cose, mannose, galactose, and arabinose [49] and the type and structure of the hemicellu-

lose depends on biomass sources. Bio-oil, syngas, and coke are the main products of the

hemicellulose pyrolysis . Hemicellulose thermal decomposition was the subject of many

experimental [50–52] and theoretical [8, 53] studies over the past decades. For example,

Shen et al. [52] conducted sets of experiments with TGAFTIR (thermo- gravimetric anal-

ysis coupled to Fourier transform infrared spectrometer) and PyGCFTIR (pyrolysisgas

chromatograph Fourier transform infrared spectrometer) to investigate the influence of

the temperature on the yields of the main gaseous products, CO, CO2, CH4, and H2 of

the hemicellulose pyrolysis. They concluded that the yield of CO is increased at higher

temperature, while the yield of CO2 was decreased. They also proposed that the feasible

pathways for formation of the bio-oil and gaseous products from hemicellulose pyrolysis,

were due to the xylan, O-acetylxylan, and 4-O-methylglucuronic acid primary decompo-

sition and other secondary reactions of the fragments. Huang et al. [8] applied density

functional theory methods to identify the main chemical pathways for the formation of

key products during xylose pyrolysis, as the most relevant constituent of the hemicellu-

lose. They proposed five main primary xylose decomposition pathways with the calculated

kinetic parameters, illustrated in Figure 1.6.

11

Reaction 1:

Reaction 2:

Reaction 3,4:

Reaction 5:

Ring-opening tautomerization reaction:

Figure 1.6: Proposed thermal decomposition pathways for xylopyra-nose [8].

The first decomposition pathway is ring-opening reaction through the tautomerization

with an energy barrier of 170.4 kJ/mol. In this primary ring-opening reaction C-O bond is

breaking, double bond is forming and hydrogen is transferring all at once as a single step

elementary reaction. The acylic molecule, can go through the further pyrolytic reactions

and form other small molecules (reactions 1-5). Huang et al. [8] based on their DFT

calculations for both kinetics and thermodynamics, concluded that reaction pathways

(2) and (5) are the major reaction channels in the xylopyranose pyrolysis which was in

agreement the observed experimental results.

1.3 Computational Method

As already mentioned, Bio-oil is a mixture of hundreds of chemicals derived from fast

pyrolysis of biomass. Production of syngas from bio-oil is usually a high pressure and

high temperature process and optimizing the process conditions (temperature, pressure,

residence time, etc.) requires an improved understanding of the chemical kinetics of the

thermal cracking reactions involved in bio-oil gasification. In this study, detailed ki-

12

netic models for bio-oil gasification were generated using Reaction Mechanism Generator

(RMG), an open source software tool that can build detailed kinetic models for hydrocar-

bon pyrolysis and combustion. Starting with a surrogate bio- oil consisting of ten known

species, and reaction conditions (temperature, pressure, reaction time) from the literature,

RMG builds a detailed kinetic model consisting of thousands of elementary reactions and

hundreds of intermediate species. In this section, an introduction to RMG, Cantera, an

open source software package for modeling chemical kinetics models, and steps for bio-oil

gasification model generation using RMG are provided.

1.3.1 Reaction Mechanism Generator

Since manually calculating the thousands of parameters in an extensive detailed kinetic

model is e↵ortful and error-prone, it is preferable to use computers instead. In recent

years, several computational algorithms to build large kinetic models have been developed

[54, 55]. RMG, Reaction Mechanism Generator, is an open-source automatic reaction

mechanism generator for building large kinetics models [56]. Like other reaction network

generators, RMG has to store chemical species in memory and identify duplicates, create

reactions and new species in the network, and estimate the thermochemistry of each

species and the rate coe�cient of each reaction. There are currently two versions of the

RMG software: the original, which is mostly written in Java with some Fortran, RMG-

Java [57], and a more recently developed version in Python, RMG-Py [10]. In this work,

we used both RMG-Java and RMG-Py versions to build models with similar specifications

for bio-oil gasification. The version of RMG-Java used was a pre-release of version 4.0,

and the RMG-Py was an early beta pre-release version.

13

1.3.1.1 Molecular Representations

In RMG, molecules represent as graphs [58], with atoms as nodes and bonds as edges

connecting the nodes, demonstrated in Figure 1.7; standard graph-theory methods use

to identify equivalent graphs and ensure uniqueness.

C CH

H

H

H

1 2

3

4

5

6

1 C u0 p0 c0 {2,D} {3,S} {4,S}2 C u0 p0 c0 {1,D} {5,S} {6,S}3 H u0 p0 c0 {1,S}4 H u0 p0 c0 {1,S}5 H u0 p0 c0 {2,S}6 H u0 p0 c0 {2,S}

Atom index

ElementUnpaired electrons

Type of bondsCharge

Lone pair electrons

Figure 1.7: Molecules are represented as 2-dimensional graphs in RMG

1.3.1.2 Data Hierarchy in RMG

Groups are the most important part in all RMG’s databases. Generally, groups describe

the structures around the reaction atoms. Data that are needed to compute both thermo-

dynamic and kinetic parameters are associated with groups. In order to use estimation

approaches during mechanism generation, a robust and reliable method for rapidly iden-

tifying which group values should be used for any given molecule, is required. RMG’s

thermodynamics and kinetics databases are stored all the group definitions and the cor-

responding group values in a hierarchical tree structure. The root nodes in the tree are

more general groups and children nodes, descending from the root nodes, are the most

specific groups. For example, Figure 1.8 demonstrates the trees of the H-abstraction with

the specified parent and children nodes for the given family.

14

H-abstraction reaction: X_H + Y_rad X_rad + Y_H

Figure 1.8: Groups tree structure for H-abstraction family, reproducedfrom RMG documentation [10]. Indented text and schematics show theused syntax in RMG to represent the parent and children nodes.

In the following section a brief introduction to RMG’s thermodynamics and kinetics

databases is provided.

1.3.1.2.1 Thermodynamic Database RMG’s thermodynamics database reports

three thermochemical quantities: 1) standard heat capacity data Cp(T ) as a function

of temperature T, 2) standard enthalpy of formation �f (H)(298K) and 3) standard en-

tropy S(298K) at 298K. RMG’s thermodynamics database has two main folders:

• Species thermochemistry libraries: In this folder the species with known thermo-

chemistry parameters are stored, the value of the thermo properties are from either

available experimental data or high-level quantum chemistry calculations.

• Species thermochemistry groups: In this folder species group additive values, ring

strain corrections, Hydrogen Bond Increments (HBI), and non-nearest neighbor in-

teractions groups are stored in a hierarchical tree fashion.

– Group additive values (GAV): In this file the the group additivity values for

di↵erent functional groups are stored in a hierarchical tree.

15

– Ring Strain Corrections (RSC): RMG separates monocyclic and polycyclic ring

correction databases.Monocyclic RSCs are used for molecules that contain one

single ring; for a molecule with two or more fused rings RMG uses a polycyclic

ring strain correction.

– Hydrogen Bond Increments (HBI): RMG has the HBI groups to consider the

influence of the loss of a hydrogen atom on enthalpy of formation, entropy and

heat capacity of the radical species.

– Non-nearest neighbor interactions: RMG also has a database with NNIs be-

side the group additivity values, to consider the interactions between atoms

separated by at least 2 atoms, such as alkane 1,4-gauche, alkane 1,5, alkene

1,4-gauche, alkene single and double cis, ene-yne cis, and ortho interactions.

1.3.1.2.2 Thermochemistry Estimation

RMG estimates the thermochemistry of species via three ways:

1. Species thermochemistry libraries: these databases include thermochemical param-

eters of the species. Data in these libraries come from either published experimental

values or high-level quantum chemistry calculations. When RMG looks for the ther-

mochemistry of a specie, values in these libraries always have the highest priority

for themo estimations in RMG.

2. Group contribution methods: RMG uses libraries of known values wherever possible

to find thermochemical data for species, but usually the data are unknown and it

estimates parameters. Thermochemistry data more commonly are estimated based

on Benson’s group additivity method [59]. In this method, the molecule breaks

down to functional groups and the total thermochemistry property of the molecule

will be the summation of the contribution of each functional group. Figure 1.9

shows an example of standard enthalpy of formation estimation for isobutylbenzene

16

using group additivity approach. The comparison between the enthalpy of forma-

tion from group additivity approach and NIST reported value for isobutylbenzene,

demonstrates that the group additivity is a reliable method to estimate the ther-

modynamics when functional groups are adequate.

ΔfH°= -5.138 kcal/molNIST value:

Figure 1.9: Group additivity approach to estimate isobutylbenzenestandard enthalpy of formation and comparison with the NIST reportedvalue.

3. On-the-fly Quantum-chemical calculation of Thermochemical Properties: Quantum

mechanical calculations are recommended to improve the thermochemistry estimates

of molecules that are not available in one of the species thermochemistry databases,

and also cannot be estimated with good accuracy using the group additivity method

such as cyclic and oxygenated species. Quantum mechanics uses a variety of math-

ematical transformation and approximation techniques to find molecular geome-

tries, vibrational frequencies, and bond energies to compute the thermochemical

properties accurately enough. The QMTP interface steps toward thermodynamics

estimation are illustrated in the Figure 1.10.

17

Figure 1.10: On-the-fly Quantum-chemical (QMTP) calculation steps(reproduced from RMG documentation [10]) toward thermochemicalproperties calculations in RMG.

First the molecular connectivity structure of the molecule is converted into a 3-D

representation using a distance geometry method, followed by a optimization using

the UFF force field in RDKit [60]. Next, an input file containing the 3D atomic

geometries along with a number of keywords will be generated. The generated

input file will be sent to a computational chemistry package, either OpenMopac

[61] or Gaussian [62], that calculates the thermochemistry of the given molecule

on-the-fly. The keywords specify the type of calculation, and the level-of-theory. In

the end the calculated thermochemistry data will be sent back to RMG. Table II

demonstrates the computational chemistry packages and levels of theory that are

currently available in the QMTP.

Table II: Supported quantum chemistry packages and levels of theory in the QMTP, reproducedfrom RMG documentation [10].

QM Package Supported Levels of TheoryOpenMopac semi-empirical (PM3, PM6, PM7)Gaussian03 semi-empirical (PM3)MM4 molecular mechanics (MM4)

18

Although using QMTP method reduces the errors for thermodynamics estimation

of some species, they are more expensive than the GA method in terms of memory

and computation cost. In cases of memory limitations or failures occurring for the

QM methods, RMG falls back to the group additivity approach.

1.3.1.2.3 Kinetic Database

The key step in generating a reliable chemical mechanism, is being able to accu-

rately estimate Arrhenius rate parameters. For each reversible elementary reaction

A + B ! C + D, both forward and reverse reaction rates should be specified in the

mechanism. The forward reaction rate (kf (T )) can be expressed as pressure independent

modified Arrhenius rate equation:

kf (T ) = AT n exp(� Ea

RT) (1.1)

Where A is the pre-exponential factor, T is the temperature, Ea is the activation

energy, and R is the universal gas constant. The reverse reaction rate (kr(T )), can be

calculated from reaction’s equilibrium constant (Keq(T ))from thermodynamic properties:

Keq(T ) =kf (T )

kr(T )= exp(��(G)

RT) (1.2)

�(G) = �(H)� T�(S) (1.3)

Where �(G) is the Gibbs free energy and has a relationship with enthalpy and entropy

of formation of the species.

RMG’s kinetics database has the following main folders to estimate the reaction kinetic

parameters from multiple ways:

19

• Libraries: kinetic libraries contain kinetic parameters for specific reactions that are

extracted from published literature or high-level quantum chemistry calculations.

RMG always pick kinetics from libraries over other methods. In case of availability

of data for a single reaction in multiple libraries, the priority of the data depends

on how libraries are listed.

• Families: RMG uses reaction families to generate all the possible reactions that a

species can undergo in the presence of the other species in the chemical mechanism;

every reaction family represents a particular type of elementary chemical reaction,

such as bond-breaking, or radical addition to a double bond. Each reaction family

has a recipe for mutating the graph, and a library of rate expressions for di↵erent

reacting sites [63, 64]. As an example, general reaction template and recipe of the

H-abstraction reaction family is illustrated in Figure 1.11.

R1 R1R2 R2

H H*1 *1

*2 *2

*3 *3

H-abstraction reaction recipe:Break bond {*1, S, *2}Form bond {*2, S, *3}Gain radical {*1, 1}Lose radical {*3, 1}

H-abstraction reaction template:

+ +. .

Figure 1.11: General template and reaction recipe for H-abstractionreaction family in RMG.

So far, there are 45 reaction families in RMG’s kinetic database. When RMG

generates a reaction, for example the following H-abstraction illustrated in Figure

1.12, first the reacting atom will be specified based on the reaction template. Next,

RMG will search within the corresponding reaction family, in this case H-abstraction

reaction family, to find the groups that mach the reaction.

20

C_pri C_pri

C_secO_pri_rad

Figure 1.12: Reactants kinetic trees (reproduced from RMG documen-tation [10]) for H-abstraction reaction and reaction matched template.

Desired templates for the example reaction are C-sec and O-pri-rad. After finding

the matched groups, the algorithm will search for data and rate parameters in the

database for the template. If there are no data available for the C-sec and O-pri-rad

templates in the database, RMG using rules will fall up to more general nodes, Cs-H

and O-rad, demonstrated in Figure 1.13:

Figure 1.13: Falling up to the more general parent nodes from the exactmatch nodes to find data, reproduced from RMG documentation [10].

If there are still no kinetic data in the Cs-H and O-rad in the database, the entire

set of children for Cs-H and O-rad will be checked. For this example, this set would

include every combination of C-pri, C-sec, C-ter with O-pri-rad, O-sec-rad. If any

these templates have kinetics, an average of their parameters will be returned as an

estimated rate parameters for the mentioned reaction.

• The training set and rules: both contain trusted kinetics that are used to fill in

templates in a family.

21

– The training set contains kinetics for specific reactions, which are then matched

to a template.

– A similar group contributions method is used to estimate the rate coe�cients

for the reactions: functional groups are identified using graph matching and

the rates are estimated from a database of rules [55]. The kinetic rules contain

kinetic parameters that do not necessarily correspond to a specific reaction,

but have been generalized for a template.

When determining the kinetics for a reaction, a match for the template is searched

for in the kinetic database. The three cases in order of decreasing reliability are:

1. Reaction match from training set.

he reaction match from training set is accurate within the documented uncer-

tainty for that reaction.

2. Node template exact match using either training set or rules.

A template exact match is usually accurate within about one order of magni-

tude.

3. Node template estimate averaged from children nodes.

When there are no kinetics available for for the template in either the training

set or rules, the kinetics are averaged from the children nodes as an estimate.

1.3.1.3 Rate-Based Model Enlarger

RMG chooses species to include in the model according to reaction flux. It gradually

expands a ‘core’ model by adding species from the edge [65], an example is illustrated in

Figure 1.14. The core begins with a trusted seed mechanism of small-molecule chemistry

and the initial reactant species (in this case 10 components of bio-oil). All reactions

between core species are identified and their rates estimated; any new products are added

22

to the edge.

Figure 1.14: RMG explores paths with high reaction rates and willmove them into the model ’core’.

User-defined tolerances control the allowed flux (relative to the root-mean-squared

flux of reactions in the core) for moving a reaction to the core or keeping the reaction on

the edge. There are possibilities in RMG to set additional tolerances for the di↵erential

equations solver accuracy and the pruning (deletion) of minor edge species. The core

is then expanded iteratively, repeatedly adding the edge species with the largest rate of

creation until the user-specified tolerance is reached and the core model is designated

complete (for the given tolerance). A tight tolerance (small number) will generate a large

model with a long calculation time, whereas with a looser tolerance (larger value) RMG

will stop sooner and the final model will be smaller.

1.3.1.4 Pressure Dependence in RMG

Two conditions can cause pressure dependence: low pressures and high temperatures.

Most discussions on the subject of pressure dependence focus on unimolecular reactions

at low pressures. The collision frequency is directly proportional to the pressure, so as

the pressure is decreased, the rate of collisional energy transfer decreases. Eventually

the pressure becomes low enough that the rate of chemical reaction becomes faster than

23

the collision rate. RMG is able to calculate pressure-dependent rate constants k(T,P)

for unimolecular reaction networks by solving master equation. A unimolecular reaction

network is defined as a set of chemically reactive molecular configurations divided into

unimolecular isomers and bimolecular reactants or products. Reactants can associate to

form an isomer, while such association is neglected for products. These configurations are

connected by chemical reactions to form a network; these are referred to as path reactions.

The system also consists of an excess of inert gas, representing a thermal bath; this allows

for neglecting all collisions other than those between an isomer and the bath gas. An

isomer molecule at su�ciently high internal energy can be transformed by a number of

possible events:

• The isomer molecule can collide with any other molecule, resulting in an increase

or decrease in energy

• The isomer molecule can isomerize to an adjacent isomer at the same energy

• The isomer molecule can dissociate into any directly connected bimolecular reactant

or product channel

It is this competition between collision and reaction events that gives rise to pressure-

dependent kinetics.

1.3.1.5 Output from RMG

RMG’s output, a detailed reaction network with associated thermodynamic and kinetics

parameters, is printed out in the ‘Chemkin format‘ and will be saved in a ’Chemkin

file’. The information in the Chemkin file is a list of all species in the model with their

associated chemical formula and thermochemistry information, standard heat and entropy

of formation and heat capacity. Also the file contains a list of reactions with known kinetic

parameters. An example of a chemkin file is presented in Figure 1.15.

24

Figure 1.15: The Chemkin file showing the list of species, thermochem-istry, and reaction information as RMG’s output.

Many research groups have been publishing their models in Chemkin format for a long

time and this format is readable for further simulations by other chemical packages such

as Cantera [66] and Chemkin [67] to solve complex chemical kinetics problems. In this

research, Cantera has been used for further simulations of RMG-generated models such

as simulations of Plug Flow Reactors (PFR) with known operational conditions.

1.3.2 Cantera

Further simulations to determine the characteristics of biofuel processes in batch, CSTR

reactors, and shock tube under di↵erent operating conditions is done using Cantera [66].

Cantera is an open source object-oriented software for modeling chemical kinetics, thermo-

dynamics, and transport processes. Furthermore di↵erent classes (objects) are provided

in Cantera to represent the phase of matter, interface between phases, time-dependent

reactor network and steady one-dimensional reacting flows. Here is some useful objects

which are currently used in biofuel simulations:

25

• Importing Phase Objects: This object is importing one phase from an input file. In

this study the phase object is the RMG-built gas phase kinetic network.

• Chemical Kinetics: This the Cantera’s kinetics manager object and is responsible for

evaluating reaction rates of progress, species production rates, and other quantities

pertaining to a reaction mechanism.

• Thermodynamic and Transport Properties: This class is responsible to describe the

thermodynamic state of the system.

• Zero-Dimensional Reactors Simulation: Cantera is conducting zero- dimentional ki-

netics simulations using this class. The type of fluid the reactor containing should

be specified through the associated object. Then this object will be used to com-

pute all required thermodynamic properties and species production rates, and must

implement the reaction mechanism and equation of state desired for the reactor.

1.3.3 Model Verification and Validation

After model generation, the most important step is the mechanism evaluation. There

are several methods toward mechanism evaluation; comparison to available experimental

data, reaction flux analysis to determine the dominant reaction channels, and sensitivity

analysis to reveal the sensitive parameters to reduce the uncertainty. After the mechanism

evaluation, from learned lessons, the model might need to be improved with new data.

New data can be provided either from theoretical calculations or from experiments. After

updating the RMG’s databases with new data and fixing bugs, RMG will generate a new

improved model with the best accessible chemical data. As a summary, Figure 1.16

illustrates model evaluation steps.

26

Figure 1.16: Steps toward building reliable detailed kinetic modelsusing RMG.

1.3.4 Bio-oil gasification modeling

In the present study, RMG was used to build bio-oil gasification models for syngas produc-

tion and models were evaluated against Chhiti et al. [2] and Zhang et al. [1] experiments

covering the range of temperatures and pressures. Sensitivity analysis was used to iden-

tify what information would be most valuable to obtain in order to improve mechanism

predictions. Furthermore, the e↵ect of RMG parameters on the model predictions were in-

vestigated, as well as the influences of pyrolysis temperature, residence time, and pressure

on the syngas yields. Model evaluations showed that RMG missed some reaction families

in generating bio-oil gasification mechanisms, and several improvements are needed for

thermodynamic and kinetic parameters estimations. Finally, several ideas for future work

in order to improve RMG for bio-oil gasification modeling are discussed. These ideas

include some thoughts on updating RMG’s current reaction families and rates, as well as

improving thermochemistry estimations for some cyclic molecules.

1.3.4.1 Bio-oil Composition

Branca et al. [69] experimentally categorized bio-oil composition into several chemical

groups including water (20-30)%, aldehydes (10-20)%, lignin fragments (15-30)%, car-

27

boxylic acid, carbohydrates (5-10)%, and phenols (2-5)% using GC/MS, and quantified

the mass fraction of 40 components of bio-oil. Based on these measurements, Zhang et al.

[70] modeled bio-oil as the mixture of 10 major components, by keeping the mass fraction

of the water the same as the experiment and scaling up the mass fraction of the other

nine components in order to account for the neglected components. In the current work,

RMG-built kinetic models are started from the Zhang et al. [70] 10-component surrogate

bio-oil mixture. The species and their mass fractions are listed as Model 1 in Table III.

Table III: Composition of surrogate bio-oil used in modeling.

Component % by massModel 1 Model 2(Normal) (High Acid)

Water 21.10 12.0Hydroxyacetaldehyde 21.77 12.5Acetic Acid 9.48 19.5Hydroxypropanone 15.06 8.6Levoglucosan 17.27 9.9Propanoic Acid 1.25 29.3(5H)-furan-2-one 2.37 1.36Isoeugenol 10.79 6.2Phenol 0.37 0.21Syringol 0.54 0.31

However, in order to investigate the e↵ect of a higher initial fraction of carboxylic

acids on the final simulation results, another model was generated in RMG with a much

higher acid content. The ratios of species were fixed except the amounts of the two car-

boxylic acids (acetic acid and propionic acid) were increased so that the overall elemental

composition closely matched that given by Chhiti et al.[2] (Table IV). The composition

of this “High Acid” Model 2 is also shown in Table III.

28

Table IV: Elemental composition of bio-oil from experiment II (ref [2]) and RMG model

Feedstocks C (wt.%) H (wt.%) O (wt.%) N (wt.%)

Experiment I (ref [1]) 49.7 7.4 42.3 0.6Experiment II (ref [2]) 42.9 7.1 50.6 <0.1RMG Model 1 (Normal) 37.7 7.8 54.5 No NitrogenRMG Model 2 (High Acid) 41.4 7.7 50.9 No Nitrogen

1.3.4.2 Simulating syngas production

The Python interface to Cantera 2.0 is used to create simulations of both Plug Flow Reac-

tor (PFR) and Continuous Stirred Tank Reactor (CSTR) conditions for bio-oil pyrolysis,

with initial mass fractions taken from Table III, and with residence times, temperatures,

and pressures either corresponding to experimental data [1], or varied as part of an op-

timization study. The mole fractions of the major gases H2, CO, CH4 and CO2 at the

end of the simulation were recorded, as these are the parameters reported by Zhang et

al. [1]. As a summary, Figure 1.17 demonstrates the complete work-flow of the bio-oil

gasification chemical kinetic modeling using RMG to generate the model and Cantera for

performing further simulations with corresponding input and output parameters.

Output:Reaction mechanism with known thermochemistry and kinetic parameters in chemkin format.

⇌RMGInput:Temperature

Pressure

Seed mechanism

Initial mole fraction

Inert bath gas

Termination time

Tolerance Output:• Bio-oil gasification

• Syngas mole fraction

Cantera Input:Temperature

Pressure

Initial mole fraction

Termination time

Figure 1.17: Work-flow of the reaction mechanism modeling for bio-oilgasification using RMG and Cantera.

Many simulations were performed to investigate the e↵ects of varying temperature,

residence time, and pressure; of simulating CSTR versus PFR; of constructing models

with or without pressure-dependent reactions; and of the influence of model size from a

29

series of incomplete (interrupted) RMG jobs.

1.3.5 Optimization

The optimization of the bio-oil gasification process involves looking for the optimal tem-

perature, pressure, and residence time within given constraints to maximize some objective

function. As the pyrolysis of bio-oil is a complex process, there are many possible objec-

tive functions. In this work, primarily as proof of concept, we used a very simple objective

function to represent syngas yield: the sum of the hydrogen and carbon monoxide mole

fractions exiting the reactor. Also, the constraints range for temperature, pressure and

time are chosen from experiments. The optimization model is therefore:

MaximizeT,P,t

f(T, P, t) = yH2+ yCO

subject to 800 K < T < 1700 K

0.5 atm < P < 20 atm

0.5 sec < t < 30 sec

The Constrained Optimization by Linear Approximation (COBYLA) method from the

SciPy toolkit [71] was used to solve the optimization, with the objective function being

evaluated by Cantera [66].

1.4 Results and Discussions

1.4.1 Influence of model size

To investigate the influence of model size, a large RMG-Java model was interrupted at

three stages of its generation, resulting in incomplete models containing 103 species, 202

species, and 307 species in the core. Full model sizes (core and edge) are listed in Table

30

V.

Table V: RMG-built model sizes in core and edge

Model Core size Edge sizeSpecies Reactions Species Reactions

Model I 103 1,711 10,500 27,725Model II 202 3,765 19,322 251,781Model III 307 7,161 22,404 428,714

The PFR and CSTR reactors produced similar results for all three models; the CSTR

results are shown here. It can be seen from Figure 1.18 that predicted syngas yield,

specially H2 and CO, increases with the model size. The models are quantitatively and

qualitatively di↵erent, which shows the importance of having a large kinetic model.

CH4

H2

CO

CO2

0

0.1

0.2

0.3

0.4

0.5

600 800 1000 1200 1400

Out

let M

ole

Frac

tion

Temperature (C)

103 Species

202 Species

307 Species

Figure 1.18: Syngas production varying with incomplete model size from a CSTR withresidence time 5 sec.

The RMG models were built on nodes of a linux cluster with 4 or 8 GB of RAM

each. As bio-oil contains several large and complex molecules, unfortunately RMG ran

out of memory and all the RMG-built models for bio-oil are currently incomplete in

both RMG-Java and RMG-Python. Several attempts were made to build a complete

model with looser tolerances, between 1 and 5. RMG-Py completed a model with a very

31

high tolerance, 5, and reaction time 0.5 sec. The model core had only 37 species and

186 reactions, missing a lot of important pathways and species. Results from Cantera

simulations showed that the completed model with the high tolerance is not useful for

predicting syngas formation.

1.4.2 Influence of pressure and pressure-dependent kinetics

Figure 1.19 shows that there is an e↵ect of reactor pressure on the predicted mole

fractions at the reactor exit. However, for this system (unlike small molecule combus-

tion), there doesn’t seem to be much di↵erence between results from models without

pressure-dependent calculations and with pressure-dependent reactions calculated by

RMG (Figure 1.19). In both models, increasing the pressure will increase the syngas

yield. The biggest di↵erence is in H2 and CH4 yield below 3 atm and from 600 to 1400 C.

32

CO2

CH4

CO

H2

0

0.1

0.2

0.3

0.4

0.5

600 800 1000 1200 1400

Out

let M

ole

Frac

tion

Temperature (C)

P= 1 atm P= 3 atm P= 5 atm P= 10 atm

(a)

CO2

CH4

H2

CO

0

0.1

0.2

0.3

0.4

0.5

600 800 1000 1200 1400

Out

let M

ole

Frac

tion

Temperature (C)

P=1 atm P=3 atm P=5 atm P=10 atm

(b)

Figure 1.19: Mole fraction of four major gases at exit of a CSTR with residence time 5 secondsat a range of temperatures and pressures, according to kinetic models built by RMG- Java.(a) without pressure-dependence calculations (b) with pressure-dependent reaction networkscalculated by modified strong collision approximation.

33

1.4.3 Comparison with experiments

The simulated syngas species concentrations at the reactor outlet were compared with

measurements from two bio-oil gasification experimentals described in the literature [1, 2]

(Figure 1.20). Although the simulations give actual amounts of these and hundreds of

minor species, because the only published data are the relative amounts (fractions sum

to 1.0) of the four major gas products (H2, CO, CH4, and CO2) at various temperatures,

those are the only data compared.

0

0.25

0.50

0.75

1.00

600 700 800 900 1000

(a) Experiment I

Syng

as F

ract

ion

Temperature (C)

CO2

CO

H2

CH4

0

0.25

0.50

0.75

1.00

600 700 800 900 1000 1100 1200 1300 1400

(c) RMG Low Acid Model

Syng

as F

ract

ion

Temperature (C)

CO2

CO

H2

CH4

1100 1200 1300 1400

(b) Experiment II

Figure 1.20: Distribution between four major gas components as afunction of temperature, (a) from experimental work by Zhang et al.[1]at 100 C intervals from 600 to 1000 C, (b) from Chhili et al.[2] at 100 Cintervals from 1000 to 1400 C, (c) from Cantera simulations (this work)at 100 C intervals from 600 to 1400 C

Besides the discrepancies between the experiments, it is obvious from Figure 1.20

34

that there is a di↵erence in CO2 and CO yields between the experimental and modeling

results. Despite this, H2 and CH4 predictions are reasonably compatible with both exper-

iments. Also, it is observed that by increasing process temperature the CH4 production

is decreased. The thermodynamics of the water-gas shift reaction would lead the ratio

of [CO2][H2] to [CO][H2O] at equilibrium to decrease with increasing temperature. The

simulation reaches and is limited by the equilibrium position at about 1200 C, but at

lower temperatures there is less H2 and CO2 than there would be at equilibrium.

Shen et al. [52] have explained that due to the presence of a large number of cyclic

oxygenated compounds such as xylan in bio-oil, CO formation is highly a↵ected by ring-

opening decomposition reactions of these components and is increasing at higher tem-

perature. On the other hand, CO2 is mainly contributed by decarboxylation reactions

and is simultaneously decreasing with increasing temperature. Additionally, Zhang et

al. discussed that the increase of CO2 concentration with temperature (600 – 1000 C)

in their experiment was mainly because the high carboxylic acids content in their bio-oil

feedstock (carboxylic acids decomposition was a major source of CO2) but they did not

state their feedstock composition, only elemental composition, so the initial amount of

carboxylic acids is unknown.

To investigate the e↵ect of a higher initial fraction of carboxylic acids on the final

simulation results, another model was generated in RMG with a much higher initial

acid content (Table IV). Simulation results for syngas production from the RMG-built

”high acid” model, Figure 1.21, shows that an increase in the carboxylic acid content

doesn’t make big di↵erences in CO and CO2 levels, but at low temperature the model

still underestimates CO2 and overestimates CO compared to Experiment I[1].

35

0

0.25

0.50

0.75

1.00

600 700 800 900 1000 1100 1200 1300 1400

RMG High Acid ModelSy

ngas

Fra

ctio

n

Temperature (C)

CO2

CO

H2

CH4

Figure 1.21: Distribution between four major gas components as afunction of temperature from high acid model.

1.4.4 Sensitivity Analysis

A sensitivity analysis was carried out on models to identify the important channels of

reactions for carboxylic acid decomposition to CO and CO2 under simulation conditions.

The analysis is from the pressure-independent (high pressure limit) model and the small

chemistry reactions are from Glarborg seed mechanism [72]. The sensitivity analysis can

be explained by consideration of two domains: low temperature and high temperature. At

both low (700C) and high (1400C) temperatures the productions of CO and CO2 are most

sensitive to the decomposition of acetic and propanoic acids and several radical reactions.

The results for both domains are briefly summarized in Figure 1.22.

36

0.0-0.393 0.426

CO2 + CH4 ⇌ Aa

Ppa + H ⇌ C[CH]C(=O)O + H2

Ppa + OH ⇌ C3H5O2 + H2O

CH3 + [CH2]C(=O)O ⇌ Ppa

CO2 + C2H6 ⇌ Ppa

CH2CH=CHC(=O)O ⇌ Hf2O

(a) CO2 Sensitivity at T=700 C , P= 1atm and t=4 sec

-0.252 0.0

C2H2 + OH ⇌ CH2CO + H

H2O + O=C=CH2⇌ Aa

Ppa + H ⇌ C[CH]C(=O)O + H2

C2H2 + OH ⇌ CO + CH3

CO2 + C2H6 ⇌ Ppa

CO2 + CH4 ⇌ Aa

(b) CO2 Sensitivity at T=1400 C , P= 1atm and t=4 sec

-0.378 0.1870.0

Ppa + H ⇌ C[CH]C(=O)O + H2

CO2 + C2H6 ⇌ Ppa

CH3CO + HCO ⇌ CH3C(=O)CH=O

Aa + H ⇌ [CH2]C(=O)O+ H2

CO + OH ⇌ HOCO

Ppa + OH ⇌ C[CH]C(=O)O + H2O

(c) CO Sensitivity at T=700 C , P= 1atm and t=4 sec

C2H2 + OH ⇌ CH2CO + H

OH + HC�CCH2⇌ C2H2 + H2C=O

C2H5+ O=COH ⇌ Ppa

C2H2 + OH ⇌ CO + CH3

C2H2 + C3H4 ⇌ C2H + C3H5

CO2 + CH4 ⇌ Aa

0.0962

(d) CO Sensitivity at T=1400 C , P= 1atm and t=4 sec

-0.00037

* Ppa: Propanoic acid* Aa: Acetic acid* Hf2O: 5H-furan-2-one

Figure 1.22: Sensitivity analysis for (a) CO2 at T=700C, (b) CO2 at T=1400C,, (c) CO atT=700C,, (d) CO at T=140C,. See text for model details.

The result of sensitivity analysis showed that free radical reactions are greatly dom-

inant at low temperature. Also predicting more methane than CO2 may indicate that

the unimolecular decomposition of acetic and propanoic acids are not taking place sig-

nificantly at lower temperature, which is in agreement with the observation of Doolan et

al. [73] in their kinetics study of acetic and propanoic acids decomposition. However,

Frey [74] and Kistiakowsky [75] suggested high amounts of CO at low temperature are

significantly coming from ketene decomposition. Decomposition of acetic and propanoic

acids to water and ketene are observed in models at both low and high temperature, and

these ketene molecules will eventually decompose into the CO and other radicals in the

model.

37

1.4.5 Poor Thermochemistry For Cyclic Molecules

In the literature there are no reports about complete detailed kinetic model of bio-oil

gasification to date but there are several studies of detailed chemical modeling of biomass

pyrolysis and gasification as a main source of the bio-oil. Several gas phase detailed

chemical models [37, 69, 76–79] were recently developed based on the reactions involved

in thermal decomposition of three major constituents of biomass: cellulose, hemicellu-

lose, and lignin. Due to the similarity between classes of hydrocarbons in the biomass

and bio-oil, bio-oil models were compered with proposed biomass models. One of the

proposed models of biomass pyrolysis from Ranzi et al. [22, 80, 81], focused on studying

the main kinetic features of biomass pyrolysis in the gas phase and proposed the detailed

kinetic model with associated thermochemistry and kinetic data from previous experimen-

tal studies and modeling e↵orts. RMG-built models were compared with Ranzi’s biomass

mechanism and a few published data for thermochemistry of heterocyclic molecules. Com-

parison shows that thermodynamic parameters of some cyclic and oxygenated species from

primary decomposition of cellulose, hemicellulose, and lignin fragments in RMG may not

be estimated accurately using the Group Additivity approach; for example, the enthalpy

of formation for xylofuranose is around 60 kcal/mol lower from that in reference [22],

although it is not clear how the latter was estimated. However, other estimates place it

40 kcal/mol lower still[82], so the range in estimates is remarkably large.

Species thermochemistry in RMG can be estimated based on two approaches: group

additivity [59] and on-the-fly quantum mechanics (QM) methods [83] using Gaussian or

OpenMopac [61]. This automatic QM approach was implemented specifically for cyclic

compounds, where group additivity often performs poorly [83]. Switching from group

additivity to QM methods for thermochemistry calculations of cyclic species shows signif-

icant improvement in species’ thermochemistry. Table VI shows the di↵erences of ther-

modynamic data between Ranzi’s biomass model and RMG estimated thermochemistry

38

from both group additivity and QM approaches for some cyclic and oxygenated species.

Table VI: Comparison of RMG estimated thermochemistry from both Group Additivity (GA)approach and Quantum Mechanics (QM) calculations of some species to Ranzi’s biomass model[22] and other published literature where available.

Species Quantity Ranzi model RMG (GA) RMG (QM) LiteratureO

Furan

�Hf (kcal/mol) –8.3 4.9 –4.1 –6.6 [84]

S�(cal/mol/K) 63.9 65.2 64.3 —OH

OH

HO

O

HO

Xylofuranose

�Hf (kcal/mol) –151.5 –213.7 –226.2 –252.8 [82]

S� (cal/mol/K) 104.9 117.0 104.1 40.4 [82]

OO

OH

OH

OH

H

HLevoglucosan

�Hf (kcal/mol) –200.9 –212.5 -204.2 –199.7 [85]

S� (cal/mol/K) 113.7 58.3 98.3 —

OH

OO

2,6-dimethoxy phenol

�Hf (kcal/mol) –113.5 –80.6 –92.6 –91.22 [86]

S� (cal/mol/K) 134.4 99.0 105.6 —

OO

O

HO

3-(4-hydroxy-3,5-dimethoxy-phenyl)acryl-aldehyde

�Hf (kcal/mol) –116.0 –102.6 –112.3 —

S�(cal/mol/K) 136.8 123.1 128.1 —

Cyclic and oxygenated species are important intermediates in bio-oil gasification and

comparison indicates that the accuracy of thermochemical data for some oxygenated and

cyclic species in RMG-built models should be improved. Many bio-oil molecules, contain-

ing sugars, cellulose, and lignin fragments, include cyclic ethers and bicyclic oxygenated

groups. Thermodynamic properties of these intermediates are the controlling parameters

in bio-oil gasification modeling and can a↵ect the overall rates of subsequent reactions

leading to formation of products such as CO2 and H2O. Furthermore, ring corrections to

account the ring strain are required for cyclic species since group additivity approach is

not able to predict the thermochemistry of the cyclic molecules accurately enough. Ring

corrections, once obtained by subtracting the experimental value from group additivity

value, allow estimation of the thermochemical properties for cyclic species, but the prob-

lem is only very few ring corrections are available for bio-oil molecules. Using quantum

39

mechanics calculations instead of the group additivity approach to calculate the thermo-

chemistry for cyclic and oxygenated species improved the model. Nevertheless, since there

are remarkable discrepancies in thermodynamic properties of the heterocyclic compounds

in literature, still additional e↵orts are needed to improve estimations and identify other

factors such as ring strain and resonance e↵ects in these species.

