A methane pyrolysis chemical kinetic model is analyzed using a skeletal reduction technique to identify key reactions and dominant chemical pathways for the conversion of methane into acetylene (C 2 H 2 ). The resulting skeletal model is then optimized, using a genetic algorithm combined with a Nelder–Mead method, for relevant methane plasma pyrolysis temperature conditions and two operating pressures (0.4 and 1 atm). The statistical fitness of the model is assessed with a robust methodology based on the maximum likelihood estimation theory. Thus, the methane, ethylene (C 2 H 4 ), acetylene and temperature profiles of the optimized reduced model are validated against a reference model. The analysis of the chemical pathways obtained with the skeletal reduction allows the identification of two conversion regimes, below and above 2500 K. In both regimes the presence of hydrogen radicals is key for the conversion of methane into ethylene and acetylene. This is justified by the hydrogen abstraction reactions significantly lowering the energy barrier compared to direct dissociation of the C-H bond in hydrocarbon molecules. This work describes the methane conversion to C 2 hydrocarbons at higher temperatures than previously assessed and provides a recipe for obtaining reduced models for this chemistry for use in plasma computational fluid dynamics (CFD). The directions of future contributions are briefly discussed, namely the inclusion of polycyclic aromatic hydrocarbons (PAHs) and free electron collisions as components of a reduced model for plasma CFD. • Skeletal reduction identifies the key reactions and dominant chemical pathways. • Hydrogen and methyl radicals drive conversion and formation of higher hydrocarbons. • Genetic algorithm optimizes skeletal model against a reference model. • Statistical fitness of the optimized models is robustly assessed using a maximum likelihood estimation approach.
Vargas et al. (Thu,) studied this question.