Automating the generation of detailed kinetic models for halocarbon combustion with the Reaction Mechanism Generator

Abstract

Originally developed to predict the chemical kinetics of hydrocarbon combustion via automated generation of detailed reaction mechanisms, Reaction Mechanism Generator (RMG) contains extensive thermokinetic data for C,H,O chemisty, and has more recently been expanded to nitrogen and sulfur. In this work, we present the addition of halogen (fluorine, chlorine, and bromine) chemisty to RMG to enable automated generation of detailed kinetic models for halocarbon combustion. RMG’s existing reaction templates are updated to include halogens, and 11 new reactions families are created specific to halogen chemistry. Notably, kinetics for more than 1000 elementary reactions are calculated 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. Additionally, halogen groups are added to RMG’s statistical mechanics database, enabling model generation with RMG’s pressure dependence module and automated computation of microcanonical rate constants for unimolecular networks. Halogen groups are also incorporated in RMG’s transport database to provide estimated parameters for the Lennard-Jones potential, important for transport-dependent simulations including laminar flame speeds. To demonstrate RMG’s capability for predicting halocarbon combustion, RMG is used to build a flame suppression model for 2-BTP (CH2=CBrCF3) in methane flames. The laminar flame speeds of RMG’s 2-BTP model show good agreement with a published model under a variety of reaction conditions. 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.