1.4.6 Missing Pathways in RMG Generated Mechanisms

As it’s already discussed in Section 1.2.2, there are several detailed kinetic models available

for primary decomposition reactions of cellulose, hemicellulose, and lignin. Comparison

between the bio-oil mechanisms generated by RMG and Zahng et al. [3], Section 1.2.2.1,

decomposition pathways of cellulose reveals that RMG missed one-step levoglucosan C-

O bond breaking decomposition pathways. Furthermore, Carstensen and Anthony [36]

developed a detailed kinetic model for biomass pyrolysis in the gas phase. They performed

electronic structure and transition state calculations to determine the rate constants of

primary decomposition reactions of major biomass components. Comparison between the

bio-oil mechanisms generated by RMG and the Carstensen and Anthony [36] model shows

that RMG missed some decomposition pathways.

Another comparison between RMG-built models for bio-oil gasification and proposed

reaction mechanism for lignin thermal decomposition from the work of Beste et al. [4],

Section 1.2.2.2, shows that RMG-built models missed Phenethyl Phenyl Ether thermal

decomposition through the concerted reactions.

Furthermore, from the comparison with Huang et al. [8] proposed model for hemicel-

lulose thermal decomposition reaction channels, Section 1.2.2.3, RMG missed Xylose pri-

mary ring-opening reaction through the tautomerization and corresponding reaction fam-

ily. Table VII shows some of these reaction pathways missing from the RMG-generated

mechanisms for bio-oil gasification with associated reaction families and references.

40

Table VII: Some missed reactions in RMG for bio-oil primary thermal decomposition.

Missed reaction Associated reaction family and reference

OO

OH

OH

OH

OHO

OH

OH

OHTetrahydro-2H-pyran-3,4,5-triolLevoglucosan

H

H

Tautomerization ring-opening [3]

OO

OH

OH

OH

H

HLevoglucosan

OO

OH

hydroxylmethyl-furfural

HO

HWater

+ 2Celloluse decomposition [36]

OHO

OH

2,3-dihydroxy-2-propenal

+ HO OH1-propene-1,3-diol

O

OH

OH

HO

OH

2-(hydroxymethyl)-3,4-dihydro-2H-pyran-3,4,5-triol

Retro Diels-Alder reaction [36]

OH

OH

HObuta-1,3-diene-1,2,4-triol

+ OOH

2-hydroxyethanal

O OH

OHHO

OH

6-(hydroxymethyl)-5,6-dihydro-2H-pyran-2,3,5-triol

Retro Diels-Alder reactions [36]

O

OH

OH

OH

OH

O OH

OH

OH

HO

Xylose 2,3,4,5-tetrahydroxypentanal

Tautomerization ring-opening [8]

O phenethyl phenyl ether

OH

phenol

+

vinylbenzene

1,3- sigmatropic H shift reaction [4]

O phenethyl phenyl ether

+

vinylbenzene

O

cyclohexa-2,4-dien-1-one

1,5- sigmatropic H shift reaction [4]

RMG generates kinetic models by predicting reactions according to a set of reaction

families, which each contain a recipe and a set of rules to estimate the kinetics. When

pathways are missing, either the template for an existing reaction family needs to be

made more general, or a new reaction family must be created. As an example of the

41

former, the reaction of phenol and vinylbenzene (reaction 6 in table VII) should match

RMG’s existing “1,3 Insertion ROR” reaction family, if the template were general enough

to allow aromatic alcohols to react instead of just aliphatic alcohols. This change has now

been implemented and the most recent versions of RMG can predict this reaction. The

other cases will require new reaction families to be created.

Kinetic models generated by RMG can be significantly improved by adding missing

reaction families into the kinetics database, and ensuring they have a su�cient number

of accurate rate rules. Adding new reaction families starts with identifying the reaction

recipe to define how the reacting species interact with each other, then proceeds with

specifying rules for the reaction rates. Since the number of reactions in each reaction

family is massive, and applying high-level electronic structure calculations for all of them

is not feasible, rate calculations can be performed for a smaller set of reactants belonging

to the particular reaction class and, if transferable, applied to the whole reaction class.

The first important step, undertaken here, is to identify the missing pathways. Calculation

of the rates and full specification of the new reaction family rules is dissuaded in Chapter

2.

1.5 Summary

This study made significant contributions toward automatically generating detailed ki-

netics models for bio-oil gasification using Reaction Mechanism Generator (RMG). Sim-

ulations suggested that there are not significant di↵erences between kinetic models from

RMG-Py and RMG-Java, and that inclusion of pressure dependent reactions doesn’t make

a remarkable di↵erence in these conditions.

The importance of having large and complete models is demonstrated by comparing

a series of incomplete models at di↵erent sizes: they are significantly di↵erent from each

other and the larger kinetic models have higher syngas conversion.

42

Unfortunately this poses problems for the current single-threaded implementation of

RMG, which frequently runs out of memory when simulating mixtures of large complex

molecules. One option would be to use shared-memory computers with very large amounts

of RAM. An alternative would be to restructure the RMG algorithm so that the entire

‘edge’ need not be held in memory at once, and ideally to allow a mechanism generation

job to run on several networked computers simultaneously; if communication requirements

were minimized then this parallelization would also o↵er run-time improvements.

For the purpose of validating kinetic models, RMG generated models are compared

with two experiments in low and high temperature range and comparison shows that there

are some disagreements between experiments and RMG generated models; however, there

are also discrepancies between experiments. Zhang argued the large amount of CO2 in

their experiment was mainly because the bio-oil contained a lot of organic carboxylic

acids from which carboxyl decomposition was a main source of CO2, but they didn’t

specify their bio-oil feedstock composition. However, rebuilding RMG models with very

high carboxylic acid content still doesn’t significantly improve the model predictions for

CO2. Comparison with experimental data is further hampered by the limitation that

both experiments reported gas compositions as only the relative ratios of four component

mole fractions. Absolute concentrations would enable a more rigorous comparison, and a

significant number of other gaseous products should be considered.

Comparison of RMG’s thermochemistry for some species with literature shows that

thermochemistry estimation of some bio-oil cyclic and oxygenated species is currently

erroneous when using a group additivity approach without su�cient ring corrections.

However, using on-the-fly quantum mechanics (QM) calculations for estimating thermo-

dynamic parameters shows remarkable improvement for some species thermochemistry.

Discrepancies between literature values show that some of these heterocyclic compounds

would merit further study.

Finally, some reaction pathways in bio-oil gasification were found to be missing from

43

RMG, so new reaction families need to be added to RMG’s kinetic database with asso-

ciated data calculated, estimated, or taken from literature, to generate more predictive

mechanisms.

The largest model we could build using RMG had not converged with respect to

model size, so a full comparison will require improvements to the memory management

and increased computing power. The complicated chemistry of oxygenated and cyclic

reactants in bio-oil, and having only few models and experiments available for these

systems, makes the modeling task more challenging. Despite these di�culties, there is

enough overlap between RMG-built models and experimental and modeling e↵orts to

encourage the use of RMG to build predictive kinetic models for bio-oil gasification.

44

1.6 Recommendations for future work

This thesis has made significant contributions toward building predictive and reliable

detailed kinetic models for bio-oil gasification. Nevertheless, further kinetic analysis and

experimental activities are required to fully understand the kinetics of the bio-oil thermal

conversion. Three major challenges were identified in RMG while building detailed kinetic

models for bio-oil gasification and particular attention should be given to improve the

understanding of these challenges. Identified challenges in building detailed kinetic models

for bio-oil gasification using RMG for future work are addressed in this section.

1.6.1 Improve RMG thermochemistry estimation

Thermochemistry of bio-oil’s cyclic and oxygenated species are not estimated accurately

enough in RMG. Quantum chemistry calculations can be used for thermochemistry pre-

dictions instead of group additivity approach. The current version of RMG-Py uses

on-the-fly quantum calculations at semi-empirical level of theory such as PM7 to estimate

the thermochemistry of cyclic and oxygenated molecules. However, as the calculated en-

thalpy of species from semi-empirical calculations had an error greater than 10 kcal/mol,

high level ab-initio calculations, i.e at CBS-QB3, should be performed.

Furthermore, another approach to overcome this limitation, can be keep updating

RMG’s thermodynamic libraries with newly published or calculated data and reading

associated parameters from libraries during mechanism generation.

Error canceling reactions such as isodesmic approach or more accurate approaches

such as homodesmotic and hyperhomodesmotic also should be implemented in RMG to

provide reliable thermodynamic estimates for biofuel species.

45

1.6.2 Add more reaction families to the RMG database

As highlighted in the Chapter, RMG missed some primary decomposition reaction path-

ways of bio-oil major constituents. New reaction families need to be added to RMGs

kinetic database with associated kinetic data taken either from published literature or

direct quantum chemistry calculations. Chapter 2 presents a framework for updating

RMG’s kinetic database with two-missing reaction families in bio-oil gasification and au-

tomatic estimation of associated rate coe�cients using reaction rate rules approach.

1.6.3 Improve memory management in RMG

As mentioned, no complete mechanisms are available for bio-oil gasification modeling

due to RMGs memory constraints. To overcome this limitation, parallelizing of RMG

algorithm will help to improve the software memory management. For e�ciently paral-

lelization, tasks that are independent from each other in RMG’s algorithm and require

little communication between processes should be identified first.For example, the calcula-

tion of species thermochemistry is entirely independent job and could be done in parallel,

but parallelizing thermochemistry calculations alone doesn’t save lot of time and memory

in RMG-Py. Furthermore, increasing computing power by using larger shared memory

clusters could always be a reliable way for better memory management

1.7 Supporting material

The largest mechanism for bio-oil gasification generated in RMG-Java is provided in

Appendix A, including Chemkin, transport, and species dictionary files.

46

Chapter 2

Rate calculation Rules for

Automated Generation of Detailed

Kinetic Models for Heterocyclic

Compounds

2.1 Introduction

Bio-oil composition is mostly carbon, oxygen, and hydrogen. However, thermal conversion

of bio-oil is very sensitive to the fuel chemistry, and sometimes too complex to model by

hand, especially for heavy cyclic oxygenated molecules. In order to generate complete

detailed models, an extensive set of reaction classes, which would define how fuel species

can react with each other, should be implemented in mechanism generators. In chapter 1,

Reaction Mechanism Generator (RMG), an open-source software, has been used to build

detailed kinetic models for bio-oil gasification.

In order to propose a comprehensive mechanism, it is important to have all reaction

classes for bio-oil thermal decomposition, and the major challenge is the presence of

47

wide range of cyclic oxygenated species in the model. In particular, more attention

should be paid in looking at specific reaction classes for decomposition of levogucosan,

xylopyronase, and lignin that are crucial steps during bio-oil gasification. In chapter 1, it’s

been investigated that some specific reactions classes for bio-oil gasification are missing

in RMG-built models for bio-oil gasification. Two of these missed reaction classes are

primary ring-opening isomerization reactions that can take place through direct C-C or

C-O bond breaking and H-migration reactions at the same time. Products from C-O

bond breaking reactions are mostly H2O and CO2 that are the main gaseous products

of bio-oil gasification, and would have significant impact on model prediction. However,

bond dissociation energies are determining either C-C or C-O bond breaking is more

feasible. RMGs kinetics database now updated with reaction recipes for these two new

reaction families. Furthermore, rules to predict Arrhenius rate parameters for the new

reaction classes were specified. However, the number of possible reactions in each reaction

family is massive, and applying high-level electronic structure calculations for each would

be prohibitively expensive. Instead, rate calculations were performed for a smaller set

of reactants belonging to the particular reaction class, then the rules of the di↵erent

functional groups were deliberated, and group-based rate rules were derived to estimate

Arrhenius parameters for any reaction in the new reaction classes.

To provide more realistic detailed kinetic model for syngas production from bio-oil gasi-

fication, RMG-built kinetic models have been simulated with Cantera in zero-dimensional

batch reactor assuming constant volume and adiabatic condition, and simulation results

were compared with literature. There are some significant di↵erences in simulation re-

sults between RMG-built models before and after updating the database with new reaction

families, specifically in CO and CO2 predictions. Discrepancies in the models show the

important role of specific reaction families when studying biofuels thermal conversion,

motivating further studies in complexities like the kinetic of heterocyclic molecules.

This chapter addresses all taken steps in updating RMG’s kinetic database with two

48

new reaction families and ab initio calculation details to extract reaction rate rules for

new families.

2.2 Critical literature review

One of the major di�culties in the detailed kinetic modeling of biofuels is defining system

composition. Biomass composition as cellulose, hemicellulose and lignin, can not describe

the system well, as constituents are not well-defined molecules. One possible solution is to

used a set of model compounds for each biomass constituent. To generate complete and

reliable detailed kinetic models for biomass model compounds, the type of reaction classes

that can be used for such modeling should be specified as well. However, both cyclic and

acyclic compounds are presented in the biomass composition and each class of compounds

need their own specific reaction families. This section of thesis briefly addresses previous

studies on biofuels both specific acyclic and cyclic reaction families and missing ones in

RMG’s kinetic database.

2.2.1 Specific reaction classes for acyclic components of biofuels

Generally, there are three main types of acyclic saturated molecules in biofuels [9]: ethers

[87], alcohols [88] and methyl esters [89]. Molecule’s Bond Dissociation Energies (BDE)

can determine which reaction channels are most feasible in the primary thermal decom-

position of the acyclic molecules. Tran et al. [9] calculated the Bond Dissociation Energy

(BDE) in acyclic oxygenated molecules and concluded that the presence of the oxygen

atom in the molecule makes the BDE di↵erent from hydrocarbon molecules, illustated in

Figure 2.1.

49

An example of BDE in an ester molecule:

An example of BDE in an ether molecule: An example of BDE in an alcohol molecule:

Figure 2.1: Calculated bond dissociation energies (in kcal/mol) in ester,ether, and alcohol molecules by Tran et al. [9].

Ethers, alcohols and ethyl esters can go through types of reaction classes such as

unimolecular initiations, bimolecular initiations, and H-abstractions, decomposition of

radicals by �-scission and intramolecular isomerizations.

2.2.1.1 Unimolecular initiations

Unimolecular initiation reaction involves the unimolecular decomposition of an energized

reactant molecule into the radical products and is the first step of the chain initiation

mechanism. The activation energy of the primary initiation reactions depend on the

strength and BDE of the C-C, C-O bonds, and also the position of the carbon atom

as primary, secondary, and tertiary. However, the reverse reaction of the unimolecular

decomposition is the radical recombination and the rate of the unimolecular initiation can

be calculated from the reverse rate by having the thermochemical data [90, 91]. Moreover,

the activation energies of radical recombination reactions are set to be zero as barrier-less

reactions and the modified Arrhenius pre-exponential factors (A) can be estimated from

an improved collision theory [91]. RMG’s kinetic database includes these unimolecular

initiation steps for acyclic molecules in biofuels modeling. As an example, Figure 2.2

illustrates the initiation reaction rate of the butanol and its reverse rate estimated in

RMG.

50

k(T) (s-1) = 5.4✕1021 ✕T-1.4 ✕ exp( - 374.7( kJ/mol) / RT )

k(T) (m3)/(mol✕s) = 1.15✕107

Radical-Recombination:(reverse reaction)

Unimolecular-initiation:(forward reaction)

Barrier less reaction rate from collision theory:

Reaction rate from reverse rate and thermochemistry properties:

Figure 2.2: Rate of the initiation and radical recombination reactionof butanol in RMG [10].

2.2.1.2 Bimolecular initiations and H-abstractions

Bimolecular initiation reactions such as H-abstraction involve the collision of the two

energized molecules and are the most common reaction classes in the fuels thermal de-

composition. The general reaction template of H-abstraction reaction family is illustrated

in Figure 2.3.

1R 2H 3R 2H 3R1R+ +

Figure 2.3: General reaction template of H-abstraction reaction family.

For hydrocarbons with no heteroatoms, the rate constants of bimolecular reactions

depend on the type of alkyl H-atoms which can be abstracted: primary –CH3, secondary

–CH2, or tertiary –CH [9]. However, the abstraction of H atom from a primary carbon is

the most di�cult one due to the high BDE and abstracting the H from a tertiary one is the

easiest. In the case of oxygenated molecules, the BDEs are di↵erent from hydrocarbons

and it’s been observed that the C-H bonds next to the oxygen atoms are weaker [9]

(Figure 2.1). From previous studies for alkanes [92] and experimentally reported values

[93], the Arrhenius pre-exponential factors (A) for H-abstraction are set to A = 7.0 ⇥1012

(cm3/mol⇥s) per abstractable H atom and the barrier height to the enthalpy of reaction

[94]. For ethers, the barrier for the H-abstraction from a carbon atom in the ↵-position of

the oxygen atom reduced about 4 kcal/mol in comparison to the case of alkanes, proposed

by Buda et al. [94].

51

Moreover, for H-abstraction from ↵-position carbon of the alcohols, the reaction rate

can be expressed as an Evans-Polanyi type correlation [95]. The Evans-Polanyi correla-

tions describes the relationship between barrier height of the reaction (E) and enthalpy

of the reaction �H, in which for a similar reactions belong to a particular reaction family

E is proportional to �H:

E = Eref � f(�Href ��H) (2.1)

Thus:

k(T ) = nHATn exp(�Eref � f(�Href ��H)

RT) (2.2)

where nH is the number of abstractable H-atoms and R is the gas constant; A, n,

and E0 are the Arrhenius rate expression parameters; ’ref’ refers to the reaction in the

set chosen as a reference. For H-abstraction reaction family Dean and Bozzelli [95] chose

ethane as the reference molecule and �Href is the enthalpy of the reaction by the radical

from ethane. �H is the enthalpy of the reaction by the radical from the reacting molecule;

f is a correlation factor and for each radical the f values are given by Dean and Bozzelli

[95]. Luo in his handbook [96] reported the BDE of the O-H bond in alcohols as 102

and 106 kcal/mol and the value is close to the C-H bond in an alkylic primary H-atom.

Thus several research groups such as [94] used similar reaction rate parameters for H-

abstraction from alcohol function to those for the abstraction from an alkylic primary

H-atom.

RMG’s kinetic database is rich in kinetic data for alcohols, esters, and ethers H-

abstraction reactions estimated from either published literature or rate rules.

2.2.1.3 Radicals decomposition by �-scission

�-scission is an important reaction to form reactive free radicals in fuels thermal decom-

position processes. The general template of the reaction is illustrated in Figure 2.4.

52

1R 3R2R 2R 1R 3R+

Figure 2.4: The general template of the �-scission reaction and forma-tion of free radical upon this reaction class.

Glaude et al. [87] proposed some reaction rate parameters and barrier height values

for the ethers. Later on, Glaude et al [89] in a new modeling study, obtained some

reaction rate parameters for esters from quantum chemical calculations in CBS-QB3 level

of theory. Table I summerizes some example of the barrier height of �-scission reactions

for oxygenated species. Buda et al. [94] proposed that the barrier heights for C-C bond

breaking in saturated hydrocarbons are usually between 26 and 31 kcal/mol, however,

values in Table I shows that how presence of the oxygen can a↵ect the reaction barrier.

Table I: Example of �-scission reaction’s barrier heights for oxygenated compounds.

Reaction Barrier height (kcal/mol) Reference

5.1 CBS-QB3[9]

49.0 DFT [97]

15.0 From reverse reaction [59]

15.6 DFT[97]

2.2.1.4 Intramolecular isomerizations

In this type of isomerization reactions an H atom or OH function can transfer in the

molecule through a cyclic transition state. The general reaction template for both reaction

families is illustrated in Figure 2.5.

53

3H 2R 1R 2R 1R 3H

1R 2O 3OH 1R 2O3HO

Intra H migration:

Intra OH migration:

Figure 2.5: The general template of intramolecular H and OH migra-tion reaction families and formation of free radical upon these reactionclasses.

The ring strain of the transition state structure can influence the kinetics of these

families. In case of esters, Wiberg et al [98] studied the enthalpies of formation and the

strain energies of monocyclic lactones with 5-14-membered rings via isodesmic reactions.

They concluded that ring strain energies are equal to 9, 11, 11.2, and 12.5 kcal/mol for

lactones and 6.3, 1, 6.4, and, 9.9 kcal/mol for alkyl radicals for 5, 6, 7, and 8 membered

ring, respectively, and the larger ring molecules have smaller strain energies.

From the literature review of biofuels specific acyclic reaction families, it is concluded

that RMG handles kinetics of acyclic compounds well and all reaction families with asso-

ciated data are available for alcohols, esters, and ethers.

2.2.2 Specific reaction classes for cyclic components of biofuels

Recently, many studies have been conducted for modeling the oxidation of cyclic alka-

nes [99–102]. Buda et al. [99] modeled oxidation of the cyclohexane in both low and

medium temperature range (650-1050 K). They developed their model using computer-

aided generation with 513 species and 2446 reactions and did some evaluations for the

kinetics of the cyclic ether. Cavallotti et al. [100] performed ab initio calculations and re-

actor simulations to estimate the kinetics of the oxygen attack to the cyclohexane radical.

They observed that the because ring strain energy the activation energies of cyclic alkanes

slightly increased in comparison with the equivalent data for linear alkanes. Cyclic alka-

nes can go through specific types of reaction classes in thermal decomposition processes,

such as unimolecular initiations, endo/exo tautomerizations, and isomerization of peroxy

radicals. In the following sections, a brief introduction to each reaction family is provided:

54

2.2.2.1 Unimolecular initiations

Unimolecular decomposition of the cyclic compounds leads to the biradical intermediates

formation. Sirjean et al. [11] conducted a theoretical study of the unimolecular decomposi-

tion of cyclobutane, cyclopentane, and cyclohexane in gas phase using quantum chemistry

calculations. They investigated feasible reaction channels for biradical decomposition and

validated their calculations with available experimental data. They proposed that the

main reaction channels in the cyclobutane case are the decomposition to two ethylene

molecules, Figure 2.6 (a), and internal disproportionation of the biradicals producing

1-pentene and 1-hexene in the case of cyclopentene and cyclohexane, Figure 2.6 (b, c),

respectively.

(a)

(c)

(b)

Figure 2.6: Proposed detailed mechanism of (a) ethylene,(b) 1-pentene,and (c) 1-hexene formation by Sirlean et al. [11] from the primary de-composition of the cyclobutane, cyclopentane, and cyclohexane and byconsidering di↵erent conformers of C4, C5, and C6 biradicals, respec-tively.

55

2.2.2.2 Endocyclic and exocyclic ring-opening in cyclic radicals

Sirjean et al.[103] in another study showed that for the cyclic alkyl radicals in the presence

of a lateral alkyl group, ’exo’, and ’endo’ ring opening reactions are another feasible

reaction channels. If the cyclic compound does not have any functional groups, then

any radical created from the parent compound can go through the endo ring openings.

However, in case of exo ring opening reaction, presence of the functional groups on the

parent molecule causes the formation of radicals on the functional group and the double

bond outside the cyclic part, Figure 2.7.

Exo ring opening:

Endo ring opening:

Figure 2.7: Exo and endo ring-opening reactions for Cyclobutylcarbinylradical and Cyclobutyl radical.

From quantum chemistry calculations in CBS-QB3 level of theory, Sirjean et al. [103]

concluded that the in the endo ring-opening reaction there is an increase of the activation

energy as the ⇡ bond is being formed in contrast to the exo ring-opening reaction in which

the ⇡ bond is formed on the side chain.

Detail investigation on the specific reaction classes for cyclic components of biofuels

must be performed, since still not adequate studies are available. In this Chapter of thesis,

one-step endocyclic and exocyclic ring-opening concerted reactions were studied in further

detail for bio-oil oxygenated cyclic compounds and results were compared with two-steps

unimolecular decomposition pathway through diradical intermediates in section 2.4.

56

2.2.3 Reaction rate calculation for biofuel compounds

Recently, theoretical methods and quantum chemistry calculations are remarkably im-

proved for accurate reaction rate calculations [104–106]. At the same time, the increase

of CPU power allows the wide use of computers to deal with the complexity of the chemi-

cal reaction systems and cto alculate the reaction rates fast and accurately enough. These

type of calculations typically use quantum chemistry methods such as Density Functional

Theory, statistical mechanics methods for calculating partition functions, frequencies, op-

timized geometries, etc. and reaction rate theory such as Transition State Theory to

obtain accurate reaction rate estimates. This section of thesis explains the general work

flow to directly calculate modified Arrhenius rate coe�cient parameters for reactions, A,

n, and Ea.

2.2.3.1 Quantum chemistry

Lately, there is a big improvement in quantum chemistry calculations thanks to the de-

velopment of accurate but a↵ordable quantum chemistry methods. Examples of popular

methods include the G family (G1 [107, 108], G2 [109], G2MP2 [110], G3 [111], G3MP2

[112], G3MP2B3 [113], G3B3 [113], G3S [114]), the complete-basis-set family (CBS-Q

[115], CBS-APNO [116], CBS-RAD [117], CBS-QB3 [116]), and hybrid density functional

theory (DFT)/HartreeFock (HF) methods [118]. Furthermore, more expensive methods

that are using more complicated treatment for some orbitals or configurations include

CCSD(T) [119], CAS-PT2 [120], MR-CI [121, 122], and Martins W family [123].

To accurately compute the thermochemical quantities the use of both static and dy-

namic electron correlation e↵ects in the quantum chemistry methods are required [124].

However, the use of these type of methods is very costly and only applicable for small

systems. Instead, composite methods such as CBS can be applied with lower cost for

larger systems. CBS is based on the use of one determinantal wavefunctions and applies

57

an infinitely large basis set by combining energies from lower level theories. The most

accurate CBS method is CBS-APNO (Atomic Pair Natural Orbital) and CBS-QB3 is

about two times less accurate than CBS-APNO but significantly faster. Basic di↵erence

between Gaussian methods such as G1, G2, G2MP2, G3, etc. is that Gaussian increases

accuracy by adding in more empirical terms to correct for known issues with the models

being used, while CBS corrects the energy by trying to extrapolate the basis set to the

infinite basis set [125].

2.2.3.2 Statistical mechanics

In statistical thermodynamics, the state of a molecule is described by the partition func-

tion. The molar partition function, Q, represents the product of the partition functions

of each degree of freedom of the molecule:

Q = Qtrans ⇥Qextrot ⇥Qintrot ⇥Qvib ⇥Qelec ⇥Qsym (2.3)

The electronic partition function, Qelec, only considered when the molecule contains an

odd electron. The standard entropy is related to the molar partition function according

to:

S� = k ln(Q) + k(@ ln(Q)

@ln(T ))V (2.4)

By combining Equation 2.3 and 2.4, standard entropy can be expressed as:

S� = S�trans + S�

extrot + S�introt + S�

vib + S�elec + S�

sym (2.5)

Moreover, the contribution of the molecule’s symmetry in the standard entropy would

be:

58

S� = S�intr �Rln(�) (2.6)

Where � is the symmetry number.

Frequency factors, A factor, for unimolecular and bimolecular reactions can be calcu-

lated from Equation 2.12 when the standard activation entropy, �S�#, of the reaction

is known. �S�# can be calculated from the di↵erence in standard entropy between the

transition state complex, S�ts, and the reactants, S�

reactant:

�S�# = S�ts � ⌃S�

reactants (2.7)

And to consider the symmetry contribution:

�S�# = S�ts � ⌃S�

reactants +Rln(�ts

⇡[�reactant]) (2.8)

Therefore, by combining Equation 2.5 and 2.8, the standard activation entropy would

be:

�S�# = �S�#trans +�S�#

extrot +�S�#introt +�S�#

vib +�S�#elec�

⌃S�(reactants) +Rln(�ts

⇡[�reactant]) (2.9)

The calculation of �S�# in Equation 2.9 will be di↵erent for every specific reaction

family.

2.2.3.3 Transition State Theory

Eyring et al. [126] were the first that presented a quantitative formulation of Transition

State Theory (TST), and they called it activated complex theory in their paper. To date,

59

many research groups started using this theory to apply to practical cases. For example,

Benson [59] discussed the application of the theory to various types of gas-phase reactions

in his book and Cohen [127] used the theory to extrapolate experimental rate constants to

higher temperatures. Based on the transition-state theory, the rate constant of a reaction

can be written as:

k(c) = (kT

h)K#

c (2.10)

Where k(c), is the reaction rate constant, K#c is the equilibrium constant for the

formation of the transition state complex from the reactants, T is the absolute temperature

(K), k is the Boltzmann constant, 1.38 ⇥ 10�23 J/K, and h is the Planck constant, 6.62

⇥ 10�34 J.s. This equation is valid both for unimolecular and bimolecular reactions and

the only di↵erence between both types of reactions is in the equilibrium constant, K#c .

While a reaction is happening, one of the internal vibrations of the activated complex is

converted into the reaction coordinate and the partition function corresponding to this

degree of freedom is removed from the equilibrium constant. Thus, K#c , is a modified

equilibrium constant [128, 129].

Moreover, by combining the the Arrhenius rate expression with the rate constant

expression from TST, equation 2.10, the activation energy, E, and the frequency factor,

A of the reaction cane be expressed as [128]:

E = �H�# + (1��v#)RT (2.11)

A =kT

hexp(1��v#)exp(�(�S�# ��v#Rln(RT )

R) (2.12)

Where �H�# and �S�# are the standard enthalpy and the standard entropy of ac-

tivation. �v# is the change in number of moles in the transition from the reactants to

60

the transition state complex, which is 0 for unimolecular reactions and -1 for bimolecular

reactions.

The calculated standard activation entropy and enthalpy for the transition state com-

plex, can be used in the reaction rate expression via TST:

k(T ) = (T )kBT

hV n�1m exp(��G#

RT) (2.13)

Where, (T ) is the tunneling factor, Vm the molar volume, n the molarity of the

reaction, n=1 for unimolecular, n=2 for bimolecular, and �G# the di↵erence in free

energy between the transition-state geometry and the reactant(s). �G# calculates from

�H# and �S# by the following thermodynamic expression:

�G# = �H# � T�S# ��Hreac + T�Sreac (2.14)

2.2.4 Reaction rate estimation methods

As the number of reactions in each family is massive and applying quantum chemistry

calculation for every reaction is expensive, rate estimation methods can be used instead.

This section briefly highlights some recent-developed estimation methods such as Evans-

Polani correlations or rate calculation rules [106, 130].

2.2.4.1 Linear Free Energy Relationship (LFER)

Linear Free Energy Relationship (LFER) describes the relationship between reactions

rate coe�cient and Gibbs free energy of the reaction. This relationship is expressed in

transition-state theory (TST), Equation 2.13, which in the case of no tunneling factor is:

ln(k(T )) = ln(kref (T ))� �G# ��G#,ref

RT(2.15)

61

The well-know expression of the mentioned equations is as [131] Hammett equation:

ln(k(T )) = ln(kref (T )) + �⇢ (2.16)

where � is the weight of the substituent on the reaction rate as the Hammett parameter

and ⇢ is a reaction class specific constant. Hammett and later Taft [132] listed resonance,

hyperconjugation, induction, and steric e↵ects as stabilizing or destabilizing factors for

transition states.

2.2.4.2 Evans-Polanyi correlation

Another well-known correlation for reaction rate estimation is Evans-Polani [95] relation-

ship and it’s based on the linear correlation between reaction exothermicity and changes

of the barrier height:

�H# = Ea +m�HR (2.17)

Which will give:

Ea = Erefa +m(�HR ��Href

R ) = constant+m�HR (2.18)

The Evans-Polanyi correlation assumes that the pre-exponential A factor of the Arrhe-

nius rate expression and the position of the transition state along the reaction coordinate

are the same for all reactions belonging to a specific reaction family.

2.2.4.3 Reaction Class Transition State Theory (RC-TST)

Truong et al. [133, 134] introduced class transition state theory (RC-TST) for estimations

of reaction rate constants for a large number of reactions in a given class. RC-TST method

is based on the fact that as all the reactions belonging to a specific reaction family, have

62

the same reacting centers, therefore their potential energy surfaces along the reaction

coordinate are very similar and can be extrapolated. This method uses the Evans-Polanyi

relationship to estimate reaction barrier heights and Arrhenius pre-exponential factor by

performing low level of electronic structure calculations such as DFT. In this approach,

contribution of the di↵erent internal modes, symmetry, and tunneling to the partition

functions, can be evaluated separately.

2.2.4.4 Rate calculation rules

Carstensen et al. [130] have shown that the rate parameters of many elementary reactions

belonging to a specific reaction family can be generalized and expressed as rate rules. In

their proposed rate rules approach, the temperature dependence of rate expressions of a

reaction family is expressed in terms of a temperature exponent (n) and a barrier height

(E) that is related to the exothermicity of a reaction by the Evans-Polanyi relationship.

The pre-exponential factor (A) can be determined by averaging rate constants of a test

set reactants. Even though this type of method has been available for long time, but it’s

application is limited as there are not enough rate rule expressions available. One of the

biggest concerns in the rate rules application, is about it’s transferability and how similar

a reaction should be to the reference reaction, or how many rate rules are required to

estimate the kinetics of the whole family.

Most reaction rate rules which originate from literature were covered in the RMG’s

kinetic database. Nevertheless, for some reaction families like exo/endocyclic ring opening

reactions, new rate rules were determined from quantum calculations as explained in

further detail in section 2.4.

63

2.3 Computational Method

As we saw in Chapter 1, Reaction Mechanism Generator (RMG) generates kinetic models

by predicting reactions according to a set of reaction families, which each contain a recipe

and a set of rules to estimate the kinetics. When pathways are missing, either the template

for an existing reaction family needs to be made more general, or a new reaction family

must be created. In Chapter 1, it was shown that RMG’s kinetic database was miss-

ing specific reaction classes for tautomerization ring-opening reactions [135]. Generally,

ring-opening tautomerization reactions occurs in two structural fashions: 1) exocyclic and

2) endocyclic. As shown in Figure 2.8, exocyclic ring-opening reaction happens through

direct R1-R2 bond breaking and H-migration at the same time. During this single-step

isomerization reaction, the cyclic component will go through the unimolecular decompo-

sition to the acyclic component. As an example, primary ring opening reaction of xylose,

a type of sugar in biomass composition, is demonstrated in Figure 2.8.

2R1R 3R2R1R 3R

O

OH

OH

OH

OH

O OH

OH

OH

HO

H H

Figure 2.8: The general template of the exocyclic tautomerization ring-opening reaction family. The example is shown for the primary ring-opening reaction of xylose, a type of sugar from wood.

Endocylic tautomerization, similar to the exocyclic family, can occur through the

direct R2-R3 bond breaking and H-migration reactions inside the ring, as shown in Fig-

ure 2.9.

64

2R1R 3R2R1R 3R H

H

OO

OH

OH

OH

OHO

OH

OH

OH

Figure 2.9: The general template of the endocyclic tautomerizationring-opening reaction family. The example is shown for the endocyclicring-opening reaction of levoglucosan, a derivative of cellulose pyrolysis.

After updating RMG’s kinetics database with reaction recipes for two new reaction

families, rules to predict Arrhenius rate parameters for the given reactions must be spec-

ified as well. RMG’s kinetic database is structured as trees and the hierarchy of the tree

is an important factor in rate rule calculations. To apply the rate rules for new reaction

families, hierarchical trees are constructed based on the two facts; first, the root of the

tree is the most general group in the family. Second, children nodes at the very base of

the tree are the most specific groups and they are di↵erent from each other based on the

di↵erent functional groups around the reactive center and the atom types. When kinetics

are determined for a reaction, the rules will search for the corresponding groups. If an

exact match for an appropriate rule can’t be found in the database, RMG will average

rules with similar groups.

To generalize a specific reaction kinetic parameters to other similar reactions in the

exo/endocyclic ring-opening reaction families, test set reactions on which to perform the

quantum chemistry calculations are constructed based on the three factors: atom type,

ring size, and functional groups (Figure 2.10). Kinetic groups for these reaction fam-

ilies are designed for Carbon, Oxygen, and Nitrogen heteroatoms and four ring sizes,

4-membered, 5-membered, 6-membered, and 7-membered rings, have been chosen to test

the e↵ect of the ring size in the rate calculation rules.

65

Exo ring opening

4-membered ring

5-membered ring

6-membered ring

7-membered ring

O HO

OHOH

OOH

OH

OH

O

OH

OH

OH

OH

O OH

OH

OH

HO

O OH

OH

OHHO

HOO

OH

OH

OH

OH

OH

NH

NH2

O

OH

OH

O OH

OH

H2NHN

NHH2N

H2N

NH

O

OH

OOH

OH

O

O

OH

C

N

O

4-membered ring

5-membered ring

6-membered ring

7-membered ring

4-membered ring

5-membered ring

6-membered ring

7-membered ring

4-membered ring

5-membered ring

6-membered ring

7-membered ring

(a)

Endo ring opening

O

O

HO

OH

OH

OH

OH

OOH

OH

OH

HO

O

OH

OH

OH

OH

O OH

OH

OH

HO

OOH

OH

OH

HOO

O

OH

OH

OH

H

H

O OH

OH

OH

HOO

O

OH

OH

OH

H

H

O

OH

NH

NH

HN

NH

O

O

O

O

NHHN

NH2HN

4-membered ring

5-membered ring

6-membered ring

7-membered ring

C

N

O

4-membered ring

5-membered ring

6-membered ring

7-membered ring

6-membered ring

7-membered fused ring

4-membered ring

5-membered ring

6-membered ring

7-membered ring

6-membered ring

7-membered fused ring

(b)

Figure 2.10: Hierarchical tree for (a) exocyclic and (b) endocyclic ring-opening reaction families.

66

All the quantum chemistry calculations were performed in Gaussian09 [62] and consist

of three major steps. First, optimized geometries and frequencies for reactant and product

species are calculated by using density function theory methods at B3LYP [136] level of

theory with the 6-31G(d) basis set. Then the geometries obtained in the first step are used

to find statistical molecular properties of each species in the reaction using CBS-QB3 [116]

level of theory. Finally, transition state theory has been used to determine the Arrhenius

rate parameters using calculated statistical thermodynamic properties in the CanTherm

[137] package. Transition state searches for the four-membered rings single-step tautomer-

ization reactions are skipped in both endocyclic and exocyclic reaction families due to the

high ring strain energies. Moreover, it’s been observed that the boat conformations work

for the transition states searches in these families after trying di↵erent conformers. For

the vibrational partition function, the harmonic oscillator approximation has been as-

sumed and hindered rotor calculations are skipped due to the floppy transition states.

