Abstract

The high global warming potentials (GWPs) of current halocarbon flame suppressants and refrigerants motivate the need for a next-generation of eco-friendly compounds. Since experimental study of safety-critical combustion properties are complex and costly, predictive kinetic modeling using microkinetic models of halocarbon combustion is crucial in screening proposed compounds. As these models are currently constructed manually, progress is slow and error-prone due to the vast number of possible species and reactions to consider and sparse thermokinetic data available in the literature. To automate the generation of microkinetic models for halocarbon combustion, I extend the Reaction Mechanism Generator (RMG), an open-source software which automatically builds detailed kinetic models from user-specified initial conditions. In this work, I present the addition of halogen (fluorine, chlorine, and bromine) thermochemistry, kinetics, statistical mechanics, and transport properties to RMG.I calculate standard enthalpies, entropies, and heat capacities for 16,813 halocarbons us- ing an automated high-fidelity thermochemistry workflow. This new dataset is used to train an extensive ensemble of group additivity values and hydrogen bond increment groups within the RMG framework. I update RMG's existing reaction family templates to include halogens, and create 11 new reactions families specific to halogen chemistry. Notably, I compute rates for more than 1000 elementary reactions via ab inito methods and transition state theory, and these kinetic data are combined with kinetics from literature sources to train rate rule decision tree estimators. I derive halogen groups in RMG's statistical mechanics database, enabling model generation with RMG's pressure dependence module. Halogen groups are also incorporated in RMG's transport database to estimate parameters for the Lennard-Jones potential. To demonstrate RMG's capability for predicting halocarbon combustion, I use RMG to build a methane flame suppression model for CF3Br, a current flame suppressant, and 2-BTP (CH2 -CBrCF3), a greener alternative. The laminar flame speeds of RMG's CF3Br/2-BTP model show good agreement with a published model under a variety of reaction conditions. RMG also accurately predicts laminar flame speeds for hydroflu- orocarbon (HFC) refrigerants compared to experimental data, but overestimates burning velocities for hydrofluoroolefin (HFO) refrigerants. Automating the generation of detailed kinetic models for halocarbon combustion will facilitate the exploration of previously unexplored reaction pathways, thereby accelerating the development of greener refrigerants and suppressants, as well as advancing the field of automated mechanism generation. This work also presents RMG-electrocat, a first-of-its-kind automated mechanism gener- ator for electrocatalysis. I incorporate charged species, proton-coupled electron transfer reactions, the computational hydrogen electrode model, potential-dependent kinetics, and an electrode reactor in RMG to enable the generation of electrochemical reaction mechanisms. As a proof-of-concept for this framework, RMG-electrocat is used to generate a microkinetic model for carbon dioxide reduction (CO2RR) on copper (111) with 37 species and 292 reactions. RMG-electrocat discovers chemical and electrochemical pathways to many experimentally observed CO2RR products includ- ing formic acid, methane, ethylene, methanol, and ethanol. RMG-electrocat will advance the under- standing of complicated electrocatalytic reaction mechanisms and facilitate the discovery of novel electrocatalysts for many complex electrochemical processes such as CO2RR.--Author's abstract

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