Activity Trends\nof Methane Oxidation Catalysts under\nEmission Conditions

Abstract

The emission of unburned exhaust methane from natural-gas-based\ncombustion engines is an important source of greenhouse gas to control.\nRutile IrO₂ has shown great potential as a methane oxidation\ncatalyst, but further developments for practical use have been slow\nas the kinetic mechanism and design principles under exhaust conditions\nare poorly understood. Here, we demonstrate the experiment-validated\nfirst-principles-based microkinetic model (MKM) for IrO₂ to elucidate the mechanistic insights and develop the descriptor-based\nMKM screening pipeline to discover feasible catalysts for methane\ncomplete oxidation. The framework uses a minimal number of ab initio\ndescriptors suggested by sensitivity analysis and scaling relations,\nequipped further with a machine learning model to extend the search\nspace to a larger scale. We search through hundreds of doped rutile\noxides by constructing the MKM-based activity map and suggest promising\nPareto-optimum candidates. The proposed workflow can be extended to\nexplore other industrial catalysts under experimental conditions.