All the obtained frequencies from CBS-QB3 are scaled by a factor of 0.99 [138]. In spite

of this, Arrhenius pre-exponential factor (A) is influenced by any errors in the frequency

calculations more than the reaction barrier height (E), and as the di↵erences in reaction

rate coe�cients are mostly associated with the barrier height (E) [139], the harmonic os-

cillator approximation should be reasonably valid for these calculations. Finally, Intrinsic

Reaction Coordinate (IRC) [140] calculations have been performed to track the minimum

energy path from a transition state to the corresponding reactant and product species.

2.4 Results and Discussions

Arrhenius rate parameters from CBS-QB3 calculations for the exocyclic reactions in the

test set are presented in Table II. Also, the calculated rate coe�cients within the temper-

ature range of 300-2000 K for the exocyclic ring-opening reactions are plotted in Figure

2.11 and 2.12.

67

Table II: Arrhenius rate constant parameters for exocyclic ring-openingreactions from CBS-QB3 calculations.

Reaction A (S�1) n E (kJ/mol)

9.08⇥ 1010 0.97 106.0

1739.33 3.52 381.54

1.71⇥ 109 1.67 483.07

HN

H2N 8.13⇥ 109 1.12 335.97

H2N

NH

2.28⇥ 1011 1.03 300.095

NH

NH2 1.11⇥ 1010 0.95 314.09

OOH 6.29⇥ 109 0.91 289.0

OH

O

1.23⇥ 1010 1.01 351.92

O

OH 1.19⇥ 1011 0.02 360.29

O HO

OHOH

OOH

OH

OH

6.77⇥ 1014 -0.41 192.58

O

OH

OH

OH

OH

O OH

OH

OH

HO2.00⇥ 108 1.24 151.47

O OH

OH

OHHO

HOO

OH

OH

OH

OH

OH

6.11⇥ 1013 0.73 176.24

68

-100

-80

-60

-40

-20

0

20

0 0.5 1 1.5 2 2.5 3 3.5

log

(k) (

m3/

mol

.s)

1000 K / T

(a)

-100

-80

-60

-40

-20

0

20

0 0.5 1 1.5 2 2.5 3 3.5

log

(k) (

m3/

mol

.s)

1000 K / T

OOH

OH

O

O

OH

(b)

Figure 2.11: High pressure limit rate coe�cients within the temperature range of 300-2000 K forexocyclic ring opening test set reactions to investigate the rate calculation rules. (a) results forthe five, six, and seven membered carbon rings (b) results for the five, six, and seven memberedoxygen rings.

69

-100

-80

-60

-40

-20

0

20

0 0.5 1 1.5 2 2.5 3 3.5

log

(k) (

m3/

mol

.s)

1000 K / T

NH

NH2

H2N

NH

NHH2N

(a)

O HO

OHOH

OOH

OH

OH

O

OH

OH

OH

OH

O OH

OH

OH

HO

O OH

OH

OHHO

HOO

OH

OH

OH

OH

OH

-100

-80

-60

-40

-20

0

20

0 0.5 1 1.5 2 2.5 3 3.5

log

(k) (

m3/

mol

.s)

1000 K / T

(b)

Figure 2.12: High pressure limit rate coe�cients within the temperature range of 300-2000 Kfor exocyclic ring opening test set reactions to investigate the rate calculation rules. (a) resultsfor the five, six, and seven membered nitrogen rings (b) results for the five, six, and sevenmembered oxygen rings with additional ’OH’ groups

Figure 2.13 shows the comparison between the rate coe�cients of the five, six, and

seven-membered rings across the carbon, oxygen, and nitrogen heteroatoms at T= 1100 K.

70

!10$

!5$

0$

5$

10$

C$ N$ O$

log(k)'at'T

=1100K

'(m3/mol.s)'

R5$

R6$

R7$

Figure 2.13: Rate coe�cient of the four, six, and seven membered ringsacross the C, N, and O heteroatoms in exocyclic test set reaction at T= 1100 K.

Results show that the rate calculation rules for the test set reactions including nitrogen

and oxygen heteroatoms in five, six, and seven-membered rings are promising , Figures

2.11 (b) and 2.12 (a). It should be taken into account that rings with nitrogen and oxygen

heteroatoms are simple rings including no additional functional groups, and calculations

show that the rate calculation rules are transferable for additional similar reactions. In the

most cases, the oxygenated-ring reactions, occurring in the biomass thermal conversion,

have additional ’OH’ functional groups. To investigate the e↵ect of the ’OH’ functional

groups, the rate rule calculations are extended for the five, six and seven membered rings

with oxygen as the heteroatom. As illustrated in 2.12 (b) rate calculation rules can still

be applied to this family for the reactions with additional ’OH’ functional groups.

Nevertheless, the rate calculation results for carbon rings, shown in Figures 2.11 and

2.13, are di↵erent from nitrogen and oxygen rings and five membered carbon ring is not

well-grouped with six and seven membered rings. In this test set, reaction rates are dif-

ferent based on the ring size particularly at lower temperatures; the rate constants for

the six and seven membered rings are lower than the five-membered ring. Part of the

71

reason can be related to the conformation of the methylcyclopentane. Flat confirma-

tion of cyclopentane with planar bond angle of 108�, has very high torsional strain. The

planer cyclopentane can, however, pucker in half-chair or envelope conformers with less

torsional strain [141]. Furthermore, cyclopentane conformation is sensitive to the nature

of functional groups, hence, di↵erent substituents, such as methyl group in the methylcy-

clopentane, can significantly a↵ect puckering of the ring. In spite of the di↵erent behavior

of the five-membered carbon ring in the current calculations, for the purpose of auto-

matic detailed mechanism generation, which needs a large number of rate parameters to

be calculated quickly on the fly, rate rules can stay reasonably valid. Meanwhile, kinetic

analysis tools such as a sensitivity analysis or flux analysis can be used to identify the

important reaction channels in the detailed kinetic model and from there, further atten-

tion can be paid to those particular reactions by applying high-level quantum chemistry

calculations.

Sirjean and Klippenstein [11, 142] in their cyclohexane decomposition study have

shown that the isomerization of cyclohexane to 1-hexene through a single step endocylic

ring-opening reaction, avoiding formation of the diradical intermediate, is not favorable

because of its lower entropy of activation even though the single-step reaction has the

lower barrier. To investigate the rate rule application for endocyclic ring-opening reaction

family, bicyclo-octane single-step ring opening reaction rate was compared versus the two-

steps reaction pathways.

72

TS1

TS2TS3

-21 kJ/mol

-0.8 kJ/mol

261 kJ/mol

451 kJ/mol

240 kJ/mol

273 kJ/mol

Single step:

CH••H2C

Two steps:

Figure 2.14: Potential energy diagram for bicyclo-octane isomerizationto 3-ethylcyclohexene calculated at the CBS-QB3 level through singlestep-endo ring-opening vs. two-steps pathway with a diradical interme-diate.

Calculation shows that the single-step reaction is more favorable and has a lower

barrier height compared with the two-step reaction channel as shown in Figure 2.14.

Generalizing a conclusion for the entire reaction family from this single evidence is di�cult

and requires further investigation. Nevertheless, for the automatic mechanism generation,

which needs a large number of rate coe�cients to be calculated reasonably cheaply, the

single-step ring-opening as the favorable reaction channel can remain relevant.

Rate constant calculation results within the temperature range of 300-2000 K for the

single-step endocyclic ring opening reactions are plotted in Figures 2.15, 2.16 , and 2.17

73

and also rate parameters are presented in Table III. Further, the comparison between

the reaction rate coe�cients of the five, six, and seven-membered ring containing carbon,

oxygen, and nitrogen heteroatoms at T=1000 K is illustrated in Figure 2.18.

Table III: Arrhenius rate constant parameters for endocyclic ring-opening reactions from CBS-QB3 calculations.

Reaction A (S�1) n E (kJ/mol)

1135 4.65 442.01

188727 3.21 441.09

24055.2 3.42 411.63

NH

NH

5.62⇥108 2.30 486.85

HN

NH

6.05⇥ 1010 1.31 494.00

NHHN 5.41⇥1010 1.20 470.52

O

O1.35⇥107 2.80 399.99

O

O

6.21⇥1010 1.40 495.61

O

O 2.05⇥109 2.24 466.71

HO

OH

OH

OH

OH

OOH

OH

OH

HO 4.21⇥1010 1.27 389.95

O

OH

OH

OH

OH

O OH

OH

OH

HO7.35⇥108 2.07 468.60

OOH

OH

OH

HOO

O

OH

OH

OH

H

H

4.61⇥1010 0.97 249.00

O OH

OH

OH

HOO

O

OH

OH

OH

H

H

6.19⇥108 2.22 298.70

74

-150

-120

-90

-60

-30

0

30

0" 0.5" 1" 1.5" 2" 2.5" 3" 3.5"

log$(k)$(m3/mol.s)$

1000$K$/$T$

(a)

O

O

O

O

O

O

-150

-120

-90

-60

-30

0

30

0" 0.5" 1" 1.5" 2" 2.5" 3" 3.5"

log$(k)$(m3/mol.s)$

1000$K$/$T$

(b)

Figure 2.15: High pressure limit rate coe�cients within the temperature range of 300-2000 K forendocyclic ring opening test set reactions to investigate the rate calculation rules. (a) results forthe five, six, and seven membered carbon rings (b) results for the five, six, and seven memberedoxygen rings.

75

NH

NH

HN

NH

NHHN

-150

-120

-90

-60

-30

0

30

0" 0.5" 1" 1.5" 2" 2.5" 3" 3.5"

log$(k)$(m3/mol.s)$

1000$K$/$T$

(a)

-150

-120

-90

-60

-30

0

30

0" 0.5" 1" 1.5" 2" 2.5" 3" 3.5"

log$(k)$(m3/mol.s)$

1000$K$/$T$

O OH

OH

OH

HOO

O

OH

OH

OH

H

H

OOH

OH

OH

HOO

O

OH

OH

OH

H

H

(b)

Figure 2.16: High pressure limit rate coe�cients within the temperature range of 300-2000 K for endocyclic ring opening test set reactions to investigate the rate calculationrules. (a) results for the five, six, and seven membered nitrogen rings (b) results for thesix membered rings with additional ’OH’ functional groups.

76

-150

-120

-90

-60

-30

0

30

0" 0.5" 1" 1.5" 2" 2.5" 3" 3.5"

log$(k)$(m3/mol.s)$

1000$K$/$T$

O

OH

OH

OH

OH

O OH

OH

OH

HO

HO

OH

OH

OH

OH

OOH

OH

OH

HO

Figure 2.17: High pressure limit rate coe�cients within the temperature range of 300-2000 Kfor endocyclic ring opening test set reactions to investigate the rate calculation rules for theseven membered fused rings.

!20$

!15$

!10$

!5$

0$

C$ N$ O$

log(k)'at'T

=1100K

'(m3/mol.s)'

R5$

R6$

R7$

Figure 2.18: Rate coe�cient of the four, six, and seven membered ringsacross the C, N, and O heteroatoms in endocyclic test set reaction atT= 1100 K.

Results show that the rate coe�cients for five, six, and seven membered carbon and

77

oxygen and nitrogen rings are grouped well together and rate rules are transferable in

this family to similar reactions for quick and accurate rate estimation Figures 2.15 and

2.16. The calculations are extended for the six-membered oxygenated ring with additional

’OH’ groups to study the impact of the functional groups, and as shown in Figure 2.16

(b), the rate rules application is evenly valid in these cases as well. Primary fused ring-

opening of levoglucosan, as an important cellulose derivative, through endocyclic single

step tautomerization reaction, appears as an important step in studying biomass thermal

conversion. Rate constants for levoglucosan’s initiation steps, have been calculated to

investigate the rate rules relevance, Figure 2.17. Though, there are slight di↵erences in

the reaction rates at lower temperatures, still the rates can be represented from rate rules

for similar reactions in the family for quick and cheap on the fly automatic estimation.

2.4.1 Case study: E↵ect of new reaction families on Bio-oil gasi-

fication

As described in detail in chapter 1, Bio-oil composition is defined in terms of three refer-

ence elements: carbon, oxygen, and hydrogen and its thermal conversion is very sensitive

to the fuel chemistry. Depending on the initial source of the biomass, bio-oil contains

di↵erent amounts of organic acids, ketones, furans, levoglucosan, and other phenolic and

cyclic oxygenated molecules [27–31]. Gasification of bio-oil at the high temperature and

pressure is a desirable process for syngas production. A detailed kinetic model for bio-oil

gasification at high temperature was previously built in RMG [135]. To provide more

realistic detailed kinetic model for syngas production from bio-oil gasification, RMG-built

kinetic models have been simulated with Cantera [66] in a zero-dimensional batch reac-

tor, assuming constant volume and adiabatic conditions, and simulated synagas species

concentrations were compared with the literature [1, 2].

As shown in Figure 2.19 (a, b, c), the previously RMG-generated model couldn’t pre-

78

dict CO and CO2 formation properly. After performing flux analysis, it has been identified

that RMG-built model was missing ring-opening initiation reactions [135]. Since products

from primary ring opening reactions through CO bond breaking have major contributors

to CO and CO2 formation, the bio-oil gasification mechanism has been updated after

adding these new reaction classes and associated kinetic parameters from rate calculation

rules. There are some significant di↵erences in simulation results between the RMG-built

models before and after updating RMG’s kinetic database shown in Figure 2.19 (c, d),

which demonstrates the importance of these reaction families and their kinetic features

when studying the thermal conversion of biofuels.

79

0

0.25

0.50

0.75

1.00

600 700 800 900 1000 1100 1200 1300 1400

RMG model after updating reaction classes

Syng

as Fr

actio

n

Temperature (C)

CO2

CO

H2

CH4

0

0.25

0.50

0.75

1.00

600 700 800 900 1000

(a) Experiment ISy

ngas

Frac

tion

Temperature (C)

CO2

CO

H2

CH4

0

0.25

0.50

0.75

1.00

600 700 800 900 1000 1100 1200 1300 1400

RMG model

Syng

as Fr

actio

n

Temperature (C)

CO2

CO

H2

CH4

1000 1100 1200 1300 1400

(b) Experiment II

(c)

(d)

Figure 2.19: Distribution between four major gas components as afunction of temperature, (a) from experimental work by Zhang et al.[1]at 100�C intervals from 600 to 1000 �C, (b) from Chhili et al.[2] at100�C intervals from 1000 to 1400 �C , (c) RMG-built model at 100�Cintervals from 600 to 1400 �C before updating RMG’s kinetic database(d) after updating RMG’s kinetic database with new reaction families.

2.5 Summary

Developing predictive detailed chemical models for heterocyclic compounds, that are im-

portant intermediates in di↵erent complex chemical systems, is challenging. To propose

80

a comprehensive mechanism, more attention should be paid in looking at specific reac-

tion classes that are specific to heterocyclic species and their associated rate parameters.

In the present study, a mechanistic study of the tautomerization reactions as important

initiation ring-opening steps in heterocyclic molecules, is presented.

Reaction Mechanism Generator (RMG) is used to build detailed kinetic models for

chemical systems including large number of heterocyclic compounds. To test the e↵ect

of the new families after updating the RMG’s database with two new reaction families,

a previously generated bio-oil gasification model has been re-built. After adding reaction

recipes for two families, electronic structure methods have been used to study the kinetics

and relevance of the rate rules. As the rate estimates are based on the local structure

of the reacting sites, the e↵ects of the ring size, atom type and functional groups in the

rate calculation rules have been investigated for the two new reaction families. In spite

of the fact that some rate constants, such as five-membered carbon ring belonging to the

exocyclic ring-opening family, is not well grouped with the six and seven membered rings,

still generalized rate calculation rules have su�cient accuracy for calculating the large

number of possible reactions quickly with a low computational cost. After generating the

detailed reaction network with known kinetic parameters, sensitivity analysis or reaction

flux analysis can be performed to identify the crucial reactions channels in the model.

Then high-level quantum chemistry calculations can be applied to study these reactions

in further details with su�cient accuracy. Lastly, new families have impacted the bio-oil

detailed kinetic modeling significantly and as there are only few kinetic models concerning

a large number of heterocyclic derivatives, continuous kinetic studies of the decomposition

these compounds are required.

2.6 Supporting material

Cartesian coordinates of all transition states are provided in Appendix A.

81

2.7 Recommendations for future work

This study has made significant contributions toward generating automatic detailed de-

tailed kinetics models for biofuels. Particular attention has been given to the accurate and

computationally a↵ordable estimation of reaction rate coe�cients for bio-oil’s cyclic and

oxygenated compounds using rate calculation rules approach. The success of this method,

was demonstrated by comparing RMG-build models for bio-oil gasification process before

and after updating RMG’s kinetic database with new rate rules. However, still there are

several challenges towards building predictive detailed chemical kinetics for biofuels using

RMG. In the current section, several such challenges for future work are addressed.

2.7.1 Expand the e↵ect of the functional groups

To investigate the e↵ect of the functional groups, the rate rule calculations were performed

for the e↵ect of the ’OH’ groups on five, six, and seven membered rings with oxygen as the

heteroatom. To fully study the e↵ect of the ’OH’ functional groups, rate rule calculations

should be extended to five, six, and seven membered rings with carbon and nitrogen

as the heteroatoms. Therefore, still several rules are needed to be updated in RMG’s

kinetic database in order to obtain reasonable estimates for type of exo/endo ring-opening

reactions.

2.7.2 Add more reaction families with associated data to the

RMG database

In constructing detailed kinetics models for biofuels, as mentioned in Chapter 1, the

presence of all the feasible elementary reactions in the model is necessary. For example,

RMG needs new reaction family for ene reactions, such as 1,5 hydrogen shift reaction

specified as a missing reaction family in Chapter 1. The ene reaction is a reaction between

82

an alkene with an allylic hydrogen (the ene) and a compound containing a multiple bond

(the enophile), in order to form a new -bond with migration of the ene double bond and

1,5 hydrogen shift [143]. The ene reaction is useful CC forming tool for the many lignin

derivative molecules and is a typical type of reaction that is happening in lignin pyrolysis.

The general template and an example of this reaction is illustrated in Figure 2.20.

R1

R2

R3R4

+R5

H6

R1

R2

R3R4

R5H6

Figure 2.20: The general template of ene reaction with an example.

After updating the database with the new reaction family, it is necessary to obtain

accurate kinetic parameters and reaction rate rules.

83

Chapter 3

Automatic Reaction Mechanism

Generation for Producing

1,1,2,3-tetrachloropropane

3.1 Introduction

As introduced by our collaborators in Mexichem Fluor: ”The fluorochemical sector of

the global chemical industry is currently gearing up to replace existing products with

equivalents that o↵er the same performance characteristics but with lower global warm-

ing potential (GWP). Thus, the current generation of hydrofluorocarbon (HFC) products

will be replaced with hydrofluoroolefins (HFOs). Key to the timely commercialisation

of HFOs will be the availability of chlorinated feedstocks from which they can be con-

veniently prepared. 2,3,3,3-Tetrafluoropropene (1234yf) is one of the leading low GWP

HFO products identified as a possible replacement for 1,1,1,2-tetrafluoroethane (134a) in

mobile air conditioning applications. The key chlorinated feedstock for 1234yf manufac-

ture is 1,1,2,3-tetrachloropropene (1230xa), which can be prepared by two routes, one

starting from ethylene and the other from tetrachloroethylene”. Both pathways include

84

several steps of dehydrochlorination and free chain radical chlorination reactions. Detailed

kinetic modeling of these processes can be a helpful tool to better understand, design and

optimize 1230xa production. There are several published patent applications with lim-

ited numbers of reactions and intermediates, showing the recognized value of this kinetic

modeling approach. However, building a detailed chemical model with an extensive set

of free radical reactions, that contains a large number of intermediates and reactions and

needs many associated thermodynamic and kinetic parameters, is not easy to do by hand;

it is preferable to do it automatically, using a tool that is exhaustive and scalable. In

this chapter, I extend the Python version of Reaction Mechanism Generator (RMG-Py),

an open source and free tool, to generate such detailed kinetic models for chlorinated

hydrocarbons.

RMG includes C, N, O, S, and Si chemistry; in order to add chlorine, Cl, chemistry

into the software, several steps were taken that are explained in this chapter. Further-

more, an RMG-generated model was validated by comparing with available data from

literature. Building predictive detailed chemical models for chlorination processes using

RMG can save several months of research and development time and cost for manufac-

turing companies and for each new process, and the models can also be used to optimize

existing processes to lower costs of production.

3.2 Critical Literature Review

Chlorinated hydrocarbons are chemical compounds composed of carbon, hydrogen, and

chlorine. These compounds can be used as intermediates to produce other chemicals or

can be used directly as chlorinated solvents. Chemical and pharmaceutical companies

are the main chlorinated hydrocarbons customers for a variety of applications such as

refrigerants, aerosol product formulation, dry cleaning detergents, pharmaceutical sol-

vents, and paint formulation and stripping. 1,1,2,3-tetrachloropropene, 1230xa, with the

85

chemical formula CCl2=CClCH2Cl, is an important chlorinated intermediate that is used

widely to produce the new generation of the refrigerants. Detailed kinetic modeling of

1230xa chlorination can be a helpful tool to better understand, design, optimize, and

commission refrigerant processes. To date, there are several published patents proposing

important reaction channels for 1230xa production, showing the recognized value of the

kinetic modeling approach. In this section of thesis, a brief literature review regarding

proposed reaction pathways for 1230xa production from published patents is provided.

Moreover, few studies regarding thermodynamics of chlorinated species and exist kinetics

estimation of chlorination reactions in the literature also are addressed in this section of

thesis.

3.2.1 Proposed pathways from published patents

Smith [12] proposed a method to produce 1230xa from 1,2,3-trichloropropane in the liquid

phase. The summary of the proposed method is as the following steps:

• Chlorination of the 1,2,3-trichloropropane in the presence of azobisisobutyroni-

trile catalyst, reaction and products illustrated in Figure 3.1, and passing

the chlorinator e✏uent which made up of 1,2,3-trichloropropane, 1,1,2,3-

tetrachloropropane, 1,2,2,3-tetrachloropropane, 1,1,1,2,3-pentachloropropane,

1,1,2,2,3-pentachloropropane, and 1,1,2,3,3-pentachloropropane to a fractionating

column.

86

Cl

Cl

Cl

1,2,3-trichloropropane

Cl

Cl Cl

Cl

Cl

1,1,2,2,3-pentachloropropane

Cl

Cl

Cl

Cl

Cl

1,1,2,3,3-pentachloropropane

Cl Cl+

Cl

Cl

ClCl

Cl

1,1,1,2,3-pentachloropropane

Cl

ClCl

Cl

1,2,2,3-tetrachloropropane

Figure 3.1: Reaction and products from 1,2,3-trichloropropane liquidphase chlorination in the presence of azobisisobutyronitrile catalyst pro-posed by Smith [12].

• Recycling the 1,2,3-trichloropropane fraction to the chlorinator and removing the

1,2,2,3-tetrachloropropane fraction

• Passing the 1,1,1,2,3- and 1,1,2,2,3-pentachloro propanes fraction from the fraction-

ating column to the second caustic dehydrochlorinator

• Dehydrochlorinating the second chlorinator e✏uent and the 1,1,1,2,3- and 1,1,2,2,3-

pentachloropropanes fraction from the fractionating column.

• Passing the second dehydrochlorinatore e✏uent, including 1,1,2,3-

tetrachloropropane and 2,3,3,3-tetrachloropropane to an isomerizer packed with

siliceous granules with polar surface and isomerizing the 2,3,3,3-tetrachloropropane

to 1,1,2,3-tetrachloropropane, summerized in Figure 3.2.

87

Cl

Cl

ClCl

Cl

1,1,1,2,3-pentachloropropane

Cl

Cl Cl

Cl

Cl

1,1,2,2,3-pentachloropropane

- HCl

- HCl

Cl

ClCl

Cl

2,3,3,3-tetrachloroproeene

Cl

Cl

Cl

Cl

1,1,2,3-tetrachloropropene

isomerization

Figure 3.2: 1230xa formation reaction channels via 1,1,1,2,3-and 1,1,2,2,3-pentachloropropanes dehydrochlorination and 2,3,3,3-tetrachloropropane isomerization to 1230xa proposed by Smith [12].

Later, Woodard [13, 14] proposed a process to 1230xa production by dehydrochlori-

nation of 1,1,1,2,3-pentachloropropane in the presence of a ferric chloride catalyst. Their

process includes these steps and the complete mechanism is summarized in Figure 3.3:

• Preparing 1,1,1,3-tetrachloropropane by reacting ethylene with carbon tetrachloride

in the presence of of metallic iron and a promoter for the reaction, phosphorus (V)

compounds containing a phosphoryl group

• Dehydrochlorination of 1,1,1,3-tetrachloropropane to produce 1,1,3- and 3,3,3-

trichloropropenes

• Chlorinating of the 1,1,3- or 3,3,3-trichloropropenes to produce 1,1,1,2,3-

pentachloropropane, 240db.

• Dehydrochlorinating the 1,1,1,2,3-pentachloropropane, 240db, to produce a mixture

of 1,1,2,3- and 2,3,3,3-tetrachloropropenes

• Isomerization of 2,3,3,3-tetrachloropropene to 1,1,2,3-tetrachloropropene by con-

tancting the tetrachloropropenes mixture with a rearrangement catalyst

88

Cl

ClCl

Cl

1,1,1,3-tetrachloropropaneetheneCl

Cl

Cl

Cl

carbon tetrachloride

+

-HCl

ClCl

Cl

3,3,3-trichloropropene

Cl

Cl

Cl

1,1,3-trichloropropene

and

+Cl2

Cl

Cl

ClCl

Cl

1,1,1,2,3-pentachloropropane240db-HCl

-HCl

Cl

Cl

Cl

Cl

1,1,2,3-tetrachloropropene1230xa

Cl

ClCl

Cl

2,3,3,3-tetrachloroproeene

isomerization

Figure 3.3: 1230xa formation reaction channels by reacting ethylenewith carbon tetrachloride from the work of Woodard [13, 14].

These two proposed processes for 1230xa production were in solvent phase that re-

quired a long reaction time and had high cost due to use of catalysts. To overcome these

di�culties associated with the proposed methods, Mukhopadhyay et al. [15], and Wilson

et al. [16] introduced a method for 1230xa production as illustrated in Figure 3.4:

• Dehydrochlorination of 1,2,3 trichloropropane with an alkali (NaOH)

• Two rounds of chlorination reaction with chlorine, (Cl2), and repeating these reac-

tions to produce 1,1,2,2,3-pentachloropropane, 240aa

• Removing HCl from 1,1,2,2,3-pentachloropropane to produce l,1,2,3-

tetrachloropropene

89

Cl

Cl

Cl

1,2,3-trichloropropane

-HCl

Cl

Cl Cl

Cl

Cl

1,1,2,2,3-pentachloropropane240aa

+Cl2

-HClCl

Cl

Cl

Cl

1,1,2,3-tetrachloropropene1230xa

Cl

Cl

2,3-dichloropropene

Figure 3.4: 1230xa formation reaction channels from 1,2,3 trichloro-propane proposed by Mukhopadhyay et al. [15] and Wilson et al. [16].

Nevertheless, this proposed method still had a lower yield and generated too much

waste because of using alkali.

Furthermore, Nose et al. [17] introduced a method for 1230xa production from heating

1,1,1,2,3-pentachloropropane,240db, in the gas-phase for non-catalytic dehdrochlorination

reaction. They reported the process as, Figure 3.5:

• Heating 1,1,1,2,3-pentachloropropane, 240db, to 200�- 550� n absence of catalyst

• Dehydrochlorination of 1,1,1,2,3-pentachloropropane,240db, by simultaneously pro-

viding inert gas, N2, in an amount of 0.5 to 100 mol per mol of 1,1,1,2,3-

pentachloropropane

• Returning unreacted 1,1,1,2,3-pentachloropropane and 2,3,3,3-

tetrachloropropene,1230xf, if it’s in the product, to the reactor for further

conversion

90

Cl

Cl

ClCl

Cl

1,1,1,2,3-pentachloropropane240db

-HCl

-HCl

Cl

Cl

Cl

Cl

1,1,2,3-tetrachloropropene1230xa

Cl

ClCl

Cl

2,3,3,3-tetrachloroproeene1230xf

isomerization

Figure 3.5: Non-catalytic gas phase reaction channels proposed by Noseet al. [17] for 1230xa formation.

They concluded that the operating in such method can produce 1230xa with a high

selectivity. They also highlighted the importance of the process temperature; lowering the

process temperature from the mentioned range, would decrease the 1230 conversion ratio

and increasing the temperature would cause the formation of cyclic dimers, dechlorinated

3,3,3-trichloropropene, etc. as by products and lower the selectivity. Their results, show-

ing the reactor outlet from their method in 4 di↵erent examples, summarized in Table

I.

Table I: The results obtained from the reactor outlet for 1230xa production in non catalyticgas-phase reaction according to the Nose et al. [17] method.

Condition Example 1 Example 2 Example 3 Example 4Reaction temperature (�C) 350 400 285 350Contact time (sec) 10.2 47 22 24.9240db Conversion ratio (%) 75.4 73.4 48.8 77.61230xa selectivity 97.9 90.3 96.8 88.31230xf selectivity 1.6 1.5 2.3 2

3.2.2 Thermodynamics of chlorinated hydrocarbons

Thermodynamic properties of the chlorinated hydrocarbons are important in the detailed

chemical modeling of chlorocarbon systems and to study their thermodynamic equilib-

91

rium. There are two methods available to estimate the thermochemistry of chlorinated hy-

drocarbons; performing electronic structure calculations and using group-based estimates

such as Benson Group Additivity (GA) approach [59]. Quantum chemistry calculations

at at higher level of theory and also for larger systems, to obtain a good estimate, are

computationally expensive. Even though using cheaper methods are faster, they don’t

have the su�cient accuracy for �H�f s of chlorocarbons [18]. Dewar et al. [144] in their

AM1 quantum mechanical calculations reported that the error in �H�f for more than 60

chlorocarbons were larger than ± 5 kcal/mol. Furthermore, Li Zhu et al. [145] calculated

�H�f298, S

�298 and CP (T ), 300 < T < 1500 K, for all C1 and C2 and eight C3-C6 chloro-

carbons using MOPAC6 PM3 [61] and compared with the literature. In their theoretical

study, they concluded that PM3 derived S�298 and CP (T ), are in good agreement with the

literature, but for �H�f298, there were ± 5 kcal/mol error, similar to the Dewar et al. [144]

observations.

Using the Benson’s GA approach to estimate the thermochemistry of the chlorinated

hydrocarbons is a valuable method [146, 147]. However, the Benson GA approach does not

fully consider the steric e↵ect, termed as non-next-nearest-neighbor interactions, of the

adjacent functional groups such as chlorine or methyl on the thermodynamic properties.

Chen et al. [18] developed chlorinated groups while considering the e↵ect of the non-next-

nearest-neighbor interaction for use in thermodynamic estimation of the chlorocarbons

using Benson GA approach. They derived the Benson groups for chlorinated alkanes and

alkenes from molecules where no chlorines were on the carbon next to the carbon atom

bonded to chlorine(s). They also used gauche interactions [59] to consider the non-next-

nearest-neighbor e↵ects in their previous studies [148, 149]. In conclusion, they illustrated

that the interactions increased in highly chlorinated hydrocarbons and the correction to

account the interaction term should be increased as well, as shown in Figure 3.6.

92

Figure 3.6: The correction in the enthalpies of formation for accountingthe e↵ect of interaction as function of number of chlorine atoms formultichloro alkanes and alkenes, reproduced from [18].

Furthermore, they compared their results with literature and showed good agreement

between their calculations and literature data with the error �H�f298= ± 0.29 kcal/mol,

S�298=± 0.68 cal/mol.K and CP (T )=± 0.23 cal/mol.K.

3.2.3 Kinetics of chlorinated hydrocarbons

As mentioned earlier, many natural and industrial processes to manufacture chlorinated

products such as 1230xa, include detailed reaction mechanism networks. In order to

propose a comprehensive mechanism for each process, specific reaction classes, which

define how chlorinated hydrocarbon species could react with each other, are required.

Like other free radical reactions, chlorination mechanism includes three steps: initiation

steps, propagation steps, and termination steps. For example, methyl chloride production

through a complete detailed mechanism of methane chlorination is illustrated in Figure

3.7.

93

Figure 3.7: Initiation, propagation and termination free radical reac-tion steps in methyl chloride production via methane chlorination.

3.2.3.1 Initiation steps

Free radical reaction mechanism starts with initiation step to initiates the reaction, which

in the chlorination case, is the separation of the Cl2 into two Cl radicals with single

unpaired electrons via the equal splitting of a Cl-Cl bond. Therefore, the reaction rate

depends on the the strength and bond dissociation energy (BDE) of the Cl-Cl bond.

Moreover, the reverse reaction of the initiation reaction is the radical recombination, al-

ready exists in RMG, and the rate of the initiation can be calculated from the reverse rate

by knowing the thermochemical data [90, 91]. The activation energies of radical recom-

bination reactions are set to be zero as barrier-less reactions and the modified Arrhenius

pre-exponential factors (A) can be estimated from an improved collision theory [91].

3.2.3.2 Propagation steps

Propagation step is the reaction of one reactive radical species with a non-radical stable

molecule to produce two new molecules: radical and stable molecules. Hydrogen abstrac-

tion and chlorine abstraction families are the most common reaction classes during the

propagation step.

94

• H-abstraction: The H abstraction from a chlorinated molecule via chlorine atom to

form a reactive molecule and a chlorinated stable molecule, is a common reaction.

The general template of the reaction is demonstrated in Figure 3.8.

1R 2H 3Cl 2H 3Cl1R+ +

Figure 3.8: The general template of the H-abstraction reaction viachlorine atom.

Goldfinger et al. [23] investigated the H-abstraction reaction kinetics from chlori-

nated ethanes via chlorine atom in the gas phase experimentally, to study the non

bonding interactions between the attacking chlorine atom and the chlorine atoms

in the molecule. They observed that there is a decrease in the pre-exponential A

factors in the highly chlorinated ethanes, on the other hand, activation energy in-

creased with the number of chlorine atoms on the attacked carbon and the adjacent

carbon atom. Furthermore, they calculated the bond dissociation energy D(C-H)

and concluded that the D(C-H) decreases from CH3 �H to CCl3 �H.

Seetula [150] studied the e↵ect of the chlorine atom on the structure and bond

dissociation energy of some chlorinated ethanes and propanes both theoretically and

experimentally. He performed MP2 and MP4 calculations to investigate the e↵ect

of di↵erent substituents on the C-H bond energies and also the e↵ect of the Cl atom

on its adjacent C-H bond. He concluded that the ↵-C-H bond is weaker than the

�-C-H bond in chlorinated hydrocarbons and furthermore, the C-Cl bond becomes

weaker in the following order ( kJ/mol): 351.0 (CH3Cl) > 334.1 (CH2Cl2) > 315.1

(CHCl3) > 288.3 (CCl4), which is in great agreement with previous observations

[151, 152].

Senkan et al. [19] studied the kinetics of the H-abstraction reaction of hydrocar-

bons and chlorinated hydrocarbons by chlorine atom and analyzed their result us-

ing Evans-Polanyi and structure-activity relationships (SAR). In their investigation,

95

they’ve shown that even the Evans-Polanyi correlation is valid for C1 chlorinated hy-

drocarbons, but they couldn’t find such correlation for C2 chlorinated hydrocarbons

(Figure 3.9).

Figure 3.9: Evans-Polanyi plot for H-abstractions from C1 and C2chlorinated hydrocarbons by Senkan et al. [19].

To establish the SAR correlation Senkan et al. used Atkins [153, 154] approach

by assuming the total rate of H-abstraction reaction by chlorine radicals can be

expressed as a linear combination of the abstraction rates of primary, secondary,

and tertiary H atoms. They showed promising success of the SAR analysis in ki-

netic modeling of chlorinated hydrocarbons by plotting the SAR predictions versus

experimental data, Figure 3.10.

96

Figure 3.10: Comparison of SAR predictions with experimental data fro H-abstraction of chlorinated hydrocarbons by chlorine radical by Senkan et al.[19].

• Cl-abstraction: The general template of the Cl-abstraction reaction is illustrated in

Figure 3.11.

1R 2Cl 3R 2Cl 3R1R+ +

Figure 3.11: The general template of the Cl-abstraction reaction family.

Bryukov et al. [20] conducted an experimental study for the kinetics of the

(Cl,H)-abstraction from chlorinated methanes by H atom using the discharge

flow/resonance fluorescence technique over wide ranges of temperatures. They also

used transition state theory and performed quantum chemistry calculations to ob-

tain a correlation between the activation energies and enthalpies of the reactions,

illustrated in Figure 3.12

97

H+ CH4 = H2 +CH3

H+CCl4 = HCl+CCl3

H+CHCl3 = H2 +CCl3

H+CH2Cl2 = H2+CHCl2

H+CH3Cl = H2 +CH2Cl

H+CHCl3 = HCl+CHCl2

H+CH2Cl2 = HCl+CH2Cl

H+CH3Cl = HCl+CH3 }}

Cl abstraction

H abstraction

(Filled symbols)

(Open symbols)

Cl-abstraction H-abstraction

Figure 3.12: Obtained correlation by Bryukov et al. [20] between activationenergies and enthalpies of reactions for (Cl,H)-abstraction from chlorinatedmethanes by H atom attacks.

Furthermore, Louis et al. [21] investigated the (H,Cl,F)-abstraction kinetics of chlo-

rinated methanes via H radical attacks theoretically. They performed the geometry

optimization and frequency calculations at MP2 level of theory and single point

energy calculations at CCSD(T) level. Furthermore, they used transition state the-

ory to estimate the rate constants as a function of temperature, 700-2500 K. For

the reactivity trend analysis, they correlated barriers with Evans-Polanyi relations

to correlate barriers with heats of reactions. In this study, they’ve shown that the

Evans-Polanyi correlation is valid for (H,Cl,F)-abstraction reactions via H radical

attacks, and their results are illustrated in Figure 3.13.

98

Figure 3.13: Predicted Evans-Polanyi plot by Louis et al. [21] for(H,Cl,F)-abstraction reactions via H radical attacks for chlorinatedmethanes.

3.2.3.3 Termination steps

Free radical chlorination reaction will be terminated by loss of the free-radical intermedi-

ates and decreases in reactants concentration. The most common termination reaction,

is radical recombination when two radicals couple to form a stable molecule. The general

template of the radical recombination reaction class is illustrated in Figure 3.14. Once

again, the activation energies of this family are barrier-less and the modified Arrhenius

pre-exponential factors (A) can be estimated from collision theory [91].

2R 1R 2R1R +

Figure 3.14: Radical recombination reaction family general reactiontemplate

3.3 Computational Method

Between proposed reaction pathways for 1230xa production in Section 3.2.1, there are two

main reaction channels to produce 1,1,2,3-tetrachloropropene (1230xa), as illustrated in

Figure 3.15; one starting from 1,1,1,3-tetrachloropropane, red pathway in Figure 3.15,

and the other from 1,1,1,2,2-pentachloropropane,blue pathway in Figure 3.15.

99

Figure 3.15: Main proposed reaction channels to produce 1,1,2,3-tetrachloropropene (1230xa) [12, 14–17]

Both pathways include several steps of dehydrochlorination and free chain radical

chlorination reactions. Detailed kinetic modeling of these processes can be a helpful

tool to better understand, design, and optimize 1230xa production. However, building a

detailed chemical model with an extensive set of free radical reactions, that contains a

large number of intermediates and reactions and needs many associated thermodynamic

and kinetic parameters, is not easy to do by hand; it is preferable to do it automatically,

using RMG.

In order to propose a comprehensive mechanism for 1230xa production using RMG,

four specific reaction classes, which define how chlorinated hydrocarbon species could react

with each other, were used. Two of these reaction classes were new: the chlorine addition

into the double bond and chlorine abstraction reactions that can take place through free

radical chain mechanism. Two existing reaction families in RMGs kinetic database were

updated with new chlorinated functional groups. Furthermore, thermodynamic data for

these chlorinated species were estimated via Bensons group additivity approach and QM

calculations. In the following sections, technical and computational aspects of detailed

100

kinetic model generation for 1230xa will be explained in further detail.

3.3.1 Chlorine (Cl) atom type in RMG

Before this work, RMG was able to model systems with only C, H, O, N, S, and Si atoms.

To include chlorine chemistry, RMG’s molecule module was updated with Cl atom type.

The atom type module of an atom in RMG describes the atom itself and some information

about the local bond structure around that atom, for example, whether the atom is able

to have single or double bond types with another atom. Chlorine belongs to the halogen

group in the periodic table with seven valence electrons and by gaining only one electron

can satisfy the octet rule [155], eight electrons in its valence shell. Thus, the current atom

type for chlorine in RMG was defined as chlorine atom with one single bond.

3.3.2 Thermodynamics of chlorinated hydrocarbons in RMG

Thermochemistry of chlorinated species in RMG can be estimated via three methods:

• Species thermochemistry libraries

• Group based methods

• Quantum-chemical calculation

This section gives some detail descriptions of each method to determine the thermochem-

istry of the chlorinated species in 1230xa detailed kinetic modeling.

3.3.2.1 Species thermochemistry libraries

These libraries have known thermochemical parameters for both radical and stable species.

Values for the thermochemistry of the species are from experimental data or high level

quantum chemistry calculations. RMG’s thermo database was updated with a new ther-

mochemistry library for chlorinated hydrocarbon, and standard heat capacity, standard

101

enthalpy of formation at 298K and standard entropy at 298K data, from direct quantum

chemistry calculations and published literature [156, 157], were reported for every species

in the library.

3.3.2.2 Group-based methods

RMG’s thermodynamic database includes functional groups for fast thermo estimates via

the group additivity approach. For stable species, RMG mainly estimates the thermo-

chemistry from the Benson Group Additivity (GA) [158] method, by dividing a molecule

into functional groups and summing the contribution of each functional group to the

overall thermodynamics. The accuracy of the using group additivity approach in the pre-

diction of thermochemical parameters depends on two factors; 1) whether group values

derived from other compounds can be used and, 2) accuracy of the group values. In

order to enable RMG to estimate the thermodynamic of chlorinated species from GA

method, the thermochemistry database of the RMG was updated with chlorinated func-

tional groups. The values for these chlorinated groups were taken from the Chen et

al. [18] study. Figure 3.16 shows the new implemented chlorinated functional groups

in RMGs thermochemistry database with an example of calculated thermochemistry of

chloroethene. As illustrated in Figure 3.16, comparison with NIST reported value for

chloroethene [157] shows that the Benson group contribution approach is an accurate and

fast method when functional groups are adequate.

102

Figure 3.16: RMG’s thermochemistry database was updated with newchlorinated functional groups. As an example, comparison between thechloroethene thermochemistry estimation via GA approach and NISTreported value shows a good agreement.

Furthermore, for radical species, RMG has Hydrogen Bond Increments (HBI) [159]

groups that describe the influence of the loss of a hydrogen atom on enthalpy of formation,

entropy, and heat capacity of the radical species. HBI correction groups can be coupled

with Bensons Group Additivity method to estimate the thermochemistry of the radical

molecules. Therefore, based on Lay et al. [159], the thermochemistry of the radical

molecule, R⇤, can be calculated from the corresponding parent molecule by adding a HBI

to account for the loss of a hydrogen atom using following equations:

�fH�298(R

⇤) = HBI(�fH�298) +�fH

�298(R�H) (3.1)

C�P (R

⇤) = HBI(C�P ) + C�

P (R�H) (3.2)

�S�298(R

⇤) = HBI(�S�298) +�S�

298(R�H) (3.3)

For the group-based thermochemistry estimation of the chlorinated radical molecules,

RMG’s HBI database was updated with chlorinated groups, illustrated in Figure 3.17.

103

Parent molecule Radical molecule

HBI (ΔfHo298)(kcal/mol)

HBI (So298)(cal/mol*K)

HBI (Cop 298)(cal/mol*K)

98.2 3.0 0.55

95.7 1.2 -0.31

109.9 1.5 -0.51

96.7 3.8 0.12

Figure 3.17: Hydrogen Bond Increment (HBI) calculations for chlori-nated species.

Further, in order to consider the e↵ect of the Cl atom on its adjacent C-H bond, more

HBI calculations were performed for the chlorinated hydrocarbons including two chlorine

atoms next to the radical carbon. Calculation results were demonstrated in Figure 3.18

and RMG’s HBI database was updated with new calculated values.

Parent molecule Radical molecule HBI(ΔfHo298)(kcal/mol)

HBI(So298)(cal/mol*K)

HBI(Cop 298)(cal/mol*K)

94.9 3.6 -0.16

99.5 3.2 0.42

111.9 2.0 -0.61

95.8 5.1 0.19

Figure 3.18: More HBI calculation to consider the e↵ect of the chlorineatom on its adjacent C-H bond.

3.3.2.3 Quantum chemistry calculation

As the computational cost increases exponentially with the number of heavy atoms, most

of the quantum chemistry calculations for chlorinated compounds were performed at the

CBS-QB3 [116] level of theory in the Gaussian09 package [62]. Geometry optimization and

frequency calculations of all chlorinated radical and stable species were first performed at

B3LYP [136] level of theory with the 6-31G(d) basis set. The calculated geometries were

then used to find improved geometries, electronic energies, and frequencies at the CBS-

QB3 [116] level of theory. The CanTherm [137] package was used to calculate the entropy

and heat capacities as a function of temperature from those data. For the vibrational

partition function, the harmonic oscillator approximation has been assumed and all the

104

obtained frequencies from CBS-QB3 calculations were scaled by a factor of 0.99 [138].

Furthermore, bond additivity corrections for CBS-QB3 standard enthalpies of formation

were added from the work of Petersson et al. [160] for a C-H, C-C, C=C, and C-Cl bond

as -0.11, -0.3, -0.08, and 1.29 kJ/mol, respectively.

3.3.3 Chlorination reaction families in RMG

RMG uses a database of reaction families to generate all the possible reactions that a

species can undergo in the presence of the other species in the chemical mechanism; every

reaction family represents a particular type of elementary chemical reaction, such as

bond-breaking, or radical addition to a double bond. For generating free radical reaction

mechanism for 1230xa production through several steps of free radical dehydrochlorination

and chlorination process, two existing reaction families in RMG, hydrogen abstraction and

radical recombination, were updated with chlorinated groups to make RMG able to build

such models. Figure 3.19 (a) shows the general template of the H-abstraction reaction

family, and to enable RMG to generate H-abstraction reactions for chlorinated species,

R1, and R3 groups were updated to include chlorine atom and chlorinated functional

groups Figure 3.19 (b) is related to radical-recombination reaction family and R1 and

R2 groups were updated with chlorinated groups.

1R 2H 3R 2H 3R1R+ +

(a)

2R 1R 2R1R +(b)

Figure 3.19: The general template of the (a) H-abstraction reaction, (b) radical recombinationreaction family.

Furthermore, two new reaction families for Cl-Cl/H-Cl addition into the double bond

and chlorine abstraction reactions (Cl-Abstraction) were added into the RMG’s database,

105

reaction general templates were illustrated in Figure 3.20.

(a)

(b)

Figure 3.20: The general template of the (a) Cl-abstraction reaction, (b) Cl2/HCl addition intothe double bond reaction family.

3.3.4 Kinetics estimation for chlorinated hydrocarbons in RMG

After updating RMG’s kinetic database with new reaction families and also updating the

existing ones, the next step is filling the database with accurate kinetic parameters. For

the radical recombination reaction family, as mentioned earlier, the activation energies

were set to be zero and the modified Arrhenius pre-exponential factors (A) were esti-

mated from an improved collision theory. Quantum chemistry calculations can be used to

estimate Arrhenius rate parameters and fill the kinetics database for each reaction family.

However, the number of reactions in each reaction family is massive, and applying high-

level electronic structure calculations, would be prohibitively computationally expensive.

Alternatively, the kinetic parameters can be taken from available data in literature and

rate rule estimation.

3.3.4.1 Training Set

Each reaction family in RMG’s kinetic database includes three specific files; 1) groups

that contain reaction recipe, definition of groups and reacting centers, 2) training set that

contains a set of training reaction with known kinetic parameters and 3) rules that specify

106

kinetic parameters by averaging rate parameters from children nodes. There are several

published kinetics data available for the H-abstraction by chlorine atom, Cl-abstraction

and HCl insertion into double bond reaction families. Reported data from literature were

used to fill in training and rules templates of the associated reaction families in RMG.

In the training sets, each reported reaction was matched to a specific template with

known kinetic parameters. Some of references uses as training sets in the three mentioned

reaction families are briefly presented in the following section.

Published reaction rates from the work of Goldfinger et al. [23] for primary, secondary,

and tertiary hydrogen atom abstraction from chlorinated C1 and C2 hydrocarbons by

chlorine radical, summarized in Table II, were used in the training set of the RMG’s

H-abstraction family.

Table II: Used activation energy (cal/mol) and pre-exponential factor (l/mol.sec) as a trainingset reactions in RMG from the work of Goldfinger et al. [23] for the H-abstraction reaction bychlorine atom for chlorinated C1 and C2 hydrocarbons.

Type of H-atom attacked Reactant (RH) Ea (cal/mol) log10A (l/mol.sec)Primary C2H6 1050 10.95Primary C2H5Cl 1500 10.05Primary 1,1-C2H4Cl2 3400 10.00Primary 1,1,1-C2H3Cl3 3600 9.40Secondary C2H5C1 1500 10.55Secondary 1,2-C2H4Cl2 3100 10.80Secondary 1,1,2-C2H3C13 3700 10.15Secondary 1,1,1,2-C2H2C14 2450 9.15Tertiary 1,l-C2H4Cl2 1900 9.95Tertiary 1,1,2-C2H3C13 3100 9.95Tertiary 1,1,2,2-C2H2Cl4, 2450 9.95Tertiary C2HCl5 3550 9.65

Furthermore, Senkan et al. [19] gathered reaction rate parameters of the chlorinated

hydrocarbons hydrogen abstraction reaction by Cl radical from previous published liter-

ature to study the Evans-Polanyi and structure-activity relationships (SAR), and these

data were used in the RMG’s H-abstraction family’s training set.

107

3.3.4.2 Quantum chemistry

All the quantum chemistry calculations were performed in Gaussian09 [62]. Density func-

tion theory methods at B3LYP [136] level of theory with the 6-31G(d) basis set were used

to optimize geometries and frequencies for reactants and products. Then the obtained

optimized geometries were used to find statistical molecular properties of each species in

the reaction using CBS-QB3 [116] level of theory. Transition state theory was applied

to determine the Arrehnius rate parameters using calculated statistical thermodynamic

properties in the CanTherm [137] package. For the vibrational partition function, the

harmonic oscillator approximation was assumed and hindered rotor calculations were not

included. All the obtained frequencies from CBS-QB3 are scaled by a factor of 0.99 [138].

Furthermore, Intrinsic Reaction Coordinate (IRC) [140] calculations have been performed

to track the minimum energy path from a transition state to the corresponding reactant

and product species.

3.3.4.3 Rate rules

For those reaction rates in the model that are not either reported in the literature (training

set) or calculated via quantum chemistry calculations, RMG’s rate rules were applied to

fill the database and kinetics were averaged from the children nodes as an estimate.

Though in these cases the kinetics estimation are less reliable than direct calculation, but

previous studies showed the promising success of using these type of correlations in kinetic

modeling of chlorinated hydrocarbons, such as SAR analysis results by Senkan et al. [19],

Bryukov et al.[20], and Louis et al. [21] Evans-Polanyi correlation results, more detail is

provided in section 3.2.3.2.

108

3.3.5 Model evaluation

After model generation, reaction mechanism evaluation is required. There are several

methods to evaluate the mechanism; comparison to the available experimental data, re-

action flux analysis to reveal the dominant reaction channels, and sensitivity analysis to

identify the sensitive rate parameters to reduce the uncertainty. After the mechanism

evaluation, from the comparison between the model and available data, the model might

need to be improved with new data. New data can be provided either from theoretical

calculations or from literature. After updating the RMG’s databases with new data and

fixing bugs, a new model was built with the best chemical data.

3.4 Results and Discussions

A first model was generated in Reaction Mechanism generator (RMG) for 1,1,2,3-

tetrachloropropene (1230xa) production with 74 species and 936 reactions. Every species

in the model has known thermodynamic properties and 936 reactions were based on the

four implemented reaction families: H-abstraction, radical recombination, Cl abstrac-

tion, and HCl/Cl2 insertion into double bond, with associated reaction rate parameters.

The output of the RMGs generated model in Chemkin format was used for the further

simulation of 1230xa in batch reactor in Cantera [66]. Simulations were performed at

atmospheric pressure, reaction temperature between 350 to 400 �C and 25 to 30 seconds

residence time; these experimental operation condition were taken from the published

patent by Nose et al. [17] for 1230xa production under non catalytic gas-phase con-

ditions. The result from the batch reactor simulation for the concentration profiles of

1,1,2,3-tetrachloropropene (1230xa) ( product) and 1,1,1,2,3-pentachloropropane (240db)

(feedstock) versus time is presented in Figure 3.21.

109

Figure 3.21: Batch reactor simulation of 1230xa (product) and 240db(feedstock) concentration profiles from RMG-built model.

To date, there is no complete reaction mechanism for 1,1,1,2,3-pentachloropropane

(1230xa) production, and published patents only proposed a small number of reactions,

as a mechanism for 1230xa. Therefore, validating the yield of the 1230xa production from

the RMG-built model by comparing it with experimental data, has remained a challenge.

The only relevant published data are from the work of Nose et al. [17], that looked at

a few reactions from 1,1,1,2,3-pentachloropropane (240db) to 1,1,2,3-tetrachloropropene

(1230xa) and reported the conversion of 240db to 1230xa (more detail is discussed in

Section 3.2.1). A comparison is provided for 1230xa conversion in Table III between

RMG-built model and Nose et al. [17] patent, though this comparison is not ideal as the

RMG-built model is more detailed than the patent.

110

Table III: 240db conversion (%) for 1230xa production from Nose et al. [17] patent and RMG-built model.

Model vs. experiment 240db conversion (%)Nose et al. [17] patent 78RMG-built model 40

From the comparison, no absolute conclusion could be taken, but the low conversion

of 1230xa from RMG-built model was a concern. In order to evaluate the model further,

thermochemistry of the main species in the RMG-generated model was compared with

available published data.

3.4.1 Thermodynamics evaluation

RMG estimated thermodynamics for both chlorinated stable and radical species were

compared with NIST reported values for stable species and with CBS-QB3 quantum

chemistry calculations for radical species. Comparison shows that thermodynamic pa-

rameters of stable molecules, calculated from the group additivity approach have a good

agreement with NIST values, as illustrated in Table IV.

Table IV: RMG estimated thermodynamics for some chlorinated stable species.

�Hf298 (kcal/mol) RMG GA estimate NIST-49.25 -45.40

-7.36 -9.6

-18.64 -20.6

-56.04 -53.1

111

But thermochemistry of chlorinated radical species in RMG may not be estimated

accurately enough using the group additivity approach, Table V.

Table V: RMG estimated thermodynamics for some chlorinated radical species.

�Hf298 (kcal/mol) RMG GA estimate CBS-QB36.64 -12.85

-4.24 -10.05

9.45 -8.76

3.86 -10.10

As mentioned in Section 3.3.2.2, to improve group additivity estimates in RMG, Hy-

dogen Bond Increments (HBI) corrections were calculated to consider the e↵ect of the

loss of a hydrogen atom on enthalpy of formation, entropy, and heat capacity of the

chlorinated radical species. Using HBI corrections for estimating thermodynamic param-

eters via group additivity shows remarkable improvement thermochemistry of chlorinated

radical compounds, as the comparison shown in Table VI.

112

Table VI: Group Additivity estimates improved when using HBI corrections for chlorinatedradical compounds thermochemistry.

�Hf298 (kcal/mol) GA estimate GA estimate with HBI CBS-QB36.64 -10.84 -12.85

-4.24 -9.62 -10.05

9.45 -6.11 -8.76

3.86 -13.64 -10.10

After improving thermochemistry estimation for chlorinated radical species, a new

model was generated for 1230xa in RMG and batch reactor simulations were performed

to demonstrate the 1230xa concentration profile in the new model. There is a di↵erence

between batch reactor simulation results with and without HBI corrections, illustrated

in Figure 3.22, showing the important influence of the thermodynamic properties on the

free radical chlorination chemical modeling.

113

Figure 3.22: Batch reactor simulation of 1230xa (product) and 240db (feed-stock) concentration profiles from RMG-built model after including HBI cor-rections for thermochemistry estimation of chlorinated radical species.

Moreover, 240db conversion was increased in the new RMG-built model when using

HBI corrections, illustrated in Table VII.

Table VII: 240db conversion (%) for 1230xa production from Nose et al. [17] patent and RMG-built models before and after adding HBI corrections.

Model vs. experiment 240db conversion (%)Nose et al. [17] patent 78RMG-built model with no HBI corrections 40RMG-built model with HBI corrections 55

3.4.2 Reaction flux analysis

Reaction flux analysis was performed to reveal the important reaction channels for 1230xa

production under the simulation conditions as shown in Figure 3.23. The main purpose

of this analysis was comparing these important reaction channels with available proposed

pathways in published patents.

114

240db

1230xa

250fb

Figure 3.23: Reaction flux analysis result to reveal the important re-action channels in the RMG-built model for 1230xa production.

Published patents [16, 17], illustrated in Figure 3.24, confirm the reaction flux analysis

result, Figure 3.23, which shows that the non-catalytic production of 1230xa in gas-phase

from 1,1,1,2,3-pentachloropropane (240db), has a high yield as a single step reaction.

115

250fb

240db

1230xa

Figure 3.24: The published patent confirms the reaction flux analysisfom RMG-built model for 1230xa production.

3.4.3 Sensitivity analysis

A sensitivity analysis was carried out on a RMG-built model to identify the important

reaction channels for 1230xa production under simulation conditions. The results for this

analysis are summarized in Figure 3.25:

116

at T= 350 C

at T= 550 C

(a)

(b)

Figure 3.25: Sensitive reaction channels for 1230xa production inRMG-built model at (a) T=550 C and (b) T=350 C.

Sensitivity analysis shows that free radical reactions are greatly dominant in 1230xa

production and some important reaction channels are not present in the patents. More-

over, high sensitivity to the 240db and 250fb dehydrochlorination reactions shows a great

agreement with the observation in the published patents.

Furthermore, both sensitivity analysis and reaction flux analysis show that the RMG-

built model provides more detailed data for 123xa production as all competing chemical

pathways and intermediates for the process are proposed in the model.

117

3.5 Summary

Due to the high contribution of chlorinated refrigerants to the global climate change and

ozone depletion, refrigerant manufacturers are developing a new generation of refrigerants,

each requiring di↵erent intermediates and feedstocks. The key chlorinated feedstock for

new generation of refrigerants manufacture with lower Global Warming Potential (GWP)

is 1,1,2,3-tetrachloropropene (1230xa). Detailed kinetic models are helpful to improve the

understanding of chlorinated hydrocarbons conversion and address the knowledge gap in

such systems. However, building predictive detailed kinetic models has high level of com-

plexity due to the presence of large number of thermodynamic and kinetic parameters

that must be estimated accurately. In this study, the Python version of the Reaction

Mechanism Generator (RMG), was extended to build a detailed kinetic model for 1230xa

production. RMG already has a good success in detailed chemical modeling of hydro-

carbons in both gas and liquid phase that contain carbon, oxygen, nitrogen, sulfur, and

silicon chemistry. To make RMG a capable tool to model chlorinated hydrocarbons, the

software was modified with additional features.

To ensure that RMG was not missing any pathways for chlorination processes, two

specific reaction classes were implemented in RMG. These reaction classes were related

to the Cl2/HCl insertion into the double bond and chlorine abstraction reactions that

can take place through free radical chain mechanism. Furthermore, two existing reac-

tion families, hydrogen abstraction and radical recombination, in RMG’s kinetic database

were updated with new chlorinated groups. RMG mainly estimates the thermochemistry

of the species from Benson Group Additivity (GA) method, by dividing a molecule into

functional groups and summing the contribution of each functional group to the overall

thermodynamics. To enable RMG to estimate the thermodynamic of chlorinated species

from GA method, the thermochemistry database of the RMG was updated with chlori-

118

nated functional groups.

A detailed kinetic model was built for 1230xa production using RMG and simulation

results were compared with experimental data from the patent literature. To validate the

thermochemistry of the both stable and radical chlorinated species, RMGs estimates from

the GA approach were compared with NIST reported values for stable species and with

CBS-QB3 quantum chemistry calculations for radical species. Comparison of the data

shows that thermodynamic parameters of radical species in RMG may not be estimated

accurately using the GA approach. To improve GA estimates, Hydrogen Bond Incre-

ments (HBI) corrections were calculated to consider the e↵ect of loss a hydrogen atom

on enthalpy of formation, entropy, and heat capacity of the chlorinated radical species.

Using HBI corrections for estimating thermodynamic parameters via Group Additivity

approach showed remarkable improvement for chlorinated radical compounds thermo-

chemistry. Furthermore, sensitivity analysis and reaction flux analysis were performed

to reveal important reaction channels in the 1230xa production. Both analyses not only

show a great agreement between RMG-built model and proposed pathways from pub-

lished patents but also highlight that the RMG-built model provides more detailed data

by proposing all competing chemical pathways and intermediates in the process.

3.6 Supporting material

The Chemkin file of the RMG-built model for 1230xa production is provided in Appendix

B.

119

3.7 Recommendations for future work

This study has made several significant contributions in building detailed kinetic models

for chlorinated hydrocarbons, specifically for 1,1,2,3-tetrachloropropene (1230xa) produc-

tion. Particular attention has been given to improve the understanding of the free radical

chlorination process and kinetics and thermodynamics of such systems. However, there

are still a number of challenges that need to be addressed in order to improve our detailed

kinetic model generation capabilities for 1230xa production. In this section, several such

challenges as recommendations for future work are discussed.

3.7.1 Improve accuracy of kinetics estimates

To move toward predictive chemical kinetics, a version of RMG-Py is under development

that uses on-the-fly quantum calculations to estimate rate coe�cients [165]. This tool

can be used not only for automatically determining the kinetic parameters for hydrogen

abstraction, chlorine abstraction and HCl addition into double bond reaction families, but

also to improve accuracy of kinetics estimates in chlorination modeling.

This tool has the ability to automatically determine transition state structures using

quantum chemistry calculations and use Transition State Theory (TST) to calculate the

rate parameters. Nevertheless, still part of the challenge will be the computational cost,

as conducting quantum chemistry calculations for the transition state of all reactions is

expensive. Another challenge is identifying the appropriate level of theory for chlorination

reactions.

3.7.2 Liquid-phase chlorination modeling

The primary detailed model for 1230xa production is generated in gas-phase. The next

step after estimating all the thermochemistry and kinetic parameters accurately in the

120

gas-phase, will be modelling 1230xa production in the liquid-phase as there are several

published patents proposing 1230xa production in solvent phase. Furthermore, there some

experimental data available for 1230xa production in liquid-phase for model evaluation

purpose. In order to extend this project from gas-phase to liquid-phase such steps need

to be taken:

• RMG’s thermodynamic database must be modified with solvation thermochemistry

predictions to cover chlorinated hydrocarbons and relevant solvents [166].

• Kinetic solvent e↵ects database for existing gas phase chlorination reactions families

is required to be developed [167].

• Kinetic database should be updated with a library of known liquid phase reaction

rates.

3.7.3 Investigating the concerted E2 elimination reaction vs.

Sn2 substitution

Under homogeneous conditions, there are two competing pathways for dehydrochlorina-

tion reaction (HCl/Cl2 insertion into double bond) in the solvent phase, as illustrated in

Figure 3.26:

• Concerted E2 elimination reaction that are favorable for solution phase processes

• Sn2 substitution reaction, one bond is broken and one bond is formed

Figure 3.26: Reaction phath for concerted E2 elimination vs. Sn2 substitu-tion.

121

The rate of the reaction for these two competing pathways depends upon the strength

of the base. Generally, relatively strong bases are required for concerted E2 elimination

reactions. The solvent for these type of reaction is often an alcohol, like ethanol, and

water. The base resulting from deprotonation of the solvent better promotes elimination

reactions. However, despite the solvent e↵ects, it is useful to find the branching ratio

between these two competing pathways in 1230xa reaction mechanism and their e↵ect in

the final model yield and selectivity.

3.7.4 Expand 1230xa modeling to fluorination reactions

Fluorocarbons are manufactured by the controlled fluorination of chlorinated organic com-

pounds. 1230xa is an intermediate in processing new low global warming potential re-

frigerants. After building a reliable and predictive model for 1230xa production and

introducing the factors that can influence the selectivity and yield of 1230xa, the next

interest will be performing similar modeling procedure for the fluorination and dehydroflu-

orination of 1230xa. Figure 3.27 provides the overview for the next step of the project;

building fluorination model based on the 1230xa detailed reaction mechanism.

CF3CFClCH3 244bb

CF3CF=CH2 1234yf Used as

refrigerant

CCl2=CClCH2Cl 1230xa

CCl2=CHCH2Cl 1240za

CCl3CHClCH2Cl 240db

CCl3CH2CH2Cl 250fb

CH2=CH2 + CCl4

CH2ClCCl2CHCl2 240aa

CH3CH=CH2

CH2ClCH2ClCH3 1,2-DCP

CH2ClCH=CH2 Allyl chloride

CH2ClCCl=CHCl 1240xd

CH2ClCCl2CH2Cl 250aa

CH2ClCHClCH2Cl 1,2,3-TCP

CH2=CClCH2Cl 1250xf

CCl3CH2CHCl2 240fa CH2=CHCl +

CCl4

+Cl2

+Cl2

+Cl2

-HCl

-HCl

-HCl

-HCl

-HCl

-HCl +HF

-HCl

CH3CCl2Cl3 240ab

CCl2=CCl2 + CH3Cl

-HCl

CF3CCl=CH2 1233xf

+HF

+Cl2

! CHCl2CH=CCl

2

1230za

! CCl3CH=CHCl

1230zd

-HCl -HCl

+Cl2

Figure 3.27: One step closer to understanding the production of fluorocar-bons refrigerants from chlorinated feedstocks.

122

Chapter 4

References

123

Bibliography

[1] Zhang, M.; Chen, H.-P.; Gao, Y.; he, R.-X.; Yang, H.-P.; Wang, X.-H.; Zhang, S.-H.BioResources 2010, 5, 135–146.

[2] Chhiti, Y. Non catalytic steam gasification of wood bio-oil. Ph.D. thesis, Universitede Toulouse, Toulouse, 2011.

[3] Zhang, X.; Yang, W.; Blasiak, W. Journal of Analytical and Applied Pyrolysis 2012,96, 110–119.

[4] Beste, A.; Buchanan III, A. The Journal of organic chemistry 2009, 74, 2837–2841.

[5] Britt, P. F.; Buchanan, A. I.; Malcolm, E. A. The Journal of Organic Chemistry1995, 60, 6523–6536.

[6] Britt, P. F.; Buchanan, A.; Cooney, M. J.; Martineau, D. R. The Journal of organicchemistry 2000, 65, 1376–1389.

[7] Britt, P. F.; Kidder, M. K.; Buchanan Iii, A. Energy & Fuels 2007, 21, 3102–3108.

[8] Huang, J.; Liu, C.; Tong, H.; Li, W.; Wu, D. Computational and Theoretical Chem-istry 2012, 1001, 44–50.

[9] Tran, L. S.; Sirjean, B.; Glaude, P.-A.; Fournet, R.; Battin-Leclerc, F. Energy 2012,43, 4–18.

[10] Gao, C.; Allen, J. W.; Green, W. H.; West, R. H. Comput. Phys. Comm. 2015,submitted.

[11] Sirjean, B.; Glaude, P.-A.; Ruiz-Lopez, M.; Fournet, R. The Journal of PhysicalChemistry A 2006, 110, 12693–12704.

[12] Smith, L. Preparation of 1, 1, 2, 3-tetrachloropropene from 1, 2, 3-trichloropropane.1974; US Patent 3,823,195.

[13] Woodard, S. Process for producing 1,1,2,3-tetrachloropropene. 1985; https://www.google.com/patents/EP0131560A1?cl=en, EP Patent App. EP19,840,870,092.

[14] Woodard, S. S. Multistep from ethylene and carbon tetrachloride. 1987; US Patent4,650,914.

124

[15] Mukhopadhyay, S.; Nair, H.; Tung, H.; Van Der Puy, M.; Merkel, D.; Dubey, R.;Ma, J. J. Method for producing fluorinated organic compounds. 2006; US PatentApp. 11/592,761.

[16] Wilson, R. L.; Klausmeyer, R. L.; Dawkins, J. L.; Rohrback, D. D.; Strathe, J. S.;Branam, L. B. Methods of making chlorinated hydrocarbons. 2012; US Patent8,115,038.

[17] Nose, M.; Suzuki, A. Process for preparing 1, 1, 2, 3-tetrachloropropene. 2014; USPatent 8,791,311.

[18] Chen, C.-J.; Wong, D.; Bozzelli, J. W. The Journal of Physical Chemistry A 1998,102, 4551–4558.

[19] Senkan, S. M.; Quam, D. The Journal of Physical Chemistry 1992, 96, 10837–10842.

[20] Bryukov, M. G.; Slagle, I. R.; Knyazev, V. D. The Journal of Physical ChemistryA 2001, 105, 3107–3122.

[21] Louis, F.; Gonzalez, C. A.; Sawerysyn, J.-P. The Journal of Physical Chemistry A2004, 108, 10586–10593.

[22] Ranzi, E.; Cuoci, A.; Faravelli, T.; Frassoldati, A.; Migliavacca, G.; Pierucci, S.;Sommariva, S. Energy & Fuels 2008, 22, 4292–4300.

[23] Cillien, C.; Goldfinger, P.; Huybrechts, G.; Martens, G. Transactions of the FaradaySociety 1967, 63, 1631–1635.

[24] Volk, T.; Abrahamson, L.; White, E.; Neuhauser, E.; Gray, E.; Demeter, C.; Lindsey,Proceedings of Bioenergy 2000, 2000 .

[25] Briens, C.; Piskorz, J.; Berruti, F. International Journal of Chemical Reactor En-gineering 2008, 6 .

[26] Xu, R. Development of advanced technologies for biomass pyrolysis ; 2010.

[27] Hosoya, T.; Kawamoto, H.; Saka, S. Journal of Analytical and Applied Pyrolysis2007, 78, 328–336.

[28] Wang, S.-r.; Tan, H.; Luo, Z.-y.; Wang, L.; Cen, K. Journal of Zhejiang University(Engineering Science) 2006, 40, 419.

[29] Yang, H.; Yan, R.; Chen, H.; Lee, D. H.; Zheng, C. Fuel 2007, 86, 1781–1788.

[30] Peng, Y.; Wu, S. Cellulose Chemistry and Technology 2011, 45, 605.

[31] Bertero, M.; de la Puente, G.; Sedran, U. Fuel 2012, 95, 263–271.

[32] Latifi, M. Gasification of Bio-oils to Syngas in Fluidized Bed Reactors. Ph.D. thesis,University of Western Ontario, 2012.

125

[33] van Rossum, G.; Kersten, S. R. A.; van Swaaij, W. P. M. Industrial & EngineeringChemistry Research 2007, 46, 3959–3967.

[34] ADJAYE, J.; BAKHSHI, N. Biomass and Bioenergy 1995, 8, 265–277.

[35] Asadullah, M.; Rahman, M. A.; Ali, M. M.; Rahman, M.; Motin, M.; Sultan, M.;Alam, M. Fuel 2007, 86, 2514–2520.

[36] Carstensen, H.-H.; Dean, A. M. Computational Modeling in Lignocellulosic BiofuelProduction; Oxford University Press UK, 2010; Chapter 10, pp 201–243.

[37] Faravelli, T.; Frassoldati, A.; Migliavacca, G.; Ranzi, E. Biomass and Bioenergy2010, 34, 290–301.

[38] Dupont, C.; Chen, L.; Cances, J.; Commandre, J.-M.; Cuoci, A.; Pierucci, S.;Ranzi, E. Journal of Analytical and Applied Pyrolysis 2009, 85, 260–267.

[39] Calonaci, M.; Grana, R.; Barker Hemings, E.; Bozzano, G.; Dente, M.; Ranzi, E.Energy & Fuels 2010, 24, 5727–5734.

[40] Shafizadeh, F.; Furneaux, R. H.; Cochran, T. G.; Scholl, J. P.; Sakai, Y. Journal ofApplied Polymer Science 1979, 23, 3525–3539.

[41] Kawamoto, H.; Murayama, M.; Saka, S. Journal of Wood Science 2003, 49, 469–473.

[42] Kawamoto, H.; Saka, S. Journal of analytical and applied pyrolysis 2006, 76, 280–284.

[43] Banyasz, J.; Li, S.; Lyons-Hart, J.; Shafer, K. Fuel 2001, 80, 1757–1763.

[44] Banyasz, J. L.; Li, S.; Lyons-Hart, J. L.; Shafer, K. H. Journal of Analytical andApplied Pyrolysis 2001, 57, 223–248.

[45] Zhang, X.; Li, J.; Yang, W.; Blasiak, W. Energy & Fuels 2011, 25, 3739–3746.

[46] Ingram, L.; Mohan, D.; Bricka, M.; Steele, P.; Strobel, D.; Crocker, D.; Mitchell, B.;Mohammad, J.; Cantrell, K.; Pittman Jr, C. U. Energy & Fuels 2007, 22, 614–625.

[47] Thangalazhy-Gopakumar, S.; Adhikari, S.; Ravindran, H.; Gupta, R. B.; Fasina, O.;Tu, M.; Fernando, S. D. Bioresource technology 2010, 101, 8389–8395.

[48] Jarvis, M. W.; Daily, J. W.; Carstensen, H.-H.; Dean, A. M.; Sharma, S.; Day-ton, D. C.; Robichaud, D. J.; Nimlos, M. R. The Journal of Physical Chemistry A2011, 115, 428–438.

[49] Sun, R.; Fang, J.; Tomkinson, J. Journal of wood chemistry and technology 1999,19, 335–356.

126

[50] Kotake, T.; Kawamoto, H.; Saka, S. Journal of Analytical and Applied Pyrolysis2014, 105, 309–316.

[51] Zhou, H.; Wu, C.; Meng, A.; Zhang, Y.; Williams, P. T. Journal of Analytical andApplied Pyrolysis 2014, 110, 264–269.

[52] Shen, D.; Gu, S.; Bridgwater, A. V. Journal of Analytical and Applied Pyrolysis2010, 87, 199–206.

[53] Di Blasi, C.; Lanzetta, M. Journal of Analytical and Applied Pyrolysis 1997, 40,287–303.

[54] Battin-Leclerc, F.; Blurock, E.; Bounaceur, R.; Fournet, R.; Glaude, P.-A.; Herbi-net, O.; Sirjean, B.; Warth, V. Chemical Society Reviews 2011, 40, 4762–4782.

[55] Susnow, R. G.; Dean, A. M.; Green, W. H.; Peczak, P.; Broadbelt, L. J. The Journalof Physical Chemistry A 1997, 101, 3731–3740.

[56] West, R. H.; Allen, J. W.; Green, W. H. 2011 AIChE Annual Meeting proceeding2011,

[57] Green, W. H. et al. rmg.sourceforge.net 2013,

[58] Song, J.; Stephanopoulos, G.; Green, W. H. Chem. Eng. Sci. 2002, 57, 4475–4491.

[59] Benson, S. W. Thermochemical kinetics: methods for the estimation of thermochem-ical data and rate parameters ; Wiley New York, 1976.

[60] Landrum, G. Online). http://www. rdkit. org. Accessed 2006, 3, 2012.

[61] Stewart, J. J. MOPAC: a semiempirical molecular orbital program. 1990; http://openmopac.net/.

[62] Gaussian 98, revision A. 7; Gaussian. 1998.

[63] Sumathi, R.; Carstensen, H. H.; Green, W. H. J. Phys. Chem. A 2001, 105, 6910–6925.

[64] Sumathi, R.; Carstensen, H. H.; Green, W. H. J. Phys. Chem. A 2001, 105, 8969–8984.

[65] Song, J. Building robust chemical reaction mechanisms: next generation of auto-matic model construction software. Ph.D. thesis, Massachusetts Institute of Tech-nology, 2004.

[66] Goodwin, D.; Malaya, N.; Mo↵at, H.; Speth, R. 2013,

[67] Kee, R. J.; Rupley, F. M.; Miller, J. A. Chemkin-II: A Fortran chemical kineticspackage for the analysis of gas-phase chemical kinetics ; 1989.

127

[68] SCons: A software construction tool. http://www.scons.org/.

[69] Branca, C.; Giudicianni, P.; Di Blasi, C. Industrial & Engineering Chemistry Re-search 2003, 42, 3190–3202.

[70] Zhang, L.; Kong, S.-C. Fuel 2012, 95, 471–480.

[71] Jones, E.; Oliphant, T.; Peterson, P. SciPy: Open source scientific tools for Python.2001.

[72] Lopez, J. G.; Rasmussen, C. L.; Alzueta, M. U.; Gao, Y.; Marshall, P.; Glarborg, P.Proceedings of the Combustion Institute 2009, 32, 367–375.

[73] Doolan, K.; Mackie, J.; Reid, C. International Journal of Chemical Kinetics 1986,18, 575–596.

[74] Frey, H. Journal of the Chemical Society 1962, 2293–2297.

[75] Chong, D. P.; Kistiakowsky, G. B. The Journal of Physical Chemistry 1964, 68,1793–1797.

[76] Wurzenberger, J. C.; Wallner, S.; Raupenstrauch, H.; Khinast, J. G. AIChE Journal2002, 48, 2398–2411.

[77] Nunn, T. R.; Howard, J. B.; Longwell, J. P.; Peters, W. A. Industrial & EngineeringChemistry Process Design and Development 1985, 24, 836–844.

[78] Grieco, E.; Baldi, G. Chemical Engineering Science 2011, 66, 650–660.

[79] Radmanesh, R.; Courbariaux, Y.; Chaouki, J.; Guy, C. Fuel 2006, 85, 1211–1220.

[80] Ranzi, E.; Sogaro, A.; Ga↵uri, P.; Pennati, G.; Westbrook, C. K.; Pitz, W. J.Combustion and Flame 1994, 99, 201–211.

[81] Ranzi, E.; Dente, M.; Goldaniga, A.; Bozzano, G.; Faravelli, T. Progress in Energyand Combustion Science 2001, 27, 99–139.

[82] Ovchinnikov, V. Chemistry Journal 2013, 2, 59–65.

[83] Magoon, G. R.; Green, W. H. Computers & Chemical Engineering 2013, 52, 35–45.

[84] Zaheeruddin, M.; Lodhi, Z. Phys. Chem.(Peshawar Pak.) 1991, 10, 111.

[85] Rocha, I. M.; Galvao, T. L.; Sapei, E.; Ribeiro da Silva, M. D.; Ribeiro daSilva, M. A. Journal of Chemical & Engineering Data 2013, 58, 1813–1821.

[86] Matos, M. A. R.; Miranda, M. S.; Morais, V. M. Journal of Chemical & EngineeringData 2003, 48, 669–679.

128

[87] Glaude, P.; Battin-Leclerc, F.; Judenherc, B.; Warth, V.; Fournet, R.; Come, G.;Scacchi, G.; Dagaut, P.; Cathonnet, M. Combustion and flame 2000, 121, 345–355.

[88] Moss, J. T.; Berkowitz, A. M.; Oehlschlaeger, M. A.; Biet, J.; Warth, V.; Glaude, P.-A.; Battin-Leclerc, F. The Journal of Physical Chemistry A 2008, 112, 10843–10855.

[89] Glaude, P. A.; Herbinet, O.; Bax, S.; Biet, J.; Warth, V.; Battin-Leclerc, F. Com-bustion and flame 2010, 157, 2035–2050.

[90] Muller, C.; Michel, V.; Scacchi, G.; Come, G.-M. Journal de chimie physique 1995,92, 1154–1178.

[91] Come, G.; Warth, V.; Glaude, P.; Fournet, R.; Battin-Leclerc, F.; Scacchi, G.Computer-aided design of gas-phase oxidation mechanismsapplication to the mod-eling of n-heptane and iso-octane oxidation. 1996.

[92] Heyberger, B.; Belmekki, N.; Conraud, V.; Glaude, P.-A.; Fournet, R.; Battin-Leclerc, F. International journal of chemical kinetics 2002, 34, 666–677.

[93] Ingham, T.; Walker, R.; Woolford, R. Kinetic parameters for the initiation reactionRH+ O2 R+ HO2. 1994.

[94] Buda, F.; Bounaceur, R.; Warth, V.; Glaude, P.-A.; Fournet, R.; Battin-Leclerc, F.Combustion and flame 2005, 142, 170–186.

[95] Dean, A. M.; Bozzelli, J. W. Gas-phase combustion chemistry ; Springer, 2000; pp125–341.

[96] Luo, Y.-R. Handbook of bond dissociation energies in organic compounds ; CRCpress, 2002.

[97] Mereau, R.; Rayez, M.-T.; Rayez, J.-C.; Caralp, F.; Lesclaux, R. Physical ChemistryChemical Physics 2001, 3, 4712–4717.

[98] Wiberg, K. B.; Waldron, R. F. Journal of the American Chemical Society 1991,113, 7697–7705.

[99] Buda, F.; Heyberger, B.; Fournet, R.; Glaude, P.-A.; Warth, V.; Battin-Leclerc, F.Energy & fuels 2006, 20, 1450–1459.

[100] Cavallotti, C.; Rota, R.; Faravelli, T.; Ranzi, E. Proceedings of the CombustionInstitute 2007, 31, 201–209.

[101] Silke, E. J.; Pitz, W. J.; Westbrook, C. K.; Ribaucour, M. The Journal of PhysicalChemistry A 2007, 111, 3761–3775.

[102] Sirjean, B.; Buda, F.; Hakka, H.; Glaude, P.-A.; Fournet, R.; Warth, V.; Battin-Leclerc, F.; Ruiz-Lopez, M. Proceedings of the Combustion Institute 2007, 31, 277–284.

129

[103] Sirjean, B.; Glaude, P.-A.; Ruiz-Lopez, M.; Fournet, R. The Journal of PhysicalChemistry A 2008, 112, 11598–11610.

[104] Truhlar, D. G.; Isaacson, A. D.; Garrett, B. C. Generalized transition state theory.1985.

[105] Miller, W. H. The Journal of Physical Chemistry A 1998, 102, 793–806.

[106] Sumathi, R.; Green Jr, W. H. Theoretical Chemistry Accounts 2002, 108, 187–213.

[107] Pople, J. A.; Head-Gordon, M.; Fox, D. J.; Raghavachari, K.; Curtiss, L. A. TheJournal of Chemical Physics 1989, 90, 5622–5629.

[108] Curtiss, L. A.; Jones, C.; Trucks, G. W.; Raghavachari, K.; Pople, J. A. The Journalof Chemical Physics 1990, 93, 2537–2545.

[109] Curtiss, L. A.; Raghavachari, K.; Trucks, G. W.; Pople, J. A. The Journal of chem-ical physics 1991, 94, 7221–7230.

[110] Curtiss, L. A.; Raghavachari, K.; Pople, J. A. The Journal of chemical physics 1993,98, 1293–1298.

[111] Curtiss, L. A.; Raghavachari, K.; Redfern, P. C.; Rassolov, V.; Pople, J. A. TheJournal of chemical physics 1998, 109, 7764–7776.

[112] Curtiss, L. A.; Redfern, P. C.; Raghavachari, K.; Rassolov, V.; Pople, J. A. TheJournal of chemical physics 1999, 110, 4703–4709.

[113] Baboul, A. G.; Curtiss, L. A.; Redfern, P. C.; Raghavachari, K. The Journal ofchemical physics 1999, 110, 7650.

[114] Curtiss, L. A.; Raghavachari, K.; Redfern, P. C.; Pople, J. A. The Journal of Chem-ical Physics 2000, 112, 1125–1132.

[115] Ochterski, J. W.; Petersson, G. A.; Montgomery Jr, J. A. The Journal of chemicalphysics 1996, 104, 2598–2619.

[116] Montgomery Jr, J. A.; Frisch, M. J.; Ochterski, J. W.; Petersson, G. A. The Journalof chemical physics 1999, 110, 2822–2827.

[117] Mayer, P. M.; Parkinson, C. J.; Smith, D. M.; Radom, L. The Journal of chemicalphysics 1998, 108, 604–615.

[118] Parr, R. G.; Yang, W. Density-functional theory of atoms and molecules ; Oxforduniversity press, 1989; Vol. 16.

[119] Pople, J. A.; Head-Gordon, M.; Raghavachari, K. The Journal of chemical physics1987, 87, 5968–5975.

130

[120] Andersson, K.; Borowski, P.; Fowler, P.; Malmqvist, P.-A.; Roos, B.; Sadlej, A.Chemical physics letters 1992, 190, 367–373.

[121] Werner, H.-J.; Knowles, P. J. The Journal of chemical physics 1988, 89, 5803–5814.

[122] Knowles, P. J.; Werner, H.-J. Chemical physics letters 1988, 145, 514–522.

[123] Martin, J. M.; de Oliveira, G. The Journal of chemical physics 1999, 111, 1843–1856.

[124] Sirjean, B.; Fournet, R.; Glaude, P.-A.; Ruiz-Lopez, M. F. Chemical physics letters2007, 435, 152–156.

[125] Lewars, E. G. Computational chemistry: introduction to the theory and applicationsof molecular and quantum mechanics ; Springer Science & Business Media, 2010.

[126] Eyring, H. The Journal of Chemical Physics 1935, 3, 107–115.

[127] Cohen, N. International Journal of Chemical Kinetics 1991, 23, 683–700.

[128] Willems, P. A.; Froment, G. F. Industrial & Engineering Chemistry Research 1988,27, 1959–1966.

[129] Willems, P. A.; Froment, G. F. Industrial & engineering chemistry research 1988,27, 1966–1971.

[130] Carstensen, H.-H.; Dean, A. M. The Journal of Physical Chemistry A 2008, 113,367–380.

[131] Hammett, L. P. Journal of the American Chemical Society 1937, 59, 96–103.

[132] Taft Jr, R. W. Journal of the American Chemical Society 1952, 74, 3120–3128.

[133] Truong, T. N. The Journal of Chemical Physics 2000, 113, 4957–4964.

[134] Zhang, S.; Truong, T. N. The Journal of Physical Chemistry A 2003, 107, 1138–1147.

[135] Seyedzadeh Khanshan, F.; West, R. H. Fuel 2015,

[136] Becke, A. D. The Journal of chemical physics 1993, 98, 5648–5652.

[137] Sharma, S.; Harper, M.; Green, W. Massachusetts Institute of Technology, Cam-bridge, MA 2010,

[138] Halls, M. D.; Velkovski, J.; Schlegel, H. B. Harmonic frequency scaling factors forHartree-Fock, S-VWN, B-LYP, B3-LYP, B3-PW91 and MP2 with the Sadlej pVTZelectric property basis set. 2001.

131

[139] Mayes, H. B.; Nolte, M. W.; Beckham, G. T.; Shanks, B. H.; Broadbelt, L. J. ACSSustainable Chemistry & Engineering 2014, 2, 1461–1473.

[140] Gonzalez, C.; Schlegel, H. B. The Journal of Chemical Physics 1989, 90, 2154–2161.

[141] Riddell, F. G. The conformational analysis of heterocyclic compounds ; AcademicPr, 1980.

[142] Kiefer, J.; Gupte, K.; Harding, L.; Klippenstein, S. The Journal of Physical Chem-istry A 2009, 113, 13570–13583.

[143] Ho↵mann, H. Angewandte Chemie International Edition in English 1969, 8, 556–577.

[144] Dewar, M. J.; Zoebisch, E. G.; Healy, E. F.; Stewart, J. J. Journal of the AmericanChemical Society 1985, 107, 3902–3909.

[145] Zhu, L.; Bozzelli, J. W.; Lay, T. H. Industrial & engineering chemistry research1998, 37, 3497–3507.

[146] Cohen, N.; Benson, S. Chemical Reviews 1993, 93, 2419–2438.

[147] Cohen, N. Journal of Physical and Chemical Reference Data 1996, 25, 1411–1481.

[148] Wong, D. K.; Kretkowski, D. A.; Bozzelli, J. W. Industrial & engineering chemistryresearch 1993, 32, 3184–3188.

[149] Wu, Y.; Patel, S.; Ritter, E.; Bozzelli, J. Thermochimica acta 1993, 222, 153–185.

[150] Seetula, J. A.; Slagle, I. R. Journal of the Chemical Society, Faraday Transactions1997, 93, 1709–1719.

[151] Hudgens, J. W.; Johnson III, R. D.; Timonen, R.; Seetula, J.; Gutman, D. TheJournal of Physical Chemistry 1991, 95, 4400–4405.

[152] Seetula, J. A. Journal of the Chemical Society, Faraday Transactions 1996, 92,3069–3078.

[153] Atkinson, R. Chemical Reviews 1986, 86, 69–201.

[154] Atkinson, R. International journal of chemical kinetics 1987, 19, 799–828.

[155] Lewis, G. N. Journal of the American Chemical Society 1916, 38, 762–785.

[156] Cloud, C.; Schwartz, M. Journal of computational chemistry 2003, 24, 640–646.

[157] Manion, J. A. Journal of Physical and Chemical Reference Data 2002, 31, 123–172.

[158] Benson, S. W.; Kistiakowsky, G. B. Journal of the American Chemical Society 1942,64, 80–86.

132

[159] Lay, T. H.; Bozzelli, J. W.; Dean, A. M.; Ritter, E. R. The Journal of PhysicalChemistry 1995, 99, 14514–14527.

[160] Petersson, G. A.; Malick, D. K.; Wilson, W. G.; Ochterski, J. W.; Mont-gomery Jr, J. A.; Frisch, M. J. The Journal of chemical physics 1998, 109, 10570–10579.

[161] Bokhan, D.; Bernadotte, S.; Ten-no, S. Chemical Physics Letters 2009, 469, 214–218.

[162] Peterson, K. A.; Adler, T. B.; Werner, H.-J. The Journal of chemical physics 2008,128, 084102.

[163] Neese, F. Wiley Interdisciplinary Reviews: Computational Molecular Science 2012,2, 73–78.

[164] Zhao, Y.; Truhlar, D. G. Theoretical Chemistry Accounts 2008, 120, 215–241.

[165] Bhoorasingh, P. L.; West, R. H. Physical Chemistry Chemical Physics 2015, 17,32173–32182.

[166] Jalan, A.; West, R. H.; Green, W. H. The Journal of Physical Chemistry B 2013,117, 2955–2970.

[167] Slakman, B. L.; West, R. H. 2015 AIChE Annual Meeting.

133

Appendices

134

Appendix A

The largest mechanism for bio-oilgasification generated in RMG-Java

The largest mechanism for bio-oil gasification generated in RMG-Java is attached as atext file in supplementary material.

135

Appendix B

Transition State Geometries ofHeterocyclic Compounds Reactions

Reaction Transition state geometryC"""""""""""1.02896"""""""""0.66996""""""""*0.27695"C""""""""""*0.22112"""""""""1.23646"""""""""0.23816"C""""""""""*1.34150"""""""""0.12500""""""""*0.08746"C""""""""""*0.68723""""""""*1.21933""""""""*0.07065"C"""""""""""1.34563""""""""*0.63637"""""""""0.21690"H"""""""""""0.53159""""""""*0.55685""""""""*0.70576"H"""""""""""1.66294"""""""""1.15857""""""""*1.00250"H""""""""""*0.47511"""""""""2.19746""""""""*0.21175"H""""""""""*0.22464"""""""""1.36484"""""""""1.32978"H""""""""""*2.13680"""""""""0.19807"""""""""0.65401"H""""""""""*1.76767"""""""""0.35961""""""""*1.06413"H""""""""""*0.83466""""""""*1.80540"""""""""0.83617"H""""""""""*0.84529""""""""*1.84944""""""""*0.94835"H"""""""""""1.19457""""""""*0.92699"""""""""1.25852"H"""""""""""2.14666""""""""*1.19417""""""""*0.26599"

NH

NH

C"""""""""""1.06510"""""""""0.56867""""""""*0.18975"C""""""""""*1.31535"""""""""0.21473"""""""""0.17994"C""""""""""*0.88237""""""""*1.09158""""""""*0.28027"C"""""""""""1.29328""""""""*0.75932"""""""""0.29298"H"""""""""""0.77818""""""""*0.58369""""""""*0.83453"H"""""""""""1.83000"""""""""1.10005""""""""*0.74136"H""""""""""*1.69625"""""""""0.21368"""""""""1.20200"H""""""""""*2.04086"""""""""0.71978""""""""*0.46362"H""""""""""*1.23870""""""""*1.96088"""""""""0.26423"H""""""""""*0.87564""""""""*1.25924""""""""*1.36003"H"""""""""""0.94717""""""""*1.14549"""""""""1.24605"H"""""""""""2.22847""""""""*1.21049""""""""*0.03800"N""""""""""*0.08995"""""""""1.21704"""""""""0.16485"H""""""""""*0.26671"""""""""2.01199""""""""*0.44607"

136

O

O

C"""""""""""1.15582""""""""(0.69726"""""""""0.37174"C"""""""""""1.55170"""""""""0.71994""""""""(0.01420"C""""""""""(0.53242"""""""""1.49685""""""""(0.32007"C""""""""""(1.30867"""""""""0.52392"""""""""0.40961"C""""""""""(1.19479""""""""(0.90582""""""""(0.05523"H""""""""""(0.57317"""""""""2.53450""""""""(0.01030"H"""""""""""2.23683"""""""""1.21220"""""""""0.67942"H"""""""""""1.86224"""""""""0.81043""""""""(1.05212"H"""""""""""0.78260""""""""(0.72896"""""""""1.41161"H"""""""""""0.01679"""""""""0.88280"""""""""0.61501"H""""""""""(1.89218"""""""""0.81257"""""""""1.27151"H""""""""""(1.82447""""""""(1.13651""""""""(0.92515"H""""""""""(1.48072""""""""(1.59345"""""""""0.75437"H"""""""""""1.99785""""""""(1.39740"""""""""0.33695"H""""""""""(0.30516"""""""""1.33676""""""""(1.36592"O"""""""""""0.14369""""""""(1.19484""""""""(0.50831"

O

O

C""""""""""#1.12932"""""""""0.30087"""""""""0.22054"C"""""""""""1.66232"""""""""0.31836""""""""#0.21648"C"""""""""""1.18672""""""""#0.78091"""""""""0.37221"C""""""""""#1.14304""""""""#0.98842""""""""#0.40690"H""""""""""#0.77594""""""""#0.40679"""""""""1.10946"H""""""""""#2.08795"""""""""0.44944"""""""""0.79431"H"""""""""""1.88307"""""""""0.34661""""""""#1.27744"H"""""""""""1.83382"""""""""1.23293"""""""""0.33200"H"""""""""""1.20888""""""""#1.75687""""""""#0.10187"H"""""""""""1.01508""""""""#0.81244"""""""""1.44505"H""""""""""#0.61115""""""""#1.24529""""""""#1.31377"H""""""""""#1.80013""""""""#1.73688"""""""""0.02543"O""""""""""#0.51572"""""""""1.35373""""""""#0.10368"C""""""""""#1.17593""""""""#0.66657""""""""#0.45797"C""""""""""#1.60089"""""""""0.69189"""""""""0.07585"C"""""""""""0.49071"""""""""1.55055"""""""""0.33764"C"""""""""""1.26360"""""""""0.60241""""""""#0.42042"C"""""""""""1.31988""""""""#0.82949"""""""""0.04463"C""""""""""#0.10027""""""""#1.33833"""""""""0.42006"H"""""""""""0.49000"""""""""2.58718"""""""""0.02113"H""""""""""#2.31524"""""""""1.23712""""""""#0.54240"H""""""""""#1.87160"""""""""0.69528"""""""""1.12988"H""""""""""#0.31732""""""""#1.13016"""""""""1.47308"H""""""""""#0.75760""""""""#0.55594""""""""#1.47500"H""""""""""#0.07610"""""""""0.91723""""""""#0.56598"H"""""""""""1.82782"""""""""0.95006""""""""#1.27446"H"""""""""""2.00237""""""""#0.97052"""""""""0.89809"H"""""""""""1.71536""""""""#1.44635""""""""#0.76849"H""""""""""#0.13473""""""""#2.42537"""""""""0.31022"H""""""""""#2.04354""""""""#1.32377""""""""#0.59778"H"""""""""""0.29792"""""""""1.40256"""""""""1.39303"

137

HN

NH

C"""""""""""1.11255""""""""'0.76238"""""""""0.38086"C"""""""""""1.62137"""""""""0.62351""""""""'0.00626"C""""""""""'0.39916"""""""""1.53458""""""""'0.36362"C""""""""""'1.24529"""""""""0.65418"""""""""0.40055"C""""""""""'1.30546""""""""'0.79641""""""""'0.00583"H""""""""""'0.36283"""""""""2.58221""""""""'0.08835"H"""""""""""2.32001"""""""""1.07159"""""""""0.70413"H"""""""""""1.96473"""""""""0.68203""""""""'1.03631"H"""""""""""0.77545""""""""'0.75882"""""""""1.43623"H"""""""""""0.10706"""""""""0.91237"""""""""0.59283"H""""""""""'1.82180"""""""""1.03930"""""""""1.22875"H""""""""""'2.03969""""""""'0.98908""""""""'0.80537"H""""""""""'1.61887""""""""'1.39661"""""""""0.86711"H"""""""""""1.92261""""""""'1.50067"""""""""0.34716"H""""""""""'0.17452"""""""""1.31711""""""""'1.39871"N"""""""""""0.02416""""""""'1.18508""""""""'0.51601"H"""""""""""0.05468""""""""'2.18482""""""""'0.66957"

HO

OH

OH

OH

OH

OOH

OH

OH

HO

O""""""""""#3.53855""""""""#0.48759""""""""#0.64939"C""""""""""#2.18101""""""""#0.36251""""""""#0.44168"C""""""""""#1.57714"""""""""0.86694""""""""#0.17325"O""""""""""#0.47182""""""""#1.25200"""""""""1.16641"C"""""""""""0.31937""""""""#1.65795"""""""""0.30010"O"""""""""""2.61011""""""""#1.42527""""""""#0.44800"C"""""""""""1.03936"""""""""0.42812""""""""#0.61238"O"""""""""""2.15884"""""""""1.29609""""""""#0.78826"C""""""""""#0.12838"""""""""1.26745""""""""#0.03084"O"""""""""""0.15804"""""""""1.61044"""""""""1.33582"H""""""""""#1.60356""""""""#1.10985""""""""#1.03762"H""""""""""#1.72808""""""""#1.02425"""""""""0.58068"H""""""""""#2.24108"""""""""1.68682"""""""""0.10148"H"""""""""""3.20207""""""""#0.71794""""""""#0.73352"H"""""""""""0.78912"""""""""0.05834""""""""#1.60861"H"""""""""""2.28753"""""""""1.74683"""""""""0.05752"H""""""""""#0.04334"""""""""2.22504""""""""#0.55930"H""""""""""#0.05055"""""""""0.81584"""""""""1.85070"C"""""""""""1.55523""""""""#0.79700"""""""""0.23137"H"""""""""""1.86752""""""""#0.43098"""""""""1.22343"H""""""""""#3.97719"""""""""0.34643""""""""#0.44731"

138

O

OH

OH

OH

OH

O OH

OH

OH

HO

C"""""""""""1.62601""""""""(2.38050""""""""(0.17079"C"""""""""""0.85049""""""""(1.29795""""""""(0.02287"O""""""""""(0.52033""""""""(1.52779"""""""""0.13549"C""""""""""(1.49950""""""""(0.55931""""""""(0.26982"O""""""""""(2.76447""""""""(1.13634""""""""(0.10070"C""""""""""(1.29882"""""""""0.72599"""""""""0.49833"O""""""""""(2.04708"""""""""1.79881"""""""""0.01301"C"""""""""""0.66215"""""""""1.21846""""""""(0.42880"O"""""""""""1.20738"""""""""2.41301""""""""(0.18444"C"""""""""""1.37048"""""""""0.06548"""""""""0.13595"O"""""""""""2.74412"""""""""0.26112"""""""""0.34518"H"""""""""""1.18217""""""""(3.36551""""""""(0.20320"H"""""""""""2.70269""""""""(2.29393""""""""(0.17933"H""""""""""(1.42377""""""""(0.37264""""""""(1.34962"H""""""""""(2.83746""""""""(1.39708"""""""""0.82650"H""""""""""(1.38346"""""""""0.57838"""""""""1.58864"H""""""""""(2.94056"""""""""1.48270""""""""(0.17813"H"""""""""""0.01837"""""""""1.27875""""""""(1.30826"H"""""""""""1.98740"""""""""2.26429"""""""""0.38034"H"""""""""""3.21867"""""""""0.05363""""""""(0.47492"H"""""""""""0.25401"""""""""0.66797"""""""""0.77766"C""""""""""#0.60479""""""""#1.30847"""""""""0.46489"C""""""""""#1.84878""""""""#0.65873""""""""#0.12234"C""""""""""#1.25616"""""""""1.39838"""""""""0.08427"C"""""""""""0.65566""""""""#1.35471""""""""#0.44465"C"""""""""""0.10160"""""""""1.50911""""""""#0.37840"C"""""""""""1.79046""""""""#0.40006""""""""#0.02522"C"""""""""""1.27839"""""""""0.99928"""""""""0.40321"H""""""""""#0.35865""""""""#0.81968"""""""""1.41546"H""""""""""#2.10393""""""""#0.99599""""""""#1.13127"H""""""""""#1.44473"""""""""1.25449"""""""""1.14452"H""""""""""#0.84694"""""""""0.48345""""""""#0.62457"H"""""""""""0.36620""""""""#1.13850""""""""#1.47878"H"""""""""""2.49169""""""""#0.30335""""""""#0.86193"H""""""""""#0.84689""""""""#2.34015"""""""""0.75327"H""""""""""#2.72023""""""""#0.67690"""""""""0.53189"H""""""""""#2.02697"""""""""1.94201""""""""#0.44919"H"""""""""""1.05003""""""""#2.37504""""""""#0.46427"H"""""""""""0.26019"""""""""2.01666""""""""#1.32227"H"""""""""""2.36091""""""""#0.83766"""""""""0.80283"H"""""""""""2.10672"""""""""1.71346"""""""""0.32525"H"""""""""""1.01429"""""""""0.96838"""""""""1.46852"

139

NHHN

C""""""""""#0.61218""""""""#1.31239"""""""""0.44095"C""""""""""#1.84024""""""""#0.61008""""""""#0.11418"C""""""""""#1.20898"""""""""1.41885"""""""""0.08213"C"""""""""""0.66323""""""""#1.32314""""""""#0.44222"C"""""""""""0.15404"""""""""1.49382""""""""#0.38788"C"""""""""""1.29283"""""""""0.93234"""""""""0.40383"H""""""""""#0.35185""""""""#0.89889"""""""""1.42136"H""""""""""#2.12324""""""""#0.91626""""""""#1.12527"H""""""""""#1.38572"""""""""1.29648"""""""""1.14681"H""""""""""#0.82530"""""""""0.48881""""""""#0.61529"H"""""""""""0.38114""""""""#1.07911""""""""#1.48157"H""""""""""#0.87310""""""""#2.35753"""""""""0.65149"H""""""""""#2.70098""""""""#0.61062"""""""""0.55311"H""""""""""#1.97163"""""""""1.97609""""""""#0.44879"H"""""""""""1.06980""""""""#2.33817""""""""#0.47050"H"""""""""""0.32724"""""""""1.96346""""""""#1.34859"H"""""""""""2.17851"""""""""1.56479"""""""""0.28627"H"""""""""""1.03756"""""""""0.96879"""""""""1.47185"N"""""""""""1.72245""""""""#0.45958"""""""""0.09113"H"""""""""""2.48827""""""""#0.43723""""""""#0.57457"

O

O

C""""""""""#0.64517""""""""#1.31311"""""""""0.41063"C""""""""""#1.84442""""""""#0.53728""""""""#0.10781"C""""""""""#1.14911"""""""""1.44085"""""""""0.11670"C"""""""""""0.65343""""""""#1.31452""""""""#0.44061"C"""""""""""0.20804"""""""""1.47661""""""""#0.38834"C"""""""""""1.33323"""""""""0.88183"""""""""0.36889"H""""""""""#0.38700""""""""#0.98609"""""""""1.42441"H""""""""""#2.14941""""""""#0.79827""""""""#1.12528"H""""""""""#1.29830"""""""""1.31712"""""""""1.18529"H""""""""""#0.81881"""""""""0.50424""""""""#0.59493"H"""""""""""0.41395""""""""#1.09164""""""""#1.49225"H""""""""""#0.94524""""""""#2.36266"""""""""0.53008"H""""""""""#2.70018""""""""#0.51837"""""""""0.56480"H""""""""""#1.90362"""""""""2.03406""""""""#0.38640"H"""""""""""1.08590""""""""#2.31683""""""""#0.42431"H"""""""""""0.37658"""""""""1.94350""""""""#1.35002"H"""""""""""2.25158"""""""""1.44849"""""""""0.19952"H"""""""""""1.12260"""""""""0.91066"""""""""1.44895"O"""""""""""1.70199""""""""#0.48631"""""""""0.03293"

140

OOH

OH

OH

HOO

O

OH

OH

OH

H

H

O"""""""""""1.64615"""""""""1.99595"""""""")0.18587"C"""""""""""0.94688"""""""""0.79597"""""""")0.54748"C"""""""""""1.42518"""""""")0.33814"""""""""0.39199"C"""""""""""1.54492"""""""")1.66884"""""""")0.36080"O"""""""""""0.27349"""""""")2.06235"""""""")0.68203"C"""""""""")0.80561"""""""")0.85379"""""""""0.94402"O"""""""""""0.38945"""""""")0.63037"""""""""1.41903"C"""""""""")1.31333"""""""")0.28492"""""""")0.28007"C"""""""""")0.59696"""""""""1.04898"""""""")0.50592"O"""""""""")0.90974"""""""""1.95590"""""""""0.54315"H"""""""""""1.69376"""""""""2.56648"""""""")0.96044"H"""""""""""1.22054"""""""""0.50596"""""""")1.56694"H"""""""""""2.29966"""""""")0.02344"""""""""0.95678"H"""""""""""2.03749"""""""")2.42021"""""""""0.27855"H"""""""""""2.21385"""""""")1.49374"""""""")1.22282"H"""""""""")1.44255"""""""")1.43434"""""""""1.60701"H"""""""""")0.91465"""""""""1.47054"""""""")1.46961"H"""""""""")0.12472"""""""""2.50917"""""""""0.66066"H"""""""""")0.63221"""""""")1.14007"""""""")0.92783"O"""""""""")2.72145"""""""")0.25428"""""""")0.35505"H"""""""""")2.98081"""""""")0.77475"""""""")1.11956"

O OH

OH

OH

HOO

O

OH

OH

OH

H

H

O""""""""""""""""0""""0.09643435""""2.80211738""".0.08683905""C""""""""""""""""0""""0.34416535""""1.43930638""".0.44057905""C""""""""""""""""0""""1.35317435""""0.74667338""""0.52233295""C""""""""""""""""0""""2.51186450""""0.49572613""".0.01101742""O""""""""""""""""0""""1.29803431""".1.63411208""".0.36324400""C""""""""""""""""0""""0.30415835""".1.18930262""""0.49302495""O""""""""""""""""0""""0.66841235""".0.16662462""""1.39041995""C""""""""""""""""0""".0.89143265""".0.77452662""".0.41330805""C""""""""""""""""0""".1.04864465""""0.75704438""".0.39904805""O""""""""""""""""0""".1.75784165""""1.13962738""""0.75814195""H""""""""""""""""0""""0.91684135""""3.29973038""".0.14574405""H""""""""""""""""0""""0.72966135""""1.39031338""".1.46765905""H""""""""""""""""0""""1.53944536""".0.73720107""""0.12642052""H""""""""""""""""0""""3.39224550""""0.26813213""""0.59844058""H""""""""""""""""0""""2.82999450""""0.83025913""".1.00130042""H""""""""""""""""0""""0.08306235""".2.09171262""""1.06525195""H""""""""""""""""0""".1.60261865""""1.06368438""".1.29719005""H""""""""""""""""0""".1.55402565""""2.07188938""""0.89949895""H""""""""""""""""0""".0.62863865""".1.08349962""".1.43328005""O""""""""""""""""0""".2.12018365""".1.35248662""".0.01035305""H""""""""""""""""0""".2.09666465""".2.28305862""".0.25227005"

141

C""""""""""#1.16300"""""""""0.75144"""""""""0.49244"H""""""""""#2.05044"""""""""1.39224"""""""""0.54140"H""""""""""#0.72202"""""""""0.72642"""""""""1.50032"C""""""""""#1.43841""""""""#0.65300"""""""""0.00663"H""""""""""#2.07929""""""""#1.25362"""""""""0.66179"H""""""""""#1.91541""""""""#0.61238""""""""#0.98269"C""""""""""#0.14319"""""""""1.22023""""""""#0.50051"H""""""""""#0.58925"""""""""1.38044""""""""#1.49487"H"""""""""""0.27805"""""""""2.21214""""""""#0.21462"C""""""""""#0.03892""""""""#1.24589""""""""#0.08395"H""""""""""#0.04293""""""""#2.12287""""""""#0.74964"H"""""""""""0.23455""""""""#1.63518"""""""""0.90254"C"""""""""""1.03690""""""""#0.34875""""""""#0.50863"H"""""""""""1.39521""""""""#0.35362""""""""#1.53900"C"""""""""""1.77868"""""""""0.11451"""""""""0.53745"H"""""""""""1.51909""""""""#0.17707"""""""""1.54815"H"""""""""""2.81035"""""""""0.43251"""""""""0.39613"H"""""""""""0.96972"""""""""0.97978""""""""#0.23009"

O HO

OHOH

OOH

OH

OH

O""""""""""#2.27925""""""""#0.33901""""""""#0.12634"C""""""""""#0.95783"""""""""0.08738""""""""#0.36232"C""""""""""#0.76741"""""""""1.54450"""""""""0.00988"O"""""""""""0.63591"""""""""1.71376"""""""""0.21825"C"""""""""""1.36377"""""""""0.00396"""""""""0.44591"O"""""""""""1.93080""""""""#0.22727""""""""#0.72745"C"""""""""""0.05476""""""""#0.65216"""""""""0.53125"O"""""""""""0.14653""""""""#2.02637"""""""""0.16641"H""""""""""#2.29273""""""""#1.29406""""""""#0.26289"H""""""""""#0.67085""""""""#0.08047""""""""#1.41082"H""""""""""#1.30312"""""""""1.76395"""""""""0.93878"H""""""""""#1.10530"""""""""2.23632""""""""#0.76535"H"""""""""""1.98016"""""""""0.20682"""""""""1.32247"H"""""""""""1.39073"""""""""0.98442""""""""#0.75132"H""""""""""#0.34667""""""""#0.63756"""""""""1.54969"H"""""""""""0.71618""""""""#2.05033""""""""#0.61584"

HN

H2N

C""""""""""#1.40821""""""""#0.57584""""""""#0.36366"H""""""""""#2.36471""""""""#0.99723""""""""#0.04633"H""""""""""#1.37167""""""""#0.64849""""""""#1.45454"C""""""""""#1.25999"""""""""0.91112"""""""""0.06297"H""""""""""#1.85441"""""""""1.56926""""""""#0.57879"H""""""""""#1.62920"""""""""1.02750"""""""""1.08796"C"""""""""""0.27612"""""""""1.21855"""""""""0.02070"H"""""""""""0.47093"""""""""2.12231"""""""""0.61346"H"""""""""""0.54672"""""""""1.41476""""""""#1.00562"C"""""""""""0.90804"""""""""0.04918"""""""""0.59949"H"""""""""""1.06148""""""""#0.04468"""""""""1.67154"C"""""""""""1.80628""""""""#0.19300""""""""#0.42603"H"""""""""""2.07315"""""""""0.55695""""""""#1.15141"H"""""""""""2.68102""""""""#0.82333""""""""#0.20390"H"""""""""""0.74177""""""""#1.25698""""""""#0.59975"N""""""""""#0.25240""""""""#1.33332"""""""""0.20320"H""""""""""#0.52166""""""""#2.04696"""""""""0.88417"

142

OOH

C"""""""""""1.35165""""""""(0.74160"""""""""0.30238"H"""""""""""2.26199""""""""(1.25323""""""""(0.03494"H"""""""""""1.29846""""""""(0.85253"""""""""1.39616"C"""""""""""1.37835"""""""""0.75683""""""""(0.06131"H"""""""""""2.06800"""""""""1.33436"""""""""0.56225"H"""""""""""1.69267"""""""""0.87019""""""""(1.10382"C""""""""""(0.08196"""""""""1.22830"""""""""0.09854"H""""""""""(0.20027"""""""""2.22294""""""""(0.35277"H""""""""""(0.31816"""""""""1.32723"""""""""1.15849"C""""""""""(0.99236"""""""""0.28946""""""""(0.54038"H""""""""""(1.06039"""""""""0.20948""""""""(1.61733"C""""""""""(1.92290""""""""(0.21564"""""""""0.35211"H""""""""""(2.03291"""""""""0.26869"""""""""1.31449"H""""""""""(2.82371""""""""(0.69954""""""""(0.01782"H""""""""""(0.91798""""""""(1.14171"""""""""0.37661"O"""""""""""0.20445""""""""(1.27376""""""""(0.32367"

OH

O

C"""""""""""1.30195"""""""")1.04727"""""""")0.28737"C"""""""""")1.36528"""""""""0.04513"""""""")0.43507"C"""""""""")0.42755"""""""""1.16368"""""""")0.78346"C"""""""""""0.71002"""""""""1.42420"""""""""0.22499"C"""""""""""1.50781"""""""""0.15954"""""""""0.64141"H"""""""""")1.90396"""""""")0.38154"""""""")1.27416"H"""""""""")1.03267"""""""""2.07477"""""""")0.89173"H"""""""""""1.38182"""""""""2.15562"""""""")0.23348"H"""""""""""1.21275"""""""")0.14607"""""""""1.65031"H"""""""""""1.64694"""""""")0.81178"""""""")1.30612"H"""""""""""1.91739"""""""")1.88761"""""""""0.06117"H"""""""""")0.82517"""""""")1.19125"""""""""0.67627"C"""""""""")1.81803"""""""")0.26967"""""""""0.87060"H"""""""""")1.55348"""""""""0.39786"""""""""1.68529"H"""""""""")2.78021"""""""")0.76176"""""""""0.96491"H"""""""""""2.57532"""""""""0.39731"""""""""0.69365"H"""""""""""0.30617"""""""""1.91048"""""""""1.11720"H"""""""""")0.00538"""""""""0.96512"""""""")1.77288"O"""""""""")0.04913"""""""")1.44686"""""""")0.34463""

143

O

OH

C""""""""""#1.26740""""""""#1.44339""""""""#0.21262"C"""""""""""1.53151""""""""#0.14725"""""""""0.67385"C""""""""""#1.87264""""""""#0.21090"""""""""0.46535"C"""""""""""0.93464"""""""""1.17921"""""""""0.56364"C""""""""""#1.55147"""""""""1.12940""""""""#0.21745"C""""""""""#0.08160"""""""""1.39377""""""""#0.59064"H""""""""""#1.53611""""""""#1.44941""""""""#1.28082"H"""""""""""0.43777"""""""""1.47675"""""""""1.49648"H""""""""""#1.51750""""""""#0.20044"""""""""1.50249"H""""""""""#1.89933"""""""""1.93835"""""""""0.43671"H""""""""""#1.70374""""""""#2.35079"""""""""0.23273"H"""""""""""1.58334""""""""#0.69118"""""""""1.60504"H""""""""""#2.96225""""""""#0.32193"""""""""0.51924"H"""""""""""1.76043"""""""""1.88787"""""""""0.43638"H""""""""""#2.14484"""""""""1.21330""""""""#1.13579"H""""""""""#0.00583"""""""""2.43497""""""""#0.92006"H"""""""""""0.20449"""""""""0.78258""""""""#1.44762"C"""""""""""2.29243""""""""#0.43452""""""""#0.43928"H"""""""""""2.48971"""""""""0.36187""""""""#1.14803"H"""""""""""3.08265""""""""#1.17933""""""""#0.37281"H"""""""""""1.21311""""""""#1.11611""""""""#0.78979"O"""""""""""0.13567""""""""#1.44806""""""""#0.07391"C"""""""""""1.63393"""""""""0.72786"""""""""0.10707"C"""""""""",1.32523"""""""""0.28884"""""""""0.40951"H"""""""""",1.76950"""""""""0.94524"""""""""1.15740"H"""""""""""1.97292"""""""""0.41437"""""""""1.10605"H"""""""""""2.47619"""""""""1.28748"""""""",0.32778"C"""""""""""1.34968"""""""",0.51114"""""""",0.74172"H"""""""""""0.88322"""""""",0.18210"""""""",1.68382"H"""""""""""2.28124"""""""",1.01353"""""""",1.03051"C"""""""""""0.43473"""""""",1.51200"""""""",0.02616"H"""""""""",0.11459"""""""",2.11103"""""""",0.76407"H"""""""""""1.04501"""""""",2.22530"""""""""0.54390"C"""""""""",0.54786"""""""",0.87145"""""""""0.95820"H"""""""""",1.28988"""""""",1.62046"""""""""1.27262"H"""""""""",0.01537"""""""",0.55240"""""""""1.86323"C"""""""""",2.02768"""""""""0.19296"""""""",0.83402"H"""""""""",2.87181"""""""""0.84217"""""""",1.03234"H"""""""""",1.79165"""""""",0.60684"""""""",1.52793"C"""""""""""0.39112"""""""""1.58438"""""""""0.21163"H"""""""""",0.84088"""""""""0.98550"""""""",0.55614"H"""""""""""0.29700"""""""""2.17720"""""""""1.12662"H"""""""""""0.28594"""""""""2.26300"""""""",0.65425"

144

O

OH

OH

OH

OH

O OH

OH

OH

HO

C"""""""""""0.33200""""""""'1.51500""""""""'0.68547"O""""""""""'1.01732""""""""'1.56252""""""""'0.23287"C""""""""""'1.62373""""""""'0.06673"""""""""0.46993"C""""""""""'0.85259"""""""""1.05204""""""""'0.18398"C"""""""""""0.67753"""""""""0.90044""""""""'0.12484"C"""""""""""1.15386""""""""'0.52021"""""""""0.12039"O""""""""""'1.36224""""""""'0.49535"""""""""1.66397"O""""""""""'1.32453"""""""""1.23559""""""""'1.49931"O"""""""""""1.17615"""""""""1.76797"""""""""0.86011"O"""""""""""2.51372""""""""'0.54794""""""""'0.26922"H""""""""""'2.65707""""""""'0.12990"""""""""0.07719"H""""""""""'1.09324"""""""""1.96687"""""""""0.37759"H"""""""""""1.03800"""""""""1.18477""""""""'1.13115"H"""""""""""1.03850""""""""'0.72779"""""""""1.19536"H"""""""""""0.35923""""""""'1.24135""""""""'1.75128"H"""""""""""0.75557""""""""'2.52538""""""""'0.60379"H""""""""""'1.07724""""""""'1.50803"""""""""0.96553"H""""""""""'1.44101"""""""""0.36821""""""""'1.90474"H"""""""""""2.13211"""""""""1.63862"""""""""0.88049"H"""""""""""2.93640""""""""'1.31129"""""""""0.13723"

H2N

NH

C""""""""""#1.72257"""""""""0.45059""""""""#0.32408"C""""""""""#0.48883"""""""""1.38954""""""""#0.29049"C"""""""""""0.56151"""""""""0.98410"""""""""0.76290"C"""""""""""1.19252""""""""#0.33199"""""""""0.50256"C""""""""""#1.43901""""""""#0.97736"""""""""0.17897"H"""""""""""1.34724"""""""""1.73727"""""""""0.82046"H""""""""""#0.01830"""""""""1.39668""""""""#1.27402"H""""""""""#0.81943"""""""""2.41257""""""""#0.09020"H""""""""""#1.58739""""""""#1.03679"""""""""1.26330"H""""""""""#2.10460"""""""""0.40518""""""""#1.34786"H"""""""""""1.54870""""""""#0.87958"""""""""1.37872"H""""""""""#2.13198""""""""#1.68961""""""""#0.27805"H""""""""""#2.53053"""""""""0.86211"""""""""0.28846"H"""""""""""0.05774"""""""""1.01217"""""""""1.74348"N""""""""""#0.04814""""""""#1.36784""""""""#0.12044"H"""""""""""0.15388""""""""#2.33661"""""""""0.12637"C"""""""""""2.01181""""""""#0.10302""""""""#0.65520"H"""""""""""0.65864""""""""#0.96416""""""""#1.07812"H"""""""""""2.18233"""""""""0.92034""""""""#0.96276"H"""""""""""2.88808""""""""#0.73588""""""""#0.79469"

145

C"""""""""""1.05992"""""""""1.44322""""""""+0.38178"C""""""""""+0.37521"""""""""1.47625"""""""""0.20284"C""""""""""+1.66218"""""""""0.05037"""""""""0.53835"C"""""""""""1.95600"""""""""0.38516"""""""""0.27923"C""""""""""+0.74865""""""""+1.05480"""""""""0.71371"C"""""""""""1.69258""""""""+1.06644""""""""+0.16950"C"""""""""""0.22031""""""""+1.41542""""""""+0.43889"H"""""""""""1.01857"""""""""1.27967""""""""+1.46615"H""""""""""+0.29087"""""""""1.59661"""""""""1.28662"H""""""""""+0.17394""""""""+0.95456"""""""""1.64244"H"""""""""""1.83658"""""""""0.46478"""""""""1.36643"H"""""""""""2.10492""""""""+1.74851"""""""""0.58322"H"""""""""""1.51973"""""""""2.42960""""""""+0.24897"H""""""""""+0.91304"""""""""2.37871""""""""+0.13053"H""""""""""+2.04121"""""""""0.55966"""""""""1.42941"H"""""""""""3.00628"""""""""0.62185"""""""""0.07974"H""""""""""+1.40918""""""""+1.91742"""""""""0.89368"H"""""""""""2.24925""""""""+1.26566""""""""+1.09244"H"""""""""""0.15346""""""""+2.48777""""""""+0.64110"H""""""""""+0.11829""""""""+0.92604""""""""+1.35334"C""""""""""+2.22925"""""""""0.06459""""""""+0.70345"H""""""""""+2.36754""""""""+0.88420""""""""+1.21336"H""""""""""+3.03125"""""""""0.77427""""""""+0.89589"H""""""""""+1.02455"""""""""0.78145""""""""+0.48279"

O OH

OH

OHHO

HOO

OH

OH

OH

OH

OH

C""""""""""#1.24672"""""""""0.61106""""""""#0.19636"C""""""""""#1.63852""""""""#0.81104"""""""""0.18532"C""""""""""#0.64861""""""""#1.86555""""""""#0.30344"C"""""""""""0.09625"""""""""1.11048"""""""""0.33892"C"""""""""""1.33478"""""""""0.42441""""""""#0.30031"C"""""""""""1.92779""""""""#0.64964"""""""""0.48727"H""""""""""#1.22480"""""""""0.67447""""""""#1.29462"H""""""""""#1.71301""""""""#0.87906"""""""""1.27786"H""""""""""#0.41054""""""""#1.70134""""""""#1.36348"H"""""""""""0.12052"""""""""0.98332"""""""""1.43013"H""""""""""#1.12226""""""""#2.85252""""""""#0.22876"H"""""""""""1.09285"""""""""0.03908""""""""#1.29732"H"""""""""""2.02796""""""""#0.52563"""""""""1.57028"O"""""""""""0.50002""""""""#1.88395"""""""""0.52505"O"""""""""""2.74739""""""""#1.39475""""""""#0.17871"H"""""""""""1.71894""""""""#2.12445""""""""#0.05265"O"""""""""""2.41113"""""""""1.35816""""""""#0.40312"H"""""""""""1.99957"""""""""2.23478""""""""#0.41278"O"""""""""""0.19746"""""""""2.49865"""""""""0.02581"H""""""""""#0.67686"""""""""2.88138"""""""""0.17589"O""""""""""#2.21880"""""""""1.52599"""""""""0.31352"H""""""""""#3.07895"""""""""1.18836"""""""""0.03542"O""""""""""#2.92748""""""""#0.99077""""""""#0.42028"H""""""""""#3.36098""""""""#1.74325""""""""#0.00661"

146

NH

NH2

C"""""""""""1.16089"""""""""1.48421""""""""+0.19127"C""""""""""+1.43394"""""""""0.24286"""""""""0.59365"C"""""""""""1.88304"""""""""0.29011"""""""""0.42786"C""""""""""+0.73905""""""""+1.05505"""""""""0.68153"C"""""""""""1.65921""""""""+1.05363""""""""+0.28113"C"""""""""""0.18100""""""""+1.43242""""""""+0.50369"H"""""""""""1.48551"""""""""1.62478""""""""+1.22823"H""""""""""+0.13751""""""""+1.13494"""""""""1.59892"H"""""""""""1.58497"""""""""0.20962"""""""""1.47793"H"""""""""""2.14436""""""""+1.82953"""""""""0.32201"H"""""""""""1.44064"""""""""2.38960"""""""""0.35715"H""""""""""+1.63571"""""""""0.75325"""""""""1.53542"H"""""""""""2.95478"""""""""0.51611"""""""""0.43645"H""""""""""+1.51019""""""""+1.81944"""""""""0.79374"H"""""""""""2.17881""""""""+1.05108""""""""+1.24615"H"""""""""""0.12508""""""""+2.51204""""""""+0.66900"H""""""""""+0.19875""""""""+0.97499""""""""+1.41921"N""""""""""+0.32715"""""""""1.34785""""""""+0.21092"H""""""""""+0.74422"""""""""2.25726""""""""+0.01671"C""""""""""+2.42769"""""""""0.09299""""""""+0.43030"H""""""""""+2.62481""""""""+0.90516""""""""+0.79899"H""""""""""+3.30808"""""""""0.73245""""""""+0.40183"H""""""""""+1.16566"""""""""0.89482""""""""+1.04496"C""""""""""#0.71911"""""""""1.41541""""""""#0.37090"C"""""""""""0.46076"""""""""0.97933"""""""""0.54123"C"""""""""""1.71793"""""""""0.52503""""""""#0.22268"C""""""""""#0.41120""""""""#1.32397"""""""""0.71134"C""""""""""#1.09882""""""""#1.06200""""""""#0.54085"C""""""""""#1.78099"""""""""0.31399""""""""#0.56733"H""""""""""#0.31656"""""""""1.70749""""""""#1.34589"H"""""""""""0.76056"""""""""1.85023"""""""""1.13255"H"""""""""""2.54725"""""""""0.49757"""""""""0.51121"H"""""""""""2.00953"""""""""1.33008""""""""#0.91414"H""""""""""#0.30869""""""""#2.33024"""""""""1.09937"H""""""""""#2.30759"""""""""0.45879""""""""#1.51472"H""""""""""#0.27403""""""""#0.96489""""""""#1.35748"C"""""""""""1.72246""""""""#0.77973""""""""#0.95646"H"""""""""""1.09635""""""""#1.61222""""""""#0.68966"H"""""""""""2.71609""""""""#1.05991""""""""#1.31193"C"""""""""""0.02553""""""""#0.14875"""""""""1.51267"H""""""""""#0.79705"""""""""0.22748"""""""""2.14647"H"""""""""""0.83988""""""""#0.40645"""""""""2.19872"H""""""""""#1.73580""""""""#1.88679""""""""#0.86977"H""""""""""#2.53511"""""""""0.36528"""""""""0.22528"H""""""""""#1.19421"""""""""2.30777"""""""""0.04783"

147

CH••H2C

C""""""""""""""""""0.35682400""""1.20125100""""0.39357500""C""""""""""""""""""1.49926800""""0.78654600""".0.60473300""C""""""""""""""""""0.82468716""".1.09640544""""1.10095972""H""""""""""""""""""0.39285555""""2.28432540""""0.60609195""H""""""""""""""""""2.47636090""""0.83059032""".0.09571882""H""""""""""""""""""1.54399242""""1.46241427""".1.47393393""H""""""""""""""""""1.31046824""".1.81783247""""1.78145146""C""""""""""""""""""1.16815553""".0.56720172""".1.06085704""H""""""""""""""""""1.98439396""".1.24267221""".0.75552463""H""""""""""""""""""1.03755854""".0.67109657""".2.15010154""C""""""""""""""""""0.82239141""""0.36980925""""1.55533009""H""""""""""""""""""1.75317121""""0.72463765""""2.02897964""H""""""""""""""""""0.02288918""""0.36685598""""2.31245085""C""""""""""""""""".0.45499360""".1.64697070""""0.47878910""H""""""""""""""""".0.31076415""".2.11958464""".0.50742064""H""""""""""""""""".0.79369316""".2.43841717""""1.16904762""C""""""""""""""""".1.57660787""".0.55899932""""0.38662402""H""""""""""""""""".1.99736044""".0.40263414""""1.39353730""H""""""""""""""""".2.39928119""".0.92890567""".0.24896392""C""""""""""""""""".1.06889303""""0.81693887""".0.16046181""H""""""""""""""""".1.79867841""""1.59468766""""0.12249877""H""""""""""""""""".1.03596020""""0.79176669""".1.26275760"

CH••H2C

C"""""""""""""""""#0.18122013""""2.01575063"""#1.54834727""C""""""""""""""""""0.19061193""""1.34208849"""#0.19370194""C""""""""""""""""""1.42775215""""0.43169512"""#0.28231099""C"""""""""""""""""#1.39011552"""#0.52242277"""#0.68798542""C"""""""""""""""""#1.27666794"""#0.21669688"""#2.03919278""C"""""""""""""""""#1.32205924""""1.30875991"""#2.31952410""H""""""""""""""""""0.71247496""""2.04205003"""#2.17944372""H""""""""""""""""""0.42347145""""2.13036878""""0.52773176""H""""""""""""""""""1.73662377""""0.19550008""""0.75529208""H""""""""""""""""""2.26589846""""1.02672914"""#0.67495746""H"""""""""""""""""#1.82486053"""#1.45861645"""#0.35805076""H"""""""""""""""""#1.23509866""""1.52074090"""#3.38888233""H"""""""""""""""""#0.02026315"""#0.96003212"""#1.29550401""C""""""""""""""""""1.34184115"""#0.85947188"""#1.03731899""H""""""""""""""""""1.17823755"""#1.80300136"""#0.54323179""H""""""""""""""""""2.04105578"""#0.90544908"""#1.87469737""C"""""""""""""""""#1.01399863""""0.51532596""""0.33931753""H"""""""""""""""""#1.85707102""""1.20569623""""0.51933193""H"""""""""""""""""#0.77882930""""0.07122744""""1.31293177""H"""""""""""""""""#0.46514661""""3.05783211"""#1.37240758""H"""""""""""""""""#2.29404960""""1.69897500"""#1.99878249""H"""""""""""""""""#1.92521874"""#0.81030051"""#2.68667657"

148

Appendix C

RMG-Py generated mechanism for1230xa

ELEMENTS H C O N Ne Ar He Si S Cl END

SPECIES Ar He Ne N2 xa(1) HCl(2) Cl2(3) Cl(4) xf(5) ab(6) db(7) fb(8) za(9) zf(10) rad1(11)rad2(12) rad3(13) rad4(14) rad5(15) C3Cl4H(18) S(20) S(25) C3Cl4H(26) S(30) S(31) S(32)S(35) S(36) S(38) S(40) S(44) S(45) S(47) S(48) S(52) C3Cl3H(56) S(58) S(79) S(85) S(86)S(87) C3Cl5H(93) C3Cl4H(95) C3Cl4H(96) S(98) S(100) S(101) S(102) S(103) C3Cl5(106)S(107) S(110) S(111) C3Cl5(114) S(120) S(127) C3Cl5(128) END

THERM ALL300.000 1000.000 5000.000

Ar Ar1 G200.000 6000.000 1000.00 12.50000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 2

-7.45375000E+02 4.37967000E+00 2.50000000E+00 0.00000000E+00 0.00000000E+00 30.00000000E+00 0.00000000E+00-7.45375000E+02 4.37967000E+00 4

He He1 G200.000 6000.000 1000.00 12.50000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 2

-7.45375000E+02 9.28724000E-01 2.50000000E+00 0.00000000E+00 0.00000000E+00 30.00000000E+00 0.00000000E+00-7.45375000E+02 9.28724000E-01 4

Ne Ne1 G200.000 6000.000 1000.00 12.50000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 2

-7.45375000E+02 3.35532000E+00 2.50000000E+00 0.00000000E+00 0.00000000E+00 30.00000000E+00 0.00000000E+00-7.45375000E+02 3.35532000E+00 4

N2 N 2 G200.000 6000.000 1000.00 1

149

2.95258000E+00 1.39690000E-03-4.92632000E-07 7.86010000E-11-4.60755000E-15 2-9.23949000E+02 5.87189000E+00 3.53101000E+00-1.23661000E-04-5.02999000E-07 32.43531000E-09-1.40881000E-12-1.04698000E+03 2.96747000E+00 4

xa(1) C 3 H 2 Cl4 G100.000 5000.000 651.72 11.08993247E+01 1.64998088E-02-8.28408659E-06 1.60440844E-09-1.11439259E-13 2

-1.64301295E+04-1.96918747E+01 1.26651083E+00 6.58475863E-02-9.93654249E-05 37.17607574E-08-1.81951957E-11-1.49669695E+04 2.42492586E+01 4

HCl(2) H 1 Cl1 G200.000 6000.000 1000.00 12.75758000E+00 1.45387000E-03-4.79647000E-07 7.77909000E-11-4.79574000E-15 2

-1.19138000E+04 6.52197000E+00 3.46376000E+00 4.76484000E-04-2.00301000E-06 33.31714000E-09-1.44958000E-12-1.21444000E+04 2.66428000E+00 4

Cl2(3) Cl2 G200.000 6000.000 1000.00 14.74728000E+00-4.88582000E-04 2.68445000E-07-2.43476000E-11-1.03683000E-15 2

-1.51102000E+03-3.44539000E-01 2.73638000E+00 7.83526000E-03-1.45105000E-05 31.25731000E-08-4.13247000E-12-1.05880000E+03 9.44557000E+00 4

Cl(4) Cl1 G200.000 6000.000 1000.00 12.94658000E+00-3.85985000E-04 1.36139000E-07-2.17033000E-11 1.28751000E-15 21.36970000E+04 3.11330000E+00 2.26062000E+00 1.54154000E-03-6.80284000E-07 3

-1.59973000E-09 1.15417000E-12 1.38553000E+04 6.57021000E+00 4

xf(5) C 3 H 2 Cl4 G100.000 5000.000 702.07 11.19197373E+01 1.59458886E-02-8.21279585E-06 1.60626658E-09-1.12188634E-13 2

-1.42407068E+04-2.68593957E+01 9.93706938E-01 7.13844639E-02-1.12105755E-04 38.64403414E-08-2.53996119E-11-1.25386621E+04 2.31831943E+01 4

ab(6) C 3 H 3 Cl5 G100.000 5000.000 936.20 11.72397189E+01 1.54384704E-02-7.38629535E-06 1.43122285E-09-1.00892825E-13 2

-3.44343251E+04-5.35045761E+01 6.66935873E-02 8.88105566E-02-1.24942672E-04 38.51415427E-08-2.24542664E-11-3.12187938E+04 2.82134810E+01 4

db(7) C 3 H 3 Cl5 G100.000 5000.000 1028.43 11.51058860E+01 1.96378541E-02-9.93544791E-06 1.99844790E-09-1.44594702E-13 2

-3.35598145E+04-4.04977805E+01 6.40881691E-01 7.58993993E-02-9.19962979E-05 35.51943096E-08-1.30761557E-11-3.05846192E+04 2.96927456E+01 4

fb(8) C 3 H 4 Cl4 G100.000 5000.000 1104.28 11.41564590E+01 1.75117196E-02-7.90979375E-06 1.52394197E-09-1.08028188E-13 2

-2.84641520E+04-3.86521194E+01 9.96593390E-01 6.51803823E-02-7.26606848E-05 34.06148727E-08-8.95791144E-12-2.55577216E+04 2.61419768E+01 4

150

za(9) C 3 H 3 Cl3 G100.000 5000.000 1143.99 11.07509764E+01 1.46445126E-02-6.46593732E-06 1.23183364E-09-8.66885039E-14 2

-1.12778503E+04-2.26894311E+01 1.88794519E+00 4.56342156E-02-4.70993985E-05 32.49110705E-08-5.26136083E-12-9.24999416E+03 2.12618988E+01 4

zf(10) C 3 H 3 Cl3 G100.000 5000.000 1120.36 11.17410069E+01 1.41451731E-02-6.42750374E-06 1.24171333E-09-8.81204273E-14 2

-9.07617631E+03-2.96867187E+01 1.69473960E+00 5.00132584E-02-5.44498005E-05 32.98172992E-08-6.46456554E-12-6.82509465E+03 1.99224478E+01 4

rad1(11) C 3 H 2 Cl3 G100.000 5000.000 918.97 11.11881100E+01 1.18049534E-02-5.51941450E-06 1.05979520E-09-7.42919842E-14 25.01823186E+03-2.62757512E+01 1.65922763E+00 5.32806730E-02-7.32176210E-05 35.01706936E-08-1.34343967E-11 6.76961024E+03 1.88905369E+01 4

rad2(12) C 3 H 1 Cl6 G100.000 5000.000 868.95 11.90717209E+01 1.17128480E-02-6.31840569E-06 1.24773205E-09-8.75053685E-14 2

-1.34302277E+04-5.64324828E+01-4.15457388E-01 1.01421642E-01-1.61183074E-04 31.20067077E-07-3.42738944E-11-1.00437136E+04 3.48435938E+01 4

rad3(13) C 3 H 2 Cl5 G100.000 5000.000 939.20 11.65076454E+01 1.37741627E-02-7.30239405E-06 1.48082953E-09-1.07103894E-13 2

-1.13749145E+04-4.42715342E+01 3.85100528E-01 8.24381837E-02-1.16964388E-04 37.93204167E-08-2.08264564E-11-8.34641194E+03 3.24993419E+01 4

rad4(14) C 3 H 2 Cl5 G100.000 5000.000 939.25 11.65076833E+01 1.37740895E-02-7.30234790E-06 1.48081791E-09-1.07102885E-13 2

-1.13749275E+04-4.49648880E+01 3.85114975E-01 8.24380305E-02-1.16963927E-04 37.93199067E-08-2.08262684E-11-8.34641259E+03 3.18061417E+01 4

rad5(15) C 3 H 4 Cl1 G100.000 5000.000 1141.50 17.36539273E+00 1.37132518E-02-5.54601922E-06 1.01798455E-09-7.02683914E-14 22.44167061E+04-1.00983885E+01 2.75462078E+00 2.36389400E-02-1.04007897E-05 3

-9.28824331E-10 1.40343730E-12 2.58753144E+04 1.45343527E+01 4

C3Cl4H(18) C 3 H 1 Cl4 G100.000 5000.000 851.31 11.09214351E+01 1.37848608E-02-7.25900539E-06 1.39864136E-09-9.54299429E-14 28.39293821E+03-1.75909608E+01 1.11609586E+00 6.92038573E-02-1.21376522E-04 31.03662486E-07-3.39143462E-11 9.72370573E+03 2.61463357E+01 4

S(20) C 3 H 2 Cl3 G100.000 5000.000 822.86 19.09394721E+00 1.49625301E-02-7.22562522E-06 1.39659353E-09-9.77397414E-14 21.81626249E+04-1.16503090E+01 1.85887718E+00 5.01321909E-02-7.13354941E-05 35.33362507E-08-1.58776503E-11 1.93533384E+04 2.18442490E+01 4

151

S(25) C 3 H 2 Cl3 G100.000 5000.000 842.87 11.00968542E+01 1.44449905E-02-7.17823048E-06 1.40462278E-09-9.90348561E-14 22.03577048E+04-1.87224104E+01 1.67210243E+00 5.44244464E-02-7.83238084E-05 35.76745593E-08-1.67882613E-11 2.17779631E+04 2.04823791E+01 4

C3Cl4H(26) C 3 H 1 Cl4 G100.000 5000.000 852.61 11.24762454E+01 1.25465749E-02-6.83970822E-06 1.32519614E-09-9.03537927E-14 21.55307132E+04-2.82353765E+01 7.89171764E-01 7.66472648E-02-1.35922926E-04 31.15010529E-07-3.71644172E-11 1.71866401E+04 2.43083116E+01 4

S(30) C 3 H 3 Cl4 G100.000 5000.000 891.28 11.20338739E+01 2.10774487E-02-1.09995158E-05 2.21583277E-09-1.59560938E-13 2

-6.67446557E+03-2.58114764E+01 1.00081724E+00 7.05937232E-02-9.43352646E-05 36.45508673E-08-1.76445085E-11-4.70778547E+03 2.61466169E+01 4

S(31) C 3 H 2 Cl5 G100.000 5000.000 884.41 11.70761325E+01 1.30732949E-02-6.57787446E-06 1.27932870E-09-8.95250282E-14 2

-9.54345316E+03-4.99739875E+01 6.54945248E-02 9.00058128E-02-1.37053852E-04 39.96280353E-08-2.78890909E-11-6.53445971E+03 3.00036798E+01 4

S(32) C 3 H 3 Cl4 G100.000 5000.000 977.65 11.46144556E+01 1.49520363E-02-7.45293132E-06 1.48604687E-09-1.06894361E-13 2

-7.52841933E+03-3.94823656E+01 8.46412960E-01 7.12830899E-02-9.38810015E-05 36.04218544E-08-1.51776466E-11-4.83634830E+03 2.66293037E+01 4

S(35) C 3 H 3 Cl4 G100.000 5000.000 943.56 11.13721851E+01 1.96455653E-02-9.84047977E-06 1.96199698E-09-1.40890906E-13 2

-4.07148822E+03-2.03625110E+01 1.32263745E+00 6.22493534E-02-7.75704973E-05 34.98174731E-08-1.28207189E-11-2.17506705E+03 2.75366553E+01 4

S(36) C 3 H 2 Cl5 G100.000 5000.000 866.40 11.40142169E+01 1.97468806E-02-1.07590456E-05 2.18904579E-09-1.57961045E-13 2

-1.05561260E+04-3.17815653E+01 5.13586233E-01 8.20773426E-02-1.18673074E-04 38.52262928E-08-2.41186471E-11-8.21676229E+03 3.14149198E+01 4

S(38) C 3 H 2 Cl5 G100.000 5000.000 951.99 11.46977729E+01 1.77051611E-02-9.38363846E-06 1.90845156E-09-1.38442461E-13 2

-8.57170697E+03-3.60076814E+01 6.74681782E-01 7.66255079E-02-1.02219997E-04 36.69196819E-08-1.72106601E-11-5.90170115E+03 3.09558767E+01 4

S(40) C 3 H 2 Cl4 G100.000 5000.000 990.57 11.31002656E+01 1.40385234E-02-6.87772550E-06 1.36209108E-09-9.76681106E-14 2

-1.31392330E+04-3.32836510E+01 1.25442626E+00 6.18723919E-02-7.93107197E-05 3

152

5.01098723E-08-1.24004843E-11-1.07923785E+04 2.37535807E+01 4

S(44) C 3 H 3 Cl4 G100.000 5000.000 941.60 11.41974249E+01 1.54036172E-02-7.38403769E-06 1.43809986E-09-1.01820102E-13 2

-4.95770933E+03-3.62780199E+01 8.15376092E-01 7.22506580E-02-9.79415287E-05 36.55529133E-08-1.71243322E-11-2.43755379E+03 2.74776246E+01 4

S(45) C 3 H 4 Cl3 G100.000 5000.000 1233.53 11.23329373E+01 1.59395197E-02-7.40095126E-06 1.44419791E-09-1.02862147E-13 2

-4.55718039E+03-2.97840090E+01 1.62339582E+00 5.06683107E-02-4.96327637E-05 32.42690125E-08-4.72886679E-12-1.91512405E+03 2.41308461E+01 4

S(47) C 3 H 3 Cl2 G100.000 5000.000 993.06 11.11994722E+01 9.69387558E-03-3.56143935E-06 6.55658844E-10-4.70214983E-14 21.00984679E+04-3.01844003E+01 2.20943835E+00 3.36205336E-02-2.11462594E-05 33.67217469E-12 3.25316522E-12 1.24897387E+04 1.61745876E+01 4

S(48) C 3 H 2 Cl3 G100.000 5000.000 997.59 11.01294504E+01 1.30651108E-02-6.11375169E-06 1.18826179E-09-8.43403556E-14 21.38031039E+04-1.69912317E+01 1.97131681E+00 4.57763306E-02-5.52988943E-05 33.40574222E-08-8.32144445E-12 1.54308058E+04 2.23473994E+01 4

S(52) C 3 H 2 Cl3 G100.000 5000.000 968.38 11.16398030E+01 1.19064526E-02-5.74213576E-06 1.12639548E-09-8.02448085E-14 22.09582214E+04-2.73882505E+01 1.64636937E+00 5.31862020E-02-6.96847869E-05 34.51475784E-08-1.14451036E-11 2.28936734E+04 2.05030065E+01 4

C3Cl3H(56) C 3 H 1 Cl3 G100.000 5000.000 822.82 18.92252829E+00 1.77966745E-02-8.44656302E-06 1.58378551E-09-1.07897883E-13 23.20324726E+04-1.26404183E+01 1.58600525E+00 5.66373695E-02-8.50419588E-05 36.83333267E-08-2.18136961E-11 3.31323074E+04 2.06701120E+01 4

S(58) C 3 H 3 Cl3 G100.000 5000.000 866.60 19.20726217E+00 1.82705537E-02-9.35335079E-06 1.87717667E-09-1.34975910E-13 2

-1.21268279E+04-1.38711026E+01 1.78896071E+00 5.25114949E-02-6.86210647E-05 34.74712234E-08-1.32881138E-11-1.08410876E+04 2.08557795E+01 4

S(79) C 3 H 3 Cl5 G100.000 5000.000 1019.40 11.58063256E+01 1.80093795E-02-9.19926463E-06 1.85960428E-09-1.34952981E-13 2

-3.10499900E+04-4.46635488E+01 5.45556289E-01 7.78891291E-02-9.73071527E-05 35.94787864E-08-1.42652293E-11-2.79385398E+04 2.92544803E+01 4

S(85) C 3 H 2 Cl2 G100.000 5000.000 1369.98 19.50552401E+00 1.47856398E-02-5.99813409E-06 1.06858280E-09-7.17074013E-14 2

153

3.68479495E+04-1.98132416E+01 2.19964937E+00 3.61170140E-02-2.93540402E-05 31.24341755E-08-2.14575503E-12 3.88497260E+04 1.77332271E+01 4

S(86) C 3 H 2 Cl4 G100.000 5000.000 1012.95 11.23454751E+01 1.52356577E-02-7.80909427E-06 1.58014402E-09-1.14660506E-13 2

-1.38402119E+04-2.83888524E+01 1.44027221E+00 5.82990874E-02-7.15788497E-05 34.35500860E-08-1.04730742E-11-1.16309415E+04 2.43626909E+01 4

S(87) C 3 H 3 Cl3 G100.000 5000.000 1270.27 11.17490332E+01 1.40456765E-02-6.67975276E-06 1.31636407E-09-9.41601392E-14 2

-1.15965658E+04-2.79551987E+01 1.87291600E+00 4.51447921E-02-4.34030030E-05 32.05894682E-08-3.88725313E-12-9.08748630E+03 2.20540650E+01 4

C3Cl5H(93) C 3 H 1 Cl5 G100.000 5000.000 822.31 11.38897975E+01 1.47634459E-02-8.02647051E-06 1.57339485E-09-1.08841103E-13 2

-1.85487953E+04-3.38707757E+01 3.76025220E-01 8.55920038E-02-1.46517105E-04 31.21382921E-07-3.88233717E-11-1.64984815E+04 2.76345765E+01 4

C3Cl4H(95) C 3 H 1 Cl4 G100.000 5000.000 800.11 11.19997385E+01 1.33919201E-02-7.07318410E-06 1.39215446E-09-9.74571025E-14 21.60732977E+04-2.53651072E+01 1.10942491E+00 6.78417351E-02-1.09163299E-04 38.64645098E-08-2.66817114E-11 1.78158039E+04 2.47446078E+01 4

C3Cl4H(96) C 3 H 1 Cl4 G100.000 5000.000 882.48 11.27424644E+01 1.21862129E-02-6.39029690E-06 1.27626379E-09-9.10340778E-14 21.62452967E+04-2.96242208E+01 1.21623525E+00 6.44326894E-02-9.51995116E-05 36.83691592E-08-1.90985913E-11 1.82795615E+04 2.45417844E+01 4

S(98) C 3 H 2 Cl5 G100.000 5000.000 888.74 11.32990278E+01 1.96815397E-02-1.08678881E-05 2.23652255E-09-1.62794792E-13 2

-6.77677916E+03-2.79401963E+01 7.83273689E-01 7.60114353E-02-1.05939780E-04 37.35518388E-08-2.02234334E-11-4.55211179E+03 3.09649386E+01 4

S(100) C 3 H 2 Cl5 G100.000 5000.000 934.42 11.56841340E+01 1.58509664E-02-8.56119146E-06 1.74946402E-09-1.27054205E-13 2

-8.83830800E+03-4.31059312E+01 4.86361109E-01 8.09056835E-02-1.12987254E-04 37.62495020E-08-2.00583417E-11-5.99796301E+03 2.91843498E+01 4

S(101) C 3 H 1 Cl4 G100.000 5000.000 916.11 11.20039765E+01 1.31890431E-02-7.19135355E-06 1.47453765E-09-1.07211517E-13 21.11201309E+04-2.49665610E+01 1.45650301E+00 5.92410210E-02-8.25927521E-05 35.63436577E-08-1.50801782E-11 1.30527158E+04 2.49950483E+01 4

S(102) C 3 H 1 Cl4 G100.000 5000.000 795.66 1

154

1.11492482E+01 1.47654396E-02-8.11231134E-06 1.63675383E-09-1.16721669E-13 21.54080374E+04-1.99414200E+01 1.28643559E+00 6.43441634E-02-1.01571320E-04 37.99372428E-08-2.47169447E-11 1.69776635E+04 2.53873359E+01 4

S(103) C 3 H 2 Cl3 G100.000 5000.000 1056.13 11.04668539E+01 1.37328484E-02-7.06696153E-06 1.43488578E-09-1.04335273E-13 21.81873885E+04-1.90701710E+01 1.99016034E+00 4.58375329E-02-5.26645207E-05 33.02176345E-08-6.91758339E-12 1.99778894E+04 2.22879122E+01 4

C3Cl5(106) C 3 Cl5 G100.000 5000.000 859.38 11.33205514E+01 1.32864479E-02-7.75068928E-06 1.52111634E-09-1.03788230E-13 21.19029981E+04-2.88847241E+01 3.68383124E-01 8.79486750E-02-1.63162386E-04 31.41548297E-07-4.65016058E-11 1.35983067E+04 2.85505516E+01 4

S(107) C 3 H 4 Cl2 G100.000 5000.000 1219.09 11.07812904E+01 1.35736360E-02-5.93192368E-06 1.13194208E-09-7.96912309E-14 2

-7.72829888E+03-2.66234067E+01 2.15603945E+00 3.49804684E-02-2.37892041E-05 36.25876735E-09-1.79831361E-13-5.11303352E+03 1.87981896E+01 4

S(110) C 3 H 1 Cl5 G100.000 5000.000 660.29 11.29825140E+01 1.62502861E-02-9.13834852E-06 1.83651726E-09-1.29728239E-13 2

-1.91949432E+04-2.81369464E+01 6.68082349E-01 8.04286897E-02-1.31258997E-04 31.01232656E-07-2.87127484E-11-1.73415384E+04 2.78819853E+01 4

S(111) C 3 H 2 Cl4 G100.000 5000.000 809.80 11.10735768E+01 1.72875299E-02-9.29219646E-06 1.87571132E-09-1.34351799E-13 2

-1.63983895E+04-2.03134796E+01 1.22350692E+00 6.59432354E-02-9.94201493E-05 37.60755088E-08-2.30418257E-11-1.48031172E+04 2.51290864E+01 4

C3Cl5(114) C 3 Cl5 G100.000 5000.000 833.30 11.30375485E+01 1.34766063E-02-8.07821376E-06 1.62225939E-09-1.13001269E-13 25.61522772E+03-2.69124761E+01 5.23944845E-01 8.36793485E-02-1.52692086E-04 31.31913736E-07-4.35809266E-11 7.34886336E+03 2.90650495E+01 4

S(120) C 3 H 2 Cl3 G100.000 5000.000 903.16 19.27911322E+00 1.57338478E-02-8.22514984E-06 1.66601765E-09-1.20505676E-13 21.81898518E+04-1.23320531E+01 1.96661178E+00 4.81201879E-02-6.20136019E-05 34.13699665E-08-1.11108077E-11 1.95107217E+04 2.22017101E+01 4

S(127) C 3 H 1 Cl5 G100.000 5000.000 885.89 11.47120369E+01 1.35284396E-02-7.03723615E-06 1.39857219E-09-9.94261532E-14 2

-1.58185227E+04-3.94506232E+01 6.61477906E-01 7.69706944E-02-1.14459644E-04 38.22390067E-08-2.29130178E-11-1.33291004E+04 2.66326456E+01 4

155

C3Cl5(128) C 3 Cl5 G100.000 5000.000 842.78 11.39029274E+01 1.23543339E-02-6.91456063E-06 1.35099186E-09-9.26155320E-14 21.32818845E+04-3.31506560E+01 4.72754060E-01 8.35515621E-02-1.46901678E-04 31.22581320E-07-3.91675455E-11 1.52808662E+04 2.77742208E+01 4

ENDREACTIONS KCAL/MOLE MOLESab(6)+C3Cl3H(56)=rad1(11)+S(31) 2.124e-02 4.340 3.400ab(6)+C3Cl4H(18)=S(110)+S(30) 8.420e-13 2.100 1.140ab(6)+C3Cl4H(18)=S(110)+S(32) 1.263e-12 2.100 1.140ab(6)+C3Cl4H(18)=S(111)+S(31) 7.242e-04 4.340 14.303ab(6)+C3Cl4H(18)=xa(1)+S(31) 1.752e-03 4.416 12.058ab(6)+C3Cl4H(26)=C3Cl5H(93)+S(30) 8.420e-13 2.100 1.140ab(6)+C3Cl4H(26)=C3Cl5H(93)+S(32) 1.263e-12 2.100 1.140ab(6)+C3Cl4H(26)=xf(5)+S(31) 2.124e-02 4.340 3.400ab(6)+C3Cl4H(95)=C3Cl5H(93)+S(30) 8.420e-13 2.100 1.140ab(6)+C3Cl4H(95)=C3Cl5H(93)+S(32) 1.263e-12 2.100 1.140ab(6)+C3Cl4H(96)=S(127)+S(30) 8.420e-13 2.100 1.140ab(6)+C3Cl4H(96)=S(127)+S(32) 1.263e-12 2.100 1.140ab(6)+C3Cl4H(96)=S(40)+S(31) 5.592e-03 4.340 3.788ab(6)+C3Cl5(106)=C3Cl5H(93)+S(31) 5.592e-03 4.340 3.788ab(6)+C3Cl5(114)=S(110)+S(31) 7.242e-04 4.340 14.303ab(6)+S(101)=S(86)+S(31) 7.242e-04 4.340 14.303ab(6)+S(102)=S(110)+S(30) 8.420e-13 2.100 1.140ab(6)+S(102)=S(110)+S(32) 1.263e-12 2.100 1.140ab(6)+S(103)=S(86)+S(30) 8.420e-13 2.100 1.140ab(6)+S(103)=S(86)+S(32) 1.263e-12 2.100 1.140ab(6)+S(103)=S(87)+S(31) 5.592e-03 4.340 3.788ab(6)+S(120)=S(111)+S(30) 8.420e-13 2.100 1.140ab(6)+S(120)=S(111)+S(32) 1.263e-12 2.100 1.140ab(6)+S(20)=xa(1)+S(30) 8.420e-13 2.100 1.140ab(6)+S(20)=xa(1)+S(32) 1.263e-12 2.100 1.140ab(6)+S(25)=xf(5)+S(30) 8.420e-13 2.100 1.140ab(6)+S(25)=xf(5)+S(32) 1.263e-12 2.100 1.140ab(6)+S(30)=ab(6)+S(32) 1.263e-12 2.100 1.140ab(6)+S(35)=db(7)+S(30) 8.420e-13 2.100 1.140ab(6)+S(35)=db(7)+S(32) 1.263e-12 2.100 1.140ab(6)+S(38)=db(7)+S(31) 1.752e-03 4.416 12.058ab(6)+S(48)=S(86)+S(30) 8.420e-13 2.100 1.140ab(6)+S(48)=S(86)+S(32) 1.263e-12 2.100 1.140ab(6)+S(48)=S(87)+S(31) 7.242e-04 4.340 14.303ab(6)+S(48)=za(9)+S(31) 1.752e-03 4.416 12.058ab(6)+S(52)=S(40)+S(30) 8.420e-13 2.100 1.140ab(6)+S(52)=S(40)+S(32) 1.263e-12 2.100 1.140

156

ab(6)+S(52)=zf(10)+S(31) 2.124e-02 4.340 3.400ab(6)+S(85)=S(47)+S(31) 2.124e-02 4.340 3.400C3Cl3H(56)+C3Cl4H(26)=C3Cl3H(56)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl3H(56)+S(107)=rad1(11)+S(47) 5.490e+00 3.330 0.630C3Cl3H(56)+S(110)=rad1(11)+C3Cl5(114) 5.490e+00 3.330 0.630C3Cl3H(56)+S(111)=rad1(11)+C3Cl4H(18) 5.490e+00 3.330 0.630C3Cl3H(56)+S(40)=rad1(11)+C3Cl4H(95) 8.420e-01 3.500 9.670C3Cl3H(56)+S(47)=rad1(11)+S(85) 1.850e-02 4.340 6.100C3Cl3H(56)+S(48)=S(85)+C3Cl4H(18) 4.210e-13 2.100 1.140C3Cl3H(56)+S(52)=S(85)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl3H(56)+S(52)=S(85)+C3Cl4H(26) 1.263e-12 2.100 1.140C3Cl3H(56)+S(58)=rad1(11)+rad1(11) 5.490e+00 3.330 0.630C3Cl3H(56)+S(79)=rad1(11)+S(100) 5.490e+00 3.330 0.630C3Cl3H(56)+S(79)=rad1(11)+S(98) 1.020e+03 3.100 8.820C3Cl3H(56)+S(86)=rad1(11)+S(101) 5.490e+00 3.330 0.630C3Cl3H(56)+S(86)=rad1(11)+S(102) 8.420e-01 3.500 9.670C3Cl3H(56)+S(87)=rad1(11)+S(120) 8.420e-01 3.500 9.670C3Cl3H(56)+S(87)=rad1(11)+S(48) 5.490e+00 3.330 0.630C3Cl4H(18)+C3Cl4H(18)=C3Cl3H(56)+C3Cl5H(93) 4.210e-13 2.100 1.140C3Cl4H(18)+C3Cl4H(18)=C3Cl3H(56)+S(110) 4.210e-13 2.100 1.140C3Cl4H(18)+C3Cl4H(26)=C3Cl3H(56)+C3Cl5H(93) 1.684e-12 2.100 1.140C3Cl4H(18)+C3Cl4H(26)=C3Cl3H(56)+S(110) 1.263e-12 2.100 1.140C3Cl4H(18)+S(20)=xa(1)+C3Cl3H(56) 4.210e-13 2.100 1.140C3Cl4H(18)+S(25)=xf(5)+C3Cl3H(56) 4.210e-13 2.100 1.140C3Cl4H(18)+S(30)=ab(6)+C3Cl3H(56) 4.210e-13 2.100 1.140C3Cl4H(18)+S(32)=ab(6)+C3Cl3H(56) 4.210e-13 2.100 1.140C3Cl4H(26)+C3Cl4H(26)=C3Cl3H(56)+C3Cl5H(93) 1.263e-12 2.100 1.140C3Cl4H(26)+S(30)=ab(6)+C3Cl3H(56) 1.263e-12 2.100 1.140C3Cl4H(26)+S(32)=ab(6)+C3Cl3H(56) 1.263e-12 2.100 1.140C3Cl4H(95)+C3Cl4H(18)=C3Cl3H(56)+C3Cl5H(93) 4.210e-13 2.100 1.140C3Cl4H(95)+C3Cl4H(26)=C3Cl3H(56)+C3Cl5H(93) 1.263e-12 2.100 1.140C3Cl4H(95)+S(107)=S(40)+S(47) 1.512e-03 4.340 -1.662C3Cl4H(95)+S(110)=C3Cl5H(93)+C3Cl4H(18) 8.420e-13 2.100 1.140C3Cl4H(95)+S(110)=C3Cl5H(93)+S(102) 4.210e-13 2.100 1.140C3Cl4H(95)+S(110)=S(40)+C3Cl5(114) 1.512e-03 4.340 -1.662C3Cl4H(95)+S(111)=S(40)+C3Cl4H(18) 1.512e-03 4.340 -1.662C3Cl4H(96)+C3Cl4H(18)=S(127)+C3Cl3H(56) 4.210e-13 2.100 1.140C3Cl4H(96)+C3Cl4H(26)=S(127)+C3Cl3H(56) 1.263e-12 2.100 1.140C3Cl4H(96)+S(107)=S(40)+S(47) 1.512e-03 4.340 -1.662C3Cl4H(96)+S(110)=S(127)+C3Cl4H(18) 8.420e-13 2.100 1.140C3Cl4H(96)+S(110)=S(40)+C3Cl5(114) 1.512e-03 4.340 -1.662C3Cl4H(96)+S(111)=S(40)+C3Cl4H(18) 1.512e-03 4.340 -1.662C3Cl5(106)+S(107)=S(47)+C3Cl5H(93) 1.512e-03 4.340 -1.662C3Cl5(106)+S(110)=C3Cl5H(93)+C3Cl5(114) 1.512e-03 4.340 -1.662

157

C3Cl5(106)+S(111)=C3Cl5H(93)+C3Cl4H(18) 1.512e-03 4.340 -1.662C3Cl5(128)+S(107)=S(127)+S(47) 1.512e-03 4.340 -1.662C3Cl5(128)+S(110)=S(127)+C3Cl5(114) 1.512e-03 4.340 -1.662C3Cl5(128)+S(111)=S(127)+C3Cl4H(18) 1.512e-03 4.340 -1.662C3Cl5(128)+S(58)=rad1(11)+S(127) 1.512e-03 4.340 -1.662C3Cl5(128)+S(79)=S(127)+S(100) 1.512e-03 4.340 -1.662C3Cl5(128)+S(86)=S(127)+S(101) 1.512e-03 4.340 -1.662C3Cl5(128)+S(87)=S(127)+S(48) 1.512e-03 4.340 -1.662C3Cl5H(93)+C3Cl4H(18)=S(110)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+C3Cl4H(26)=C3Cl5H(93)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+C3Cl4H(95)=C3Cl5H(93)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+C3Cl4H(95)=C3Cl5H(93)+C3Cl4H(26) 4.210e-13 2.100 1.140C3Cl5H(93)+C3Cl4H(96)=S(127)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+C3Cl4H(96)=S(40)+C3Cl5(106) 5.781e-03 4.340 6.104C3Cl5H(93)+S(101)=S(127)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+S(102)=S(110)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+S(102)=S(110)+C3Cl4H(26) 4.210e-13 2.100 1.140C3Cl5H(93)+S(103)=S(86)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+S(120)=C3Cl4H(95)+S(111) 4.210e-13 2.100 1.140C3Cl5H(93)+S(120)=S(111)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+S(120)=S(111)+C3Cl4H(26) 4.210e-13 2.100 1.140C3Cl5H(93)+S(20)=xa(1)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+S(20)=xa(1)+C3Cl4H(26) 4.210e-13 2.100 1.140C3Cl5H(93)+S(25)=xf(5)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+S(25)=xf(5)+C3Cl4H(26) 4.210e-13 2.100 1.140C3Cl5H(93)+S(30)=ab(6)+C3Cl4H(18) 1.263e-12 2.100 1.140C3Cl5H(93)+S(32)=ab(6)+C3Cl4H(18) 1.263e-12 2.100 1.140Cl(4)+ab(6)=HCl(2)+S(31) 8.469e+04 2.483 10.027Cl(4)+C3Cl3H(56)=C3Cl4H(18) 1.000e+13 0.000 0.000Cl(4)+C3Cl3H(56)=C3Cl4H(26) 1.000e+13 0.000 0.000Cl(4)+C3Cl4H(18)=C3Cl5H(93) 1.000e+13 0.000 0.000Cl(4)+C3Cl4H(18)=S(110) 1.000e+13 0.000 0.000Cl(4)+C3Cl4H(26)=C3Cl5H(93) 1.000e+13 0.000 0.000Cl(4)+C3Cl4H(26)=Cl2(3)+C3Cl3H(56) 1.263e-12 2.100 2.125Cl(4)+C3Cl4H(95)=C3Cl5H(93) 1.000e+13 0.000 0.000Cl(4)+C3Cl4H(96)=S(127) 1.000e+13 0.000 0.000Cl(4)+Cl(4)=Cl2(3) 1.000e+13 0.000 0.000Cl(4)+db(7)=HCl(2)+S(36) 2.823e+04 2.483 9.977Cl(4)+db(7)=HCl(2)+S(38) 5.646e+04 2.483 10.027Cl(4)+fb(8)=HCl(2)+S(35) 5.646e+04 2.483 9.997Cl(4)+fb(8)=HCl(2)+S(44) 5.646e+04 2.483 9.994Cl(4)+rad1(11)=HCl(2)+C3Cl3H(56) 5.646e+04 2.483 10.066Cl(4)+rad1(11)=xa(1) 1.000e+13 0.000 0.000Cl(4)+rad1(11)=xf(5) 1.000e+13 0.000 0.000

158

Cl(4)+S(101)=S(127) 1.000e+13 0.000 0.000Cl(4)+S(102)=S(110) 1.000e+13 0.000 0.000Cl(4)+S(103)=S(86) 1.000e+13 0.000 0.000Cl(4)+S(107)=HCl(2)+S(47) 2.823e+04 2.483 9.869Cl(4)+S(110)=HCl(2)+C3Cl5(114) 2.823e+04 2.483 10.027Cl(4)+S(111)=HCl(2)+C3Cl4H(18) 2.823e+04 2.483 10.023Cl(4)+S(120)=S(111) 1.000e+13 0.000 0.000Cl(4)+S(20)=xa(1) 1.000e+13 0.000 0.000Cl(4)+S(25)=xf(5) 1.000e+13 0.000 0.000Cl(4)+S(30)=ab(6) 1.000e+13 0.000 0.000Cl(4)+S(32)=ab(6) 1.000e+13 0.000 0.000Cl(4)+S(35)=db(7) 1.000e+13 0.000 0.000Cl(4)+S(44)=S(79) 1.000e+13 0.000 0.000Cl(4)+S(45)=fb(8) 1.000e+13 0.000 0.000Cl(4)+S(47)=HCl(2)+S(85) 5.646e+04 2.483 10.066Cl(4)+S(47)=za(9) 1.000e+13 0.000 0.000Cl(4)+S(47)=zf(10) 1.000e+13 0.000 0.000Cl(4)+S(48)=S(40) 1.000e+13 0.000 0.000Cl(4)+S(48)=S(86) 1.000e+13 0.000 0.000Cl(4)+S(52)=Cl2(3)+S(85) 1.263e-12 2.100 2.125Cl(4)+S(52)=S(40) 1.000e+13 0.000 0.000Cl(4)+S(58)=HCl(2)+rad1(11) 2.823e+04 2.483 9.869Cl(4)+S(79)=HCl(2)+S(100) 2.823e+04 2.483 9.966Cl(4)+S(79)=HCl(2)+S(98) 5.646e+04 2.483 9.997Cl(4)+S(85)=S(48) 1.000e+13 0.000 0.000Cl(4)+S(85)=S(52) 1.000e+13 0.000 0.000Cl(4)+S(86)=HCl(2)+S(101) 2.823e+04 2.483 10.027Cl(4)+S(87)=HCl(2)+S(48) 2.823e+04 2.483 10.023Cl(4)+za(9)=Cl2(3)+S(47) 4.210e-13 2.100 13.705Cl(4)+za(9)=HCl(2)+S(48) 5.646e+04 2.483 10.027Cl2(3)+C3Cl3H(56)=Cl(4)+C3Cl4H(18) 8.420e-13 2.100 1.140Cl2(3)+C3Cl4H(18)=Cl(4)+C3Cl5H(93) 8.420e-13 2.100 1.140Cl2(3)+C3Cl4H(18)=Cl(4)+S(110) 8.420e-13 2.100 1.140Cl2(3)+C3Cl4H(26)=Cl(4)+C3Cl5H(93) 8.420e-13 2.100 1.140Cl2(3)+C3Cl4H(95)=Cl(4)+C3Cl5H(93) 8.420e-13 2.100 1.140Cl2(3)+C3Cl4H(96)=Cl(4)+S(127) 8.420e-13 2.100 1.140Cl2(3)+rad1(11)=Cl(4)+xf(5) 8.420e-13 2.100 1.140Cl2(3)+S(101)=Cl(4)+S(127) 8.420e-13 2.100 1.140Cl2(3)+S(102)=Cl(4)+S(110) 8.420e-13 2.100 1.140Cl2(3)+S(103)=Cl(4)+S(86) 8.420e-13 2.100 1.140Cl2(3)+S(120)=Cl(4)+S(111) 8.420e-13 2.100 1.140Cl2(3)+S(20)=xa(1)+Cl(4) 8.420e-13 2.100 1.140Cl2(3)+S(25)=Cl(4)+xf(5) 8.420e-13 2.100 1.140Cl2(3)+S(30)=Cl(4)+ab(6) 8.420e-13 2.100 1.140

159

Cl2(3)+S(32)=Cl(4)+ab(6) 8.420e-13 2.100 1.140Cl2(3)+S(35)=Cl(4)+db(7) 8.420e-13 2.100 1.140Cl2(3)+S(44)=Cl(4)+S(79) 8.420e-13 2.100 1.140Cl2(3)+S(45)=Cl(4)+fb(8) 8.420e-13 2.100 1.140Cl2(3)+S(47)=Cl(4)+zf(10) 8.420e-13 2.100 1.140Cl2(3)+S(48)=Cl(4)+S(40) 8.420e-13 2.100 1.140Cl2(3)+S(48)=Cl(4)+S(86) 8.420e-13 2.100 1.140Cl2(3)+S(52)=Cl(4)+S(40) 8.420e-13 2.100 1.140Cl2(3)+S(85)=Cl(4)+S(48) 8.420e-13 2.100 1.140Cl2(3)+za(9)=db(7) 1.600e+03 3.000 45.000Cl2(3)+zf(10)=db(7) 1.600e+03 3.000 45.000db(7)+C3Cl3H(56)=rad1(11)+S(36) 5.490e+00 3.330 0.630db(7)+C3Cl3H(56)=rad1(11)+S(38) 5.200e-02 3.900 0.860db(7)+C3Cl4H(18)=S(36)+S(111) 1.126e-04 4.331 4.596db(7)+C3Cl4H(18)=S(38)+S(111) 3.117e-04 4.388 8.709db(7)+C3Cl4H(18)=xa(1)+S(36) 5.842e-04 4.388 5.581db(7)+C3Cl4H(26)=S(35)+C3Cl5H(93) 4.210e-13 2.100 1.140db(7)+C3Cl4H(26)=xf(5)+S(36) 5.490e+00 3.330 0.630db(7)+C3Cl4H(26)=xf(5)+S(38) 5.200e-02 3.900 0.860db(7)+C3Cl4H(95)=S(35)+C3Cl5H(93) 4.210e-13 2.100 1.140db(7)+C3Cl4H(95)=S(36)+S(40) 1.512e-03 4.340 -1.662db(7)+C3Cl4H(95)=S(38)+S(40) 5.826e-03 4.305 1.115db(7)+C3Cl4H(96)=S(127)+S(35) 4.210e-13 2.100 1.140db(7)+C3Cl4H(96)=S(36)+S(40) 1.512e-03 4.340 -1.662db(7)+C3Cl4H(96)=S(38)+S(40) 5.826e-03 4.305 1.115db(7)+C3Cl5(106)=S(36)+C3Cl5H(93) 1.512e-03 4.340 -1.662db(7)+C3Cl5(106)=S(38)+C3Cl5H(93) 5.826e-03 4.305 1.115db(7)+C3Cl5(114)=S(38)+S(110) 3.117e-04 4.388 8.709db(7)+C3Cl5(128)=S(127)+S(36) 1.512e-03 4.340 -1.662db(7)+C3Cl5(128)=S(127)+S(38) 5.826e-03 4.305 1.115db(7)+rad1(11)=S(58)+S(36) 1.126e-04 4.331 9.642db(7)+S(101)=S(38)+S(86) 3.117e-04 4.388 8.709db(7)+S(102)=S(35)+S(110) 4.210e-13 2.100 1.140db(7)+S(102)=S(36)+S(86) 1.512e-03 4.340 -1.662db(7)+S(102)=S(38)+S(86) 5.826e-03 4.305 1.115db(7)+S(103)=S(35)+S(86) 4.210e-13 2.100 1.140db(7)+S(103)=S(36)+S(87) 1.512e-03 4.340 -1.662db(7)+S(103)=S(38)+S(87) 5.826e-03 4.305 1.115db(7)+S(120)=S(35)+S(111) 4.210e-13 2.100 1.140db(7)+S(120)=S(36)+S(87) 1.512e-03 4.340 -1.662db(7)+S(120)=S(38)+S(87) 5.826e-03 4.305 1.115db(7)+S(20)=xa(1)+S(35) 4.210e-13 2.100 1.140db(7)+S(20)=za(9)+S(36) 1.512e-03 4.340 -1.662db(7)+S(20)=za(9)+S(38) 5.826e-03 4.305 1.115

160

db(7)+S(25)=xf(5)+S(35) 4.210e-13 2.100 1.140db(7)+S(25)=zf(10)+S(36) 1.512e-03 4.340 -1.662db(7)+S(25)=zf(10)+S(38) 5.826e-03 4.305 1.115db(7)+S(31)=ab(6)+S(36) 9.240e-04 4.378 5.465db(7)+S(35)=fb(8)+S(36) 5.842e-04 4.388 5.581db(7)+S(38)=db(7)+S(36) 5.842e-04 4.388 5.581db(7)+S(44)=fb(8)+S(36) 5.842e-04 4.388 5.581db(7)+S(44)=fb(8)+S(38) 2.162e-03 4.354 9.271db(7)+S(47)=S(36)+S(107) 1.126e-04 4.331 9.642db(7)+S(48)=S(36)+S(87) 1.126e-04 4.331 4.596db(7)+S(48)=S(38)+S(87) 3.117e-04 4.388 8.709db(7)+S(48)=za(9)+S(36) 5.842e-04 4.388 5.581db(7)+S(48)=za(9)+S(38) 2.162e-03 4.354 9.271db(7)+S(52)=S(35)+S(40) 4.210e-13 2.100 1.140db(7)+S(52)=zf(10)+S(36) 5.490e+00 3.330 0.630db(7)+S(52)=zf(10)+S(38) 5.200e-02 3.900 0.860db(7)+S(85)=S(36)+S(47) 5.490e+00 3.330 0.630db(7)+S(85)=S(38)+S(47) 5.200e-02 3.900 0.860db(7)+S(98)=S(36)+S(79) 5.842e-04 4.388 5.581fb(8)+C3Cl3H(56)=rad1(11)+S(35) 1.020e+03 3.100 8.820fb(8)+C3Cl3H(56)=rad1(11)+S(44) 5.200e-02 3.900 0.860fb(8)+C3Cl3H(56)=S(45)+C3Cl4H(18) 1.263e-12 2.100 1.140fb(8)+C3Cl4H(18)=S(35)+S(111) 3.117e-04 4.388 8.709fb(8)+C3Cl4H(18)=S(44)+S(111) 3.117e-04 4.388 8.709fb(8)+C3Cl4H(18)=S(45)+C3Cl5H(93) 1.263e-12 2.100 1.140fb(8)+C3Cl4H(18)=S(45)+S(110) 1.263e-12 2.100 1.140fb(8)+C3Cl4H(18)=xa(1)+S(35) 2.162e-03 4.354 9.271fb(8)+C3Cl4H(26)=S(45)+C3Cl5H(93) 1.263e-12 2.100 1.140fb(8)+C3Cl4H(26)=xf(5)+S(35) 1.020e+03 3.100 8.820fb(8)+C3Cl4H(26)=xf(5)+S(44) 5.200e-02 3.900 0.860fb(8)+C3Cl4H(95)=S(40)+S(44) 5.826e-03 4.305 1.115fb(8)+C3Cl4H(95)=S(45)+C3Cl5H(93) 1.263e-12 2.100 1.140fb(8)+C3Cl4H(96)=S(127)+S(45) 1.263e-12 2.100 1.140fb(8)+C3Cl4H(96)=S(35)+S(40) 5.826e-03 4.305 1.115fb(8)+C3Cl4H(96)=S(40)+S(44) 5.826e-03 4.305 1.115fb(8)+C3Cl5(106)=S(35)+C3Cl5H(93) 5.826e-03 4.305 1.115fb(8)+C3Cl5(106)=S(44)+C3Cl5H(93) 5.826e-03 4.305 1.115fb(8)+C3Cl5(114)=S(35)+S(110) 3.117e-04 4.388 8.709fb(8)+C3Cl5(114)=S(44)+S(110) 3.117e-04 4.388 8.709fb(8)+C3Cl5(128)=S(127)+S(44) 5.826e-03 4.305 1.115fb(8)+S(101)=S(127)+S(45) 1.263e-12 2.100 1.140fb(8)+S(101)=S(35)+S(86) 3.117e-04 4.388 8.709fb(8)+S(101)=S(44)+S(86) 3.117e-04 4.388 8.709fb(8)+S(102)=S(44)+S(86) 5.826e-03 4.305 1.115

161

fb(8)+S(102)=S(45)+S(110) 1.263e-12 2.100 1.140fb(8)+S(103)=S(35)+S(87) 5.826e-03 4.305 1.115fb(8)+S(103)=S(44)+S(87) 5.826e-03 4.305 1.115fb(8)+S(103)=S(45)+S(86) 1.263e-12 2.100 1.140fb(8)+S(120)=S(44)+S(87) 5.826e-03 4.305 1.115fb(8)+S(120)=S(45)+S(111) 1.263e-12 2.100 1.140fb(8)+S(20)=xa(1)+S(45) 1.263e-12 2.100 1.140fb(8)+S(20)=za(9)+S(44) 5.826e-03 4.305 1.115fb(8)+S(25)=xf(5)+S(45) 1.263e-12 2.100 1.140fb(8)+S(25)=zf(10)+S(44) 5.826e-03 4.305 1.115fb(8)+S(30)=ab(6)+S(45) 1.263e-12 2.100 1.140fb(8)+S(31)=ab(6)+S(35) 1.840e-03 4.340 7.000fb(8)+S(31)=ab(6)+S(44) 4.969e-03 4.304 8.942fb(8)+S(32)=ab(6)+S(45) 1.263e-12 2.100 1.140fb(8)+S(35)=db(7)+S(45) 1.263e-12 2.100 1.140fb(8)+S(38)=db(7)+S(35) 2.162e-03 4.354 9.271fb(8)+S(44)=fb(8)+S(35) 2.162e-03 4.354 9.271fb(8)+S(44)=S(45)+S(79) 1.263e-12 2.100 1.140fb(8)+S(48)=S(35)+S(87) 3.117e-04 4.388 8.709fb(8)+S(48)=S(40)+S(45) 1.263e-12 2.100 1.140fb(8)+S(48)=S(44)+S(87) 3.117e-04 4.388 8.709fb(8)+S(48)=S(45)+S(86) 1.263e-12 2.100 1.140fb(8)+S(48)=za(9)+S(35) 2.162e-03 4.354 9.271fb(8)+S(52)=S(40)+S(45) 1.263e-12 2.100 1.140fb(8)+S(52)=zf(10)+S(35) 1.020e+03 3.100 8.820fb(8)+S(52)=zf(10)+S(44) 5.200e-02 3.900 0.860fb(8)+S(85)=S(35)+S(47) 1.020e+03 3.100 8.820fb(8)+S(85)=S(44)+S(47) 5.200e-02 3.900 0.860fb(8)+S(85)=S(45)+S(48) 1.263e-12 2.100 1.140HCl(2)+C3Cl4H(26)=Cl(4)+xf(5) 2.823e+04 2.483 9.960HCl(2)+C3Cl4H(95)=Cl(4)+S(40) 2.823e+04 2.483 9.984HCl(2)+C3Cl4H(96)=Cl(4)+S(40) 2.823e+04 2.483 9.975HCl(2)+C3Cl5(106)=Cl(4)+C3Cl5H(93) 2.823e+04 2.483 9.952HCl(2)+C3Cl5(128)=Cl(4)+S(127) 2.823e+04 2.483 9.984HCl(2)+S(102)=Cl(4)+S(86) 2.823e+04 2.483 9.984HCl(2)+S(103)=Cl(4)+S(87) 2.823e+04 2.483 9.975HCl(2)+S(120)=Cl(4)+S(87) 2.823e+04 2.483 9.984HCl(2)+S(20)=Cl(4)+za(9) 2.823e+04 2.483 9.984HCl(2)+S(25)=Cl(4)+zf(10) 2.823e+04 2.483 9.984HCl(2)+S(40)=db(7) 4.000e+02 3.000 45.000HCl(2)+S(40)=S(79) 4.000e+02 3.000 45.000HCl(2)+S(52)=Cl(4)+zf(10) 2.823e+04 2.483 9.960HCl(2)+S(86)=S(79) 4.000e+02 3.000 45.000HCl(2)+xf(5)=ab(6) 4.000e+02 3.000 45.000

162

HCl(2)+xf(5)=db(7) 4.000e+02 3.000 45.000HCl(2)+za(9)=fb(8) 4.000e+02 3.000 45.000HCl(2)+zf(10)=fb(8) 4.000e+02 3.000 45.000rad1(11)+C3Cl4H(26)=xa(1)+C3Cl3H(56) 1.263e-12 2.100 1.140rad1(11)+C3Cl4H(26)=xf(5)+C3Cl3H(56) 1.263e-12 2.100 1.140rad1(11)+C3Cl4H(26)=xf(5)+C3Cl3H(56) 1.850e-02 4.340 6.100rad1(11)+C3Cl4H(96)=C3Cl3H(56)+S(40) 2.604e-02 4.340 8.405rad1(11)+C3Cl5(106)=C3Cl3H(56)+C3Cl5H(93) 2.604e-02 4.340 8.405rad1(11)+S(103)=C3Cl3H(56)+S(87) 2.604e-02 4.340 8.405rad1(11)+S(110)=S(58)+C3Cl5(114) 1.126e-04 4.331 14.080rad1(11)+S(111)=S(58)+C3Cl4H(18) 1.126e-04 4.331 13.760rad1(11)+S(52)=xa(1)+S(85) 1.263e-12 2.100 1.140rad1(11)+S(52)=xf(5)+S(85) 1.263e-12 2.100 1.140rad1(11)+S(52)=zf(10)+C3Cl3H(56) 1.850e-02 4.340 6.100rad1(11)+S(79)=S(58)+S(100) 1.126e-04 4.331 8.700rad1(11)+S(86)=S(58)+S(101) 1.126e-04 4.331 14.080rad1(11)+S(87)=S(58)+S(48) 1.126e-04 4.331 13.760S(100)+S(110)=S(79)+C3Cl5(114) 1.126e-04 4.331 5.456S(101)+C3Cl4H(18)=S(127)+C3Cl3H(56) 4.210e-13 2.100 1.140S(101)+C3Cl4H(26)=S(127)+C3Cl3H(56) 1.263e-12 2.100 1.140S(101)+S(110)=S(86)+C3Cl5(114) 1.126e-04 4.331 4.596S(102)+C3Cl4H(18)=C3Cl3H(56)+S(110) 4.210e-13 2.100 1.140S(102)+C3Cl4H(26)=C3Cl3H(56)+S(110) 1.263e-12 2.100 1.140S(102)+S(107)=S(47)+S(86) 1.512e-03 4.340 -1.662S(102)+S(110)=S(110)+C3Cl4H(18) 8.420e-13 2.100 1.140S(102)+S(110)=S(86)+C3Cl5(114) 1.512e-03 4.340 -1.662S(102)+S(111)=S(86)+C3Cl4H(18) 1.512e-03 4.340 -1.662S(103)+C3Cl4H(18)=C3Cl3H(56)+S(86) 4.210e-13 2.100 1.140S(103)+C3Cl4H(26)=C3Cl3H(56)+S(86) 1.263e-12 2.100 1.140S(103)+S(107)=S(47)+S(87) 1.512e-03 4.340 -1.662S(103)+S(110)=S(86)+C3Cl4H(18) 8.420e-13 2.100 1.140S(103)+S(110)=S(87)+C3Cl5(114) 1.512e-03 4.340 -1.662S(103)+S(111)=S(87)+C3Cl4H(18) 1.512e-03 4.340 -1.662S(107)+C3Cl4H(18)=xa(1)+S(47) 5.842e-04 4.388 5.581S(107)+C3Cl4H(26)=xf(5)+S(47) 5.490e+00 3.330 0.630S(107)+S(120)=S(47)+S(87) 1.512e-03 4.340 -1.662S(107)+S(20)=za(9)+S(47) 1.512e-03 4.340 -1.662S(107)+S(25)=zf(10)+S(47) 1.512e-03 4.340 -1.662S(107)+S(31)=ab(6)+S(47) 9.240e-04 4.378 5.465S(110)+C3Cl4H(18)=S(111)+C3Cl5(114) 1.126e-04 4.331 4.596S(110)+C3Cl4H(26)=C3Cl5H(93)+C3Cl4H(18) 8.420e-13 2.100 1.140S(110)+C3Cl4H(26)=xf(5)+C3Cl5(114) 5.490e+00 3.330 0.630S(110)+S(120)=S(102)+S(111) 4.210e-13 2.100 1.140S(110)+S(120)=S(111)+C3Cl4H(18) 8.420e-13 2.100 1.140

163

S(110)+S(120)=S(87)+C3Cl5(114) 1.512e-03 4.340 -1.662S(110)+S(20)=xa(1)+C3Cl4H(18) 8.420e-13 2.100 1.140S(110)+S(20)=za(9)+C3Cl5(114) 1.512e-03 4.340 -1.662S(110)+S(25)=xf(5)+C3Cl4H(18) 8.420e-13 2.100 1.140S(110)+S(25)=zf(10)+C3Cl5(114) 1.512e-03 4.340 -1.662S(111)+C3Cl4H(26)=xf(5)+C3Cl4H(18) 5.490e+00 3.330 0.630S(111)+S(120)=S(87)+C3Cl4H(18) 1.512e-03 4.340 -1.662S(111)+S(20)=za(9)+C3Cl4H(18) 1.512e-03 4.340 -1.662S(111)+S(25)=zf(10)+C3Cl4H(18) 1.512e-03 4.340 -1.662S(120)+C3Cl4H(18)=C3Cl3H(56)+S(111) 4.210e-13 2.100 1.140S(120)+C3Cl4H(26)=C3Cl3H(56)+S(111) 1.263e-12 2.100 1.140S(127)+C3Cl3H(56)=rad1(11)+C3Cl5(128) 8.420e-01 3.500 9.670S(127)+C3Cl4H(18)=S(101)+S(110) 1.263e-12 2.100 1.140S(127)+C3Cl4H(26)=C3Cl5H(93)+C3Cl4H(96) 8.420e-13 2.100 1.140S(127)+C3Cl4H(26)=C3Cl5H(93)+S(101) 1.263e-12 2.100 1.140S(127)+C3Cl4H(26)=xf(5)+C3Cl5(128) 8.420e-01 3.500 9.670S(127)+C3Cl4H(95)=C3Cl5(128)+S(40) 5.560e-03 4.340 4.500S(127)+C3Cl4H(95)=C3Cl5H(93)+C3Cl4H(96) 8.420e-13 2.100 1.140S(127)+C3Cl4H(95)=C3Cl5H(93)+S(101) 1.263e-12 2.100 1.140S(127)+C3Cl4H(96)=C3Cl5(128)+S(40) 5.781e-03 4.340 6.104S(127)+C3Cl4H(96)=S(127)+S(101) 1.263e-12 2.100 1.140S(127)+C3Cl5(106)=C3Cl5(128)+C3Cl5H(93) 5.781e-03 4.340 6.104S(127)+S(102)=C3Cl4H(96)+S(110) 8.420e-13 2.100 1.140S(127)+S(102)=C3Cl5(128)+S(86) 5.560e-03 4.340 4.500S(127)+S(102)=S(101)+S(110) 1.263e-12 2.100 1.140S(127)+S(103)=C3Cl5(128)+S(87) 5.781e-03 4.340 6.104S(127)+S(103)=S(86)+S(101) 1.263e-12 2.100 1.140S(127)+S(120)=C3Cl4H(96)+S(111) 8.420e-13 2.100 1.140S(127)+S(120)=C3Cl5(128)+S(87) 5.560e-03 4.340 4.500S(127)+S(120)=S(101)+S(111) 1.263e-12 2.100 1.140S(127)+S(20)=xa(1)+C3Cl4H(96) 8.420e-13 2.100 1.140S(127)+S(20)=xa(1)+S(101) 1.263e-12 2.100 1.140S(127)+S(20)=za(9)+C3Cl5(128) 5.560e-03 4.340 4.500S(127)+S(25)=xf(5)+C3Cl4H(96) 8.420e-13 2.100 1.140S(127)+S(25)=xf(5)+S(101) 1.263e-12 2.100 1.140S(127)+S(30)=ab(6)+S(101) 1.263e-12 2.100 1.140S(127)+S(31)=ab(6)+C3Cl5(128) 1.280e-03 4.340 9.700S(127)+S(32)=ab(6)+S(101) 1.263e-12 2.100 1.140S(127)+S(35)=db(7)+S(101) 1.263e-12 2.100 1.140S(127)+S(35)=fb(8)+C3Cl5(128) 1.480e-03 4.340 10.550S(127)+S(48)=S(86)+S(101) 1.263e-12 2.100 1.140S(127)+S(52)=S(40)+C3Cl4H(96) 8.420e-13 2.100 1.140S(127)+S(52)=S(40)+S(101) 1.263e-12 2.100 1.140S(127)+S(52)=zf(10)+C3Cl5(128) 8.420e-01 3.500 9.670

164

S(127)+S(85)=C3Cl5(128)+S(47) 8.420e-01 3.500 9.670S(127)+S(98)=C3Cl5(128)+S(79) 1.480e-03 4.340 10.550S(20)+C3Cl4H(26)=xa(1)+C3Cl3H(56) 1.263e-12 2.100 1.140S(25)+C3Cl4H(26)=xf(5)+C3Cl3H(56) 1.263e-12 2.100 1.140S(35)+C3Cl4H(18)=db(7)+C3Cl3H(56) 4.210e-13 2.100 1.140S(35)+C3Cl4H(26)=db(7)+C3Cl3H(56) 1.263e-12 2.100 1.140S(35)+C3Cl5H(93)=db(7)+C3Cl4H(18) 1.263e-12 2.100 1.140S(35)+S(107)=fb(8)+S(47) 5.842e-04 4.388 5.581S(35)+S(110)=db(7)+C3Cl4H(18) 8.420e-13 2.100 1.140S(35)+S(40)=db(7)+S(48) 1.263e-12 2.100 1.140S(35)+S(40)=fb(8)+C3Cl4H(95) 1.480e-03 4.340 10.550S(35)+S(48)=db(7)+S(85) 4.210e-13 2.100 1.140S(35)+S(52)=db(7)+S(85) 1.263e-12 2.100 1.140S(35)+S(79)=db(7)+S(44) 8.420e-13 2.100 1.140S(35)+S(79)=fb(8)+S(100) 5.842e-04 4.388 5.581S(35)+S(79)=fb(8)+S(98) 1.730e-03 4.340 7.500S(35)+S(86)=db(7)+S(48) 8.420e-13 2.100 1.140S(35)+S(86)=fb(8)+S(102) 1.480e-03 4.340 10.550S(35)+S(87)=fb(8)+S(120) 1.480e-03 4.340 10.550S(36)+S(110)=db(7)+C3Cl5(114) 1.126e-04 4.331 4.608S(36)+S(79)=db(7)+S(100) 1.126e-04 4.331 4.596S(36)+S(86)=db(7)+S(101) 1.126e-04 4.331 4.608S(38)+S(107)=db(7)+S(47) 5.842e-04 4.388 5.581S(38)+S(79)=db(7)+S(100) 5.842e-04 4.388 5.581S(38)+S(79)=db(7)+S(98) 2.162e-03 4.354 9.271S(40)+C3Cl4H(18)=S(48)+S(110) 1.263e-12 2.100 1.140S(40)+C3Cl4H(26)=S(48)+C3Cl5H(93) 1.263e-12 2.100 1.140S(40)+C3Cl4H(26)=S(52)+C3Cl5H(93) 4.210e-13 2.100 1.140S(40)+C3Cl4H(26)=xf(5)+C3Cl4H(95) 8.420e-01 3.500 9.670S(40)+C3Cl4H(26)=xf(5)+C3Cl4H(96) 1.302e-02 4.340 8.405S(40)+C3Cl4H(95)=S(48)+C3Cl5H(93) 1.263e-12 2.100 1.140S(40)+C3Cl4H(95)=S(52)+C3Cl5H(93) 4.210e-13 2.100 1.140S(40)+C3Cl4H(96)=S(127)+S(48) 1.263e-12 2.100 1.140S(40)+C3Cl4H(96)=S(40)+C3Cl4H(95) 5.781e-03 4.340 6.104S(40)+C3Cl5(106)=C3Cl5H(93)+C3Cl4H(95) 5.781e-03 4.340 6.104S(40)+S(101)=S(127)+S(48) 1.263e-12 2.100 1.140S(40)+S(102)=S(48)+S(110) 1.263e-12 2.100 1.140S(40)+S(102)=S(52)+S(110) 4.210e-13 2.100 1.140S(40)+S(103)=S(48)+S(86) 1.263e-12 2.100 1.140S(40)+S(103)=S(87)+C3Cl4H(95) 5.781e-03 4.340 6.104S(40)+S(120)=S(48)+S(111) 1.263e-12 2.100 1.140S(40)+S(120)=S(52)+S(111) 4.210e-13 2.100 1.140S(40)+S(20)=xa(1)+S(48) 1.263e-12 2.100 1.140S(40)+S(20)=xa(1)+S(52) 4.210e-13 2.100 1.140

165

S(40)+S(20)=za(9)+C3Cl4H(95) 5.560e-03 4.340 4.500S(40)+S(25)=xf(5)+S(48) 1.263e-12 2.100 1.140S(40)+S(25)=xf(5)+S(52) 4.210e-13 2.100 1.140S(40)+S(30)=ab(6)+S(48) 1.263e-12 2.100 1.140S(40)+S(31)=ab(6)+C3Cl4H(95) 1.280e-03 4.340 9.700S(40)+S(32)=ab(6)+S(48) 1.263e-12 2.100 1.140S(40)+S(48)=S(48)+S(86) 1.263e-12 2.100 1.140S(40)+S(52)=S(40)+S(48) 1.263e-12 2.100 1.140S(40)+S(52)=zf(10)+C3Cl4H(95) 8.420e-01 3.500 9.670S(40)+S(52)=zf(10)+C3Cl4H(96) 1.302e-02 4.340 8.405S(40)+S(85)=S(47)+C3Cl4H(95) 8.420e-01 3.500 9.670S(40)+S(98)=S(79)+C3Cl4H(95) 1.480e-03 4.340 10.550S(44)+C3Cl4H(18)=C3Cl3H(56)+S(79) 4.210e-13 2.100 1.140S(44)+C3Cl4H(26)=C3Cl3H(56)+S(79) 1.263e-12 2.100 1.140S(44)+S(107)=fb(8)+S(47) 5.842e-04 4.388 5.581S(44)+S(48)=S(79)+S(85) 4.210e-13 2.100 1.140S(44)+S(52)=S(79)+S(85) 1.263e-12 2.100 1.140S(44)+S(79)=fb(8)+S(100) 5.842e-04 4.388 5.581S(44)+S(79)=fb(8)+S(98) 2.162e-03 4.354 9.271S(45)+C3Cl4H(26)=fb(8)+C3Cl3H(56) 1.263e-12 2.100 1.140S(45)+S(52)=fb(8)+S(85) 1.263e-12 2.100 1.140S(47)+C3Cl4H(26)=xf(5)+S(85) 1.850e-02 4.340 6.100S(47)+C3Cl4H(26)=za(9)+C3Cl3H(56) 1.263e-12 2.100 1.140S(47)+C3Cl4H(26)=zf(10)+C3Cl3H(56) 1.263e-12 2.100 1.140S(47)+C3Cl4H(96)=S(40)+S(85) 2.604e-02 4.340 8.405S(47)+C3Cl5(106)=S(85)+C3Cl5H(93) 2.604e-02 4.340 8.405S(47)+S(103)=S(85)+S(87) 2.604e-02 4.340 8.405S(47)+S(110)=S(107)+C3Cl5(114) 1.126e-04 4.331 14.080S(47)+S(111)=S(107)+C3Cl4H(18) 1.126e-04 4.331 13.760S(47)+S(52)=za(9)+S(85) 1.263e-12 2.100 1.140S(47)+S(52)=zf(10)+S(85) 1.263e-12 2.100 1.140S(47)+S(52)=zf(10)+S(85) 1.850e-02 4.340 6.100S(47)+S(79)=S(100)+S(107) 1.126e-04 4.331 8.700S(47)+S(86)=S(101)+S(107) 1.126e-04 4.331 14.080S(47)+S(87)=S(48)+S(107) 1.126e-04 4.331 13.760S(48)+C3Cl4H(18)=C3Cl3H(56)+S(40) 4.210e-13 2.100 1.140S(48)+C3Cl4H(18)=C3Cl3H(56)+S(86) 4.210e-13 2.100 1.140S(48)+C3Cl4H(18)=S(85)+C3Cl5H(93) 4.210e-13 2.100 1.140S(48)+C3Cl4H(18)=S(85)+S(110) 4.210e-13 2.100 1.140S(48)+C3Cl4H(26)=C3Cl3H(56)+S(40) 1.263e-12 2.100 1.140S(48)+C3Cl4H(26)=C3Cl3H(56)+S(86) 1.263e-12 2.100 1.140S(48)+C3Cl4H(26)=S(85)+C3Cl5H(93) 4.210e-13 2.100 1.140S(48)+C3Cl4H(95)=S(85)+C3Cl5H(93) 4.210e-13 2.100 1.140S(48)+C3Cl4H(96)=S(127)+S(85) 4.210e-13 2.100 1.140

166

S(48)+C3Cl5H(93)=S(40)+C3Cl4H(18) 1.263e-12 2.100 1.140S(48)+C3Cl5H(93)=S(86)+C3Cl4H(18) 1.263e-12 2.100 1.140S(48)+S(101)=S(127)+S(85) 4.210e-13 2.100 1.140S(48)+S(102)=S(85)+S(110) 4.210e-13 2.100 1.140S(48)+S(103)=S(85)+S(86) 4.210e-13 2.100 1.140S(48)+S(107)=za(9)+S(47) 5.842e-04 4.388 5.581S(48)+S(110)=S(86)+C3Cl4H(18) 8.420e-13 2.100 1.140S(48)+S(110)=S(87)+C3Cl5(114) 1.126e-04 4.331 4.596S(48)+S(120)=S(85)+S(111) 4.210e-13 2.100 1.140S(48)+S(20)=xa(1)+S(85) 4.210e-13 2.100 1.140S(48)+S(25)=xf(5)+S(85) 4.210e-13 2.100 1.140S(48)+S(30)=ab(6)+S(85) 4.210e-13 2.100 1.140S(48)+S(32)=ab(6)+S(85) 4.210e-13 2.100 1.140S(48)+S(48)=S(40)+S(85) 4.210e-13 2.100 1.140S(48)+S(48)=S(85)+S(86) 4.210e-13 2.100 1.140S(48)+S(52)=S(40)+S(85) 1.684e-12 2.100 1.140S(48)+S(52)=S(85)+S(86) 1.263e-12 2.100 1.140S(48)+S(79)=S(40)+S(44) 8.420e-13 2.100 1.140S(48)+S(79)=S(44)+S(86) 8.420e-13 2.100 1.140S(48)+S(79)=S(87)+S(100) 1.126e-04 4.331 4.596S(48)+S(79)=S(87)+S(98) 3.117e-04 4.388 8.709S(48)+S(79)=za(9)+S(100) 5.842e-04 4.388 5.581S(48)+S(79)=za(9)+S(98) 2.162e-03 4.354 9.271S(48)+S(86)=S(87)+S(101) 1.126e-04 4.331 4.596S(52)+C3Cl4H(18)=C3Cl3H(56)+S(40) 4.210e-13 2.100 1.140S(52)+C3Cl4H(18)=S(85)+C3Cl5H(93) 1.263e-12 2.100 1.140S(52)+C3Cl4H(18)=S(85)+S(110) 1.263e-12 2.100 1.140S(52)+C3Cl4H(26)=C3Cl3H(56)+S(40) 1.263e-12 2.100 1.140S(52)+C3Cl4H(26)=S(85)+C3Cl5H(93) 1.263e-12 2.100 1.140S(52)+C3Cl4H(95)=S(85)+C3Cl5H(93) 1.263e-12 2.100 1.140S(52)+C3Cl4H(96)=S(127)+S(85) 1.263e-12 2.100 1.140S(52)+C3Cl5H(93)=S(40)+C3Cl4H(18) 1.263e-12 2.100 1.140S(52)+S(101)=S(127)+S(85) 1.263e-12 2.100 1.140S(52)+S(102)=S(85)+S(110) 1.263e-12 2.100 1.140S(52)+S(103)=S(85)+S(86) 1.263e-12 2.100 1.140S(52)+S(107)=zf(10)+S(47) 5.490e+00 3.330 0.630S(52)+S(110)=S(40)+C3Cl4H(18) 8.420e-13 2.100 1.140S(52)+S(110)=zf(10)+C3Cl5(114) 5.490e+00 3.330 0.630S(52)+S(111)=zf(10)+C3Cl4H(18) 5.490e+00 3.330 0.630S(52)+S(120)=S(85)+S(111) 1.263e-12 2.100 1.140S(52)+S(20)=xa(1)+S(85) 1.263e-12 2.100 1.140S(52)+S(25)=xf(5)+S(85) 1.263e-12 2.100 1.140S(52)+S(30)=ab(6)+S(85) 1.263e-12 2.100 1.140S(52)+S(32)=ab(6)+S(85) 1.263e-12 2.100 1.140

167

S(52)+S(52)=S(40)+S(85) 1.263e-12 2.100 1.140S(52)+S(79)=S(40)+S(44) 8.420e-13 2.100 1.140S(52)+S(79)=zf(10)+S(100) 5.490e+00 3.330 0.630S(52)+S(79)=zf(10)+S(98) 1.020e+03 3.100 8.820S(52)+S(85)=S(48)+S(85) 1.263e-12 2.100 1.140S(52)+S(86)=S(40)+S(103) 8.420e-13 2.100 1.140S(52)+S(86)=S(40)+S(48) 8.420e-13 2.100 1.140S(52)+S(86)=zf(10)+S(101) 5.490e+00 3.330 0.630S(52)+S(86)=zf(10)+S(102) 8.420e-01 3.500 9.670S(52)+S(87)=zf(10)+S(103) 1.302e-02 4.340 8.405S(52)+S(87)=zf(10)+S(120) 8.420e-01 3.500 9.670S(52)+S(87)=zf(10)+S(48) 5.490e+00 3.330 0.630S(58)+C3Cl4H(18)=xa(1)+rad1(11) 5.842e-04 4.388 5.581S(58)+C3Cl4H(26)=xf(5)+rad1(11) 5.490e+00 3.330 0.630S(58)+C3Cl4H(95)=rad1(11)+S(40) 1.512e-03 4.340 -1.662S(58)+C3Cl4H(96)=rad1(11)+S(40) 1.512e-03 4.340 -1.662S(58)+C3Cl5(106)=rad1(11)+C3Cl5H(93) 1.512e-03 4.340 -1.662S(58)+S(102)=rad1(11)+S(86) 1.512e-03 4.340 -1.662S(58)+S(103)=rad1(11)+S(87) 1.512e-03 4.340 -1.662S(58)+S(120)=rad1(11)+S(87) 1.512e-03 4.340 -1.662S(58)+S(20)=za(9)+rad1(11) 1.512e-03 4.340 -1.662S(58)+S(25)=zf(10)+rad1(11) 1.512e-03 4.340 -1.662S(58)+S(31)=ab(6)+rad1(11) 9.240e-04 4.378 5.465S(58)+S(35)=fb(8)+rad1(11) 5.842e-04 4.388 5.581S(58)+S(38)=db(7)+rad1(11) 5.842e-04 4.388 5.581S(58)+S(44)=fb(8)+rad1(11) 5.842e-04 4.388 5.581S(58)+S(47)=rad1(11)+S(107) 1.126e-04 4.331 4.596S(58)+S(48)=za(9)+rad1(11) 5.842e-04 4.388 5.581S(58)+S(52)=zf(10)+rad1(11) 5.490e+00 3.330 0.630S(58)+S(85)=rad1(11)+S(47) 5.490e+00 3.330 0.630S(58)+S(98)=rad1(11)+S(79) 5.842e-04 4.388 5.581S(79)+C3Cl4H(18)=S(100)+S(111) 1.126e-04 4.331 4.596S(79)+C3Cl4H(18)=S(44)+C3Cl5H(93) 8.420e-13 2.100 1.140S(79)+C3Cl4H(18)=S(44)+S(110) 8.420e-13 2.100 1.140S(79)+C3Cl4H(18)=S(98)+S(111) 3.117e-04 4.388 8.709S(79)+C3Cl4H(18)=xa(1)+S(100) 5.842e-04 4.388 5.581S(79)+C3Cl4H(18)=xa(1)+S(98) 2.162e-03 4.354 9.271S(79)+C3Cl4H(26)=S(44)+C3Cl5H(93) 8.420e-13 2.100 1.140S(79)+C3Cl4H(26)=xf(5)+S(100) 5.490e+00 3.330 0.630S(79)+C3Cl4H(26)=xf(5)+S(98) 1.020e+03 3.100 8.820S(79)+C3Cl4H(95)=S(40)+S(100) 1.512e-03 4.340 -1.662S(79)+C3Cl4H(95)=S(44)+C3Cl5H(93) 8.420e-13 2.100 1.140S(79)+C3Cl4H(96)=S(127)+S(44) 8.420e-13 2.100 1.140S(79)+C3Cl4H(96)=S(40)+S(100) 1.512e-03 4.340 -1.662

168

S(79)+C3Cl4H(96)=S(40)+S(98) 5.826e-03 4.305 1.115S(79)+C3Cl5(106)=C3Cl5H(93)+S(100) 1.512e-03 4.340 -1.662S(79)+C3Cl5(106)=C3Cl5H(93)+S(98) 5.826e-03 4.305 1.115S(79)+C3Cl5(114)=S(98)+S(110) 3.117e-04 4.388 8.709S(79)+S(101)=S(127)+S(44) 8.420e-13 2.100 1.140S(79)+S(101)=S(86)+S(100) 1.126e-04 4.331 4.596S(79)+S(101)=S(86)+S(98) 3.117e-04 4.388 8.709S(79)+S(102)=S(44)+S(110) 8.420e-13 2.100 1.140S(79)+S(102)=S(86)+S(100) 1.512e-03 4.340 -1.662S(79)+S(103)=S(44)+S(86) 8.420e-13 2.100 1.140S(79)+S(103)=S(87)+S(100) 1.512e-03 4.340 -1.662S(79)+S(103)=S(87)+S(98) 5.826e-03 4.305 1.115S(79)+S(120)=S(44)+S(111) 8.420e-13 2.100 1.140S(79)+S(120)=S(87)+S(100) 1.512e-03 4.340 -1.662S(79)+S(20)=xa(1)+S(44) 8.420e-13 2.100 1.140S(79)+S(20)=za(9)+S(100) 1.512e-03 4.340 -1.662S(79)+S(25)=xf(5)+S(44) 8.420e-13 2.100 1.140S(79)+S(25)=zf(10)+S(100) 1.512e-03 4.340 -1.662S(79)+S(30)=ab(6)+S(44) 8.420e-13 2.100 1.140S(79)+S(31)=ab(6)+S(100) 9.240e-04 4.378 5.465S(79)+S(31)=ab(6)+S(98) 1.840e-03 4.340 7.000S(79)+S(32)=ab(6)+S(44) 8.420e-13 2.100 1.140S(79)+S(85)=S(47)+S(100) 5.490e+00 3.330 0.630S(79)+S(85)=S(47)+S(98) 1.020e+03 3.100 8.820S(79)+S(98)=S(79)+S(100) 5.842e-04 4.388 5.581S(85)+C3Cl4H(26)=C3Cl3H(56)+S(48) 1.263e-12 2.100 1.140S(85)+S(107)=S(47)+S(47) 5.490e+00 3.330 0.630S(85)+S(110)=S(47)+C3Cl5(114) 5.490e+00 3.330 0.630S(85)+S(111)=S(47)+C3Cl4H(18) 5.490e+00 3.330 0.630S(85)+S(86)=S(47)+S(101) 5.490e+00 3.330 0.630S(85)+S(86)=S(47)+S(102) 8.420e-01 3.500 9.670S(85)+S(87)=S(47)+S(120) 8.420e-01 3.500 9.670S(85)+S(87)=S(47)+S(48) 5.490e+00 3.330 0.630S(86)+C3Cl4H(18)=S(101)+S(111) 1.126e-04 4.331 4.596S(86)+C3Cl4H(26)=C3Cl5H(93)+S(103) 8.420e-13 2.100 1.140S(86)+C3Cl4H(26)=S(48)+C3Cl5H(93) 8.420e-13 2.100 1.140S(86)+C3Cl4H(26)=xf(5)+S(101) 5.490e+00 3.330 0.630S(86)+C3Cl4H(26)=xf(5)+S(102) 8.420e-01 3.500 9.670S(86)+C3Cl4H(95)=C3Cl5H(93)+S(103) 8.420e-13 2.100 1.140S(86)+C3Cl4H(95)=S(40)+S(101) 1.512e-03 4.340 -1.662S(86)+C3Cl4H(95)=S(40)+S(102) 5.560e-03 4.340 4.500S(86)+C3Cl4H(95)=S(48)+C3Cl5H(93) 8.420e-13 2.100 1.140S(86)+C3Cl4H(96)=S(127)+S(103) 8.420e-13 2.100 1.140S(86)+C3Cl4H(96)=S(127)+S(48) 8.420e-13 2.100 1.140

169

S(86)+C3Cl4H(96)=S(40)+S(101) 1.512e-03 4.340 -1.662S(86)+C3Cl4H(96)=S(40)+S(102) 5.781e-03 4.340 6.104S(86)+C3Cl5(106)=C3Cl5H(93)+S(101) 1.512e-03 4.340 -1.662S(86)+C3Cl5(106)=C3Cl5H(93)+S(102) 5.781e-03 4.340 6.104S(86)+S(102)=S(103)+S(110) 8.420e-13 2.100 1.140S(86)+S(102)=S(48)+S(110) 8.420e-13 2.100 1.140S(86)+S(102)=S(86)+S(101) 1.512e-03 4.340 -1.662S(86)+S(103)=S(48)+S(86) 8.420e-13 2.100 1.140S(86)+S(103)=S(87)+S(101) 1.512e-03 4.340 -1.662S(86)+S(103)=S(87)+S(102) 5.781e-03 4.340 6.104S(86)+S(120)=S(103)+S(111) 8.420e-13 2.100 1.140S(86)+S(120)=S(48)+S(111) 8.420e-13 2.100 1.140S(86)+S(120)=S(87)+S(101) 1.512e-03 4.340 -1.662S(86)+S(20)=xa(1)+S(103) 8.420e-13 2.100 1.140S(86)+S(20)=xa(1)+S(48) 8.420e-13 2.100 1.140S(86)+S(20)=za(9)+S(101) 1.512e-03 4.340 -1.662S(86)+S(20)=za(9)+S(102) 5.560e-03 4.340 4.500S(86)+S(25)=xf(5)+S(103) 8.420e-13 2.100 1.140S(86)+S(25)=xf(5)+S(48) 8.420e-13 2.100 1.140S(86)+S(25)=zf(10)+S(101) 1.512e-03 4.340 -1.662S(86)+S(31)=ab(6)+S(102) 1.280e-03 4.340 9.700S(86)+S(98)=S(79)+S(102) 1.480e-03 4.340 10.550S(87)+C3Cl4H(18)=S(48)+S(111) 1.126e-04 4.331 4.596S(87)+C3Cl4H(26)=xf(5)+S(103) 1.302e-02 4.340 8.405S(87)+C3Cl4H(26)=xf(5)+S(120) 8.420e-01 3.500 9.670S(87)+C3Cl4H(26)=xf(5)+S(48) 5.490e+00 3.330 0.630S(87)+C3Cl4H(95)=S(40)+S(120) 5.560e-03 4.340 4.500S(87)+C3Cl4H(95)=S(40)+S(48) 1.512e-03 4.340 -1.662S(87)+C3Cl4H(96)=S(40)+S(103) 5.781e-03 4.340 6.104S(87)+C3Cl4H(96)=S(40)+S(120) 5.781e-03 4.340 6.104S(87)+C3Cl4H(96)=S(40)+S(48) 1.512e-03 4.340 -1.662S(87)+C3Cl5(106)=C3Cl5H(93)+S(103) 5.781e-03 4.340 6.104S(87)+C3Cl5(106)=C3Cl5H(93)+S(120) 5.781e-03 4.340 6.104S(87)+C3Cl5(106)=S(48)+C3Cl5H(93) 1.512e-03 4.340 -1.662S(87)+S(102)=S(48)+S(86) 1.512e-03 4.340 -1.662S(87)+S(102)=S(86)+S(120) 5.560e-03 4.340 4.500S(87)+S(103)=S(48)+S(87) 1.512e-03 4.340 -1.662S(87)+S(103)=S(87)+S(120) 5.781e-03 4.340 6.104S(87)+S(120)=S(48)+S(87) 1.512e-03 4.340 -1.662S(87)+S(20)=za(9)+S(120) 5.560e-03 4.340 4.500S(87)+S(20)=za(9)+S(48) 1.512e-03 4.340 -1.662S(87)+S(25)=zf(10)+S(48) 1.512e-03 4.340 -1.662S(87)+S(31)=ab(6)+S(120) 1.280e-03 4.340 9.700S(87)+S(98)=S(79)+S(120) 1.480e-03 4.340 10.550

170

S(98)+S(107)=S(47)+S(79) 5.842e-04 4.388 5.581xa(1)+C3Cl3H(56)=rad1(11)+C3Cl4H(18) 4.210e-13 2.100 1.140xa(1)+C3Cl3H(56)=rad1(11)+C3Cl4H(18) 5.200e-02 3.900 0.860xa(1)+C3Cl4H(18)=rad1(11)+C3Cl5H(93) 4.210e-13 2.100 1.140xa(1)+C3Cl4H(18)=rad1(11)+S(110) 4.210e-13 2.100 1.140xa(1)+C3Cl4H(18)=S(111)+C3Cl4H(18) 3.117e-04 4.388 8.709xa(1)+C3Cl4H(26)=rad1(11)+C3Cl5H(93) 4.210e-13 2.100 1.140xa(1)+C3Cl4H(26)=xf(5)+C3Cl4H(18) 5.200e-02 3.900 0.860xa(1)+C3Cl4H(95)=C3Cl5H(93)+S(20) 4.210e-13 2.100 1.140xa(1)+C3Cl4H(95)=rad1(11)+C3Cl5H(93) 4.210e-13 2.100 1.140xa(1)+C3Cl4H(95)=S(40)+C3Cl4H(18) 5.826e-03 4.305 1.115xa(1)+C3Cl4H(96)=rad1(11)+S(127) 4.210e-13 2.100 1.140xa(1)+C3Cl4H(96)=S(40)+C3Cl4H(18) 5.826e-03 4.305 1.115xa(1)+C3Cl5(106)=C3Cl5H(93)+C3Cl4H(18) 5.826e-03 4.305 1.115xa(1)+C3Cl5(114)=S(110)+C3Cl4H(18) 3.117e-04 4.388 8.709xa(1)+C3Cl5(128)=S(127)+C3Cl4H(18) 5.826e-03 4.305 1.115xa(1)+Cl(4)=Cl2(3)+rad1(11) 4.210e-13 2.100 13.705xa(1)+Cl(4)=HCl(2)+C3Cl4H(18) 5.646e+04 2.483 10.027xa(1)+HCl(2)=db(7) 4.000e+02 3.000 45.000xa(1)+S(101)=rad1(11)+S(127) 4.210e-13 2.100 1.140xa(1)+S(101)=S(86)+C3Cl4H(18) 3.117e-04 4.388 8.709xa(1)+S(102)=rad1(11)+S(110) 4.210e-13 2.100 1.140xa(1)+S(102)=S(110)+S(20) 4.210e-13 2.100 1.140xa(1)+S(102)=S(86)+C3Cl4H(18) 5.826e-03 4.305 1.115xa(1)+S(103)=rad1(11)+S(86) 4.210e-13 2.100 1.140xa(1)+S(103)=S(87)+C3Cl4H(18) 5.826e-03 4.305 1.115xa(1)+S(120)=rad1(11)+S(111) 4.210e-13 2.100 1.140xa(1)+S(120)=S(111)+S(20) 4.210e-13 2.100 1.140xa(1)+S(120)=S(87)+C3Cl4H(18) 5.826e-03 4.305 1.115xa(1)+S(20)=xa(1)+rad1(11) 4.210e-13 2.100 1.140xa(1)+S(20)=za(9)+C3Cl4H(18) 5.826e-03 4.305 1.115xa(1)+S(25)=xf(5)+rad1(11) 4.210e-13 2.100 1.140xa(1)+S(25)=xf(5)+S(20) 4.210e-13 2.100 1.140xa(1)+S(25)=zf(10)+C3Cl4H(18) 5.826e-03 4.305 1.115xa(1)+S(30)=ab(6)+rad1(11) 4.210e-13 2.100 1.140xa(1)+S(32)=ab(6)+rad1(11) 4.210e-13 2.100 1.140xa(1)+S(35)=db(7)+rad1(11) 4.210e-13 2.100 1.140xa(1)+S(38)=db(7)+C3Cl4H(18) 2.162e-03 4.354 9.271xa(1)+S(44)=fb(8)+C3Cl4H(18) 2.162e-03 4.354 9.271xa(1)+S(44)=rad1(11)+S(79) 4.210e-13 2.100 1.140xa(1)+S(45)=fb(8)+rad1(11) 4.210e-13 2.100 1.140xa(1)+S(47)=za(9)+rad1(11) 4.210e-13 2.100 1.140xa(1)+S(48)=rad1(11)+S(40) 4.210e-13 2.100 1.140xa(1)+S(48)=rad1(11)+S(86) 4.210e-13 2.100 1.140

171

xa(1)+S(48)=S(87)+C3Cl4H(18) 3.117e-04 4.388 8.709xa(1)+S(48)=za(9)+C3Cl4H(18) 2.162e-03 4.354 9.271xa(1)+S(52)=rad1(11)+S(40) 4.210e-13 2.100 1.140xa(1)+S(52)=zf(10)+C3Cl4H(18) 5.200e-02 3.900 0.860xa(1)+S(85)=rad1(11)+S(48) 4.210e-13 2.100 1.140xa(1)+S(85)=S(47)+C3Cl4H(18) 5.200e-02 3.900 0.860xf(5)+C3Cl3H(56)=rad1(11)+C3Cl4H(18) 1.263e-12 2.100 1.140xf(5)+C3Cl4H(18)=rad1(11)+C3Cl5H(93) 1.263e-12 2.100 1.140xf(5)+C3Cl4H(18)=rad1(11)+S(110) 1.263e-12 2.100 1.140xf(5)+C3Cl4H(26)=rad1(11)+C3Cl5H(93) 1.263e-12 2.100 1.140xf(5)+C3Cl4H(95)=C3Cl5H(93)+S(25) 4.210e-13 2.100 1.140xf(5)+C3Cl4H(95)=rad1(11)+C3Cl5H(93) 1.263e-12 2.100 1.140xf(5)+C3Cl4H(96)=rad1(11)+S(127) 1.263e-12 2.100 1.140xf(5)+C3Cl5(106)=C3Cl5H(93)+C3Cl4H(26) 2.604e-02 4.340 8.405xf(5)+rad1(11)=xa(1)+rad1(11) 1.263e-12 2.100 1.140xf(5)+S(101)=rad1(11)+S(127) 1.263e-12 2.100 1.140xf(5)+S(102)=rad1(11)+S(110) 1.263e-12 2.100 1.140xf(5)+S(102)=S(110)+S(25) 4.210e-13 2.100 1.140xf(5)+S(103)=rad1(11)+S(86) 1.263e-12 2.100 1.140xf(5)+S(120)=rad1(11)+S(111) 1.263e-12 2.100 1.140xf(5)+S(120)=S(111)+S(25) 4.210e-13 2.100 1.140xf(5)+S(20)=xa(1)+rad1(11) 1.263e-12 2.100 1.140xf(5)+S(25)=xf(5)+rad1(11) 1.263e-12 2.100 1.140xf(5)+S(30)=ab(6)+rad1(11) 1.263e-12 2.100 1.140xf(5)+S(32)=ab(6)+rad1(11) 1.263e-12 2.100 1.140xf(5)+S(35)=db(7)+rad1(11) 1.263e-12 2.100 1.140xf(5)+S(44)=rad1(11)+S(79) 1.263e-12 2.100 1.140xf(5)+S(45)=fb(8)+rad1(11) 1.263e-12 2.100 1.140xf(5)+S(47)=za(9)+rad1(11) 1.263e-12 2.100 1.140xf(5)+S(47)=zf(10)+rad1(11) 1.263e-12 2.100 1.140xf(5)+S(48)=rad1(11)+S(40) 1.263e-12 2.100 1.140xf(5)+S(48)=rad1(11)+S(86) 1.263e-12 2.100 1.140xf(5)+S(52)=rad1(11)+S(40) 1.263e-12 2.100 1.140xf(5)+S(52)=zf(10)+C3Cl4H(26) 1.850e-02 4.340 6.100xf(5)+S(85)=rad1(11)+S(48) 1.263e-12 2.100 1.140za(9)+C3Cl3H(56)=rad1(11)+S(20) 8.420e-01 3.500 9.670za(9)+C3Cl3H(56)=rad1(11)+S(48) 5.200e-02 3.900 0.860za(9)+C3Cl3H(56)=S(47)+C3Cl4H(18) 4.210e-13 2.100 1.140za(9)+C3Cl4H(18)=S(47)+C3Cl5H(93) 4.210e-13 2.100 1.140za(9)+C3Cl4H(18)=S(47)+S(110) 4.210e-13 2.100 1.140za(9)+C3Cl4H(18)=S(48)+S(111) 3.117e-04 4.388 8.709za(9)+C3Cl4H(26)=S(47)+C3Cl5H(93) 4.210e-13 2.100 1.140za(9)+C3Cl4H(26)=xf(5)+S(20) 8.420e-01 3.500 9.670za(9)+C3Cl4H(26)=xf(5)+S(48) 5.200e-02 3.900 0.860

172

za(9)+C3Cl4H(95)=S(40)+S(48) 5.826e-03 4.305 1.115za(9)+C3Cl4H(95)=S(47)+C3Cl5H(93) 4.210e-13 2.100 1.140za(9)+C3Cl4H(96)=S(127)+S(47) 4.210e-13 2.100 1.140za(9)+C3Cl4H(96)=S(40)+S(20) 5.781e-03 4.340 6.104za(9)+C3Cl4H(96)=S(40)+S(48) 5.826e-03 4.305 1.115za(9)+C3Cl5(106)=C3Cl5H(93)+S(20) 5.781e-03 4.340 6.104za(9)+C3Cl5(106)=S(48)+C3Cl5H(93) 5.826e-03 4.305 1.115za(9)+C3Cl5(114)=S(48)+S(110) 3.117e-04 4.388 8.709za(9)+C3Cl5(128)=S(127)+S(48) 5.826e-03 4.305 1.115za(9)+S(101)=S(127)+S(47) 4.210e-13 2.100 1.140za(9)+S(101)=S(48)+S(86) 3.117e-04 4.388 8.709za(9)+S(102)=S(47)+S(110) 4.210e-13 2.100 1.140za(9)+S(102)=S(48)+S(86) 5.826e-03 4.305 1.115za(9)+S(103)=S(47)+S(86) 4.210e-13 2.100 1.140za(9)+S(103)=S(48)+S(87) 5.826e-03 4.305 1.115za(9)+S(103)=S(87)+S(20) 5.781e-03 4.340 6.104za(9)+S(120)=S(47)+S(111) 4.210e-13 2.100 1.140za(9)+S(120)=S(48)+S(87) 5.826e-03 4.305 1.115za(9)+S(20)=xa(1)+S(47) 4.210e-13 2.100 1.140za(9)+S(20)=za(9)+S(48) 5.826e-03 4.305 1.115za(9)+S(25)=xf(5)+S(47) 4.210e-13 2.100 1.140za(9)+S(25)=zf(10)+S(48) 5.826e-03 4.305 1.115za(9)+S(30)=ab(6)+S(47) 4.210e-13 2.100 1.140za(9)+S(31)=ab(6)+S(20) 1.280e-03 4.340 9.700za(9)+S(32)=ab(6)+S(47) 4.210e-13 2.100 1.140za(9)+S(35)=db(7)+S(47) 4.210e-13 2.100 1.140za(9)+S(35)=fb(8)+S(20) 1.480e-03 4.340 10.550za(9)+S(44)=fb(8)+S(48) 2.162e-03 4.354 9.271za(9)+S(44)=S(47)+S(79) 4.210e-13 2.100 1.140za(9)+S(45)=fb(8)+S(47) 4.210e-13 2.100 1.140za(9)+S(48)=S(40)+S(47) 4.210e-13 2.100 1.140za(9)+S(48)=S(47)+S(86) 4.210e-13 2.100 1.140za(9)+S(48)=S(48)+S(87) 3.117e-04 4.388 8.709za(9)+S(52)=S(40)+S(47) 4.210e-13 2.100 1.140za(9)+S(52)=zf(10)+S(20) 8.420e-01 3.500 9.670za(9)+S(52)=zf(10)+S(48) 5.200e-02 3.900 0.860za(9)+S(85)=S(47)+S(20) 8.420e-01 3.500 9.670za(9)+S(85)=S(47)+S(48) 4.210e-13 2.100 1.140za(9)+S(85)=S(47)+S(48) 5.200e-02 3.900 0.860za(9)+S(98)=S(79)+S(20) 1.480e-03 4.340 10.550zf(10)+C3Cl3H(56)=rad1(11)+S(25) 8.420e-01 3.500 9.670zf(10)+C3Cl3H(56)=S(47)+C3Cl4H(18) 1.263e-12 2.100 1.140zf(10)+C3Cl4H(18)=S(47)+C3Cl5H(93) 1.263e-12 2.100 1.140zf(10)+C3Cl4H(18)=S(47)+S(110) 1.263e-12 2.100 1.140

173

zf(10)+C3Cl4H(26)=S(47)+C3Cl5H(93) 1.263e-12 2.100 1.140zf(10)+C3Cl4H(26)=xf(5)+S(25) 8.420e-01 3.500 9.670zf(10)+C3Cl4H(95)=S(40)+S(25) 5.560e-03 4.340 4.500zf(10)+C3Cl4H(95)=S(47)+C3Cl5H(93) 1.263e-12 2.100 1.140zf(10)+C3Cl4H(96)=S(127)+S(47) 1.263e-12 2.100 1.140zf(10)+C3Cl4H(96)=S(40)+S(25) 5.781e-03 4.340 6.104zf(10)+C3Cl5(106)=C3Cl5H(93)+S(25) 5.781e-03 4.340 6.104zf(10)+C3Cl5(106)=S(52)+C3Cl5H(93) 2.604e-02 4.340 8.405zf(10)+C3Cl5(128)=S(127)+S(25) 5.560e-03 4.340 4.500zf(10)+rad1(11)=xa(1)+S(47) 1.263e-12 2.100 1.140zf(10)+S(101)=S(127)+S(47) 1.263e-12 2.100 1.140zf(10)+S(102)=S(47)+S(110) 1.263e-12 2.100 1.140zf(10)+S(102)=S(86)+S(25) 5.560e-03 4.340 4.500zf(10)+S(103)=S(47)+S(86) 1.263e-12 2.100 1.140zf(10)+S(103)=S(87)+S(25) 5.781e-03 4.340 6.104zf(10)+S(120)=S(47)+S(111) 1.263e-12 2.100 1.140zf(10)+S(120)=S(87)+S(25) 5.560e-03 4.340 4.500zf(10)+S(20)=xa(1)+S(47) 1.263e-12 2.100 1.140zf(10)+S(20)=za(9)+S(25) 5.560e-03 4.340 4.500zf(10)+S(25)=xf(5)+S(47) 1.263e-12 2.100 1.140zf(10)+S(30)=ab(6)+S(47) 1.263e-12 2.100 1.140zf(10)+S(31)=ab(6)+S(25) 1.280e-03 4.340 9.700zf(10)+S(32)=ab(6)+S(47) 1.263e-12 2.100 1.140zf(10)+S(35)=db(7)+S(47) 1.263e-12 2.100 1.140zf(10)+S(35)=fb(8)+S(25) 1.480e-03 4.340 10.550zf(10)+S(44)=S(47)+S(79) 1.263e-12 2.100 1.140zf(10)+S(45)=fb(8)+S(47) 1.263e-12 2.100 1.140zf(10)+S(47)=za(9)+S(47) 1.263e-12 2.100 1.140zf(10)+S(48)=S(40)+S(47) 1.263e-12 2.100 1.140zf(10)+S(48)=S(47)+S(86) 1.263e-12 2.100 1.140zf(10)+S(52)=S(40)+S(47) 1.263e-12 2.100 1.140zf(10)+S(52)=zf(10)+S(25) 8.420e-01 3.500 9.670zf(10)+S(85)=S(47)+S(25) 8.420e-01 3.500 9.670zf(10)+S(85)=S(47)+S(48) 1.263e-12 2.100 1.140zf(10)+S(98)=S(79)+S(25) 1.480e-03 4.340 10.550END

174