Genesys-Cat: automatic microkinetic model generation for heterogeneous catalysis with improved Bayesian optimization

Abstract

Developing complex microkinetic models for heterogeneous catalysis is a cumbersome task, often lacking accuracy if proper kinetic properties are unknown. Therefore, a novel rule-based microkinetic model generator for heterogeneous catalysis called Genesys-Cat is presented. Genesys-Cat automatically generates an elementary reaction network based on user-defined reaction families. One of the main advantages of Genesys-Cat is the determination of kinetic properties based on a limited set of experimental data when ab initio data is absent. Genesys-Cat employs an improved, highly efficient Bayesian optimization algorithm to estimate accurate kinetic properties with limited computational and experimental effort. In this way, computationally and experimentally efficient, accurate microkinetic models (R² = 0.89–0.99) can be generated for a wide range of processes involving heterogeneous catalysts. Genesys-Cat facilitates the automatic generation of gas and surface-phase mechanisms in parallel, which is compatible with standard reactor model simulators like Chemkin and Cantera. The benefits of our approach are demonstrated in the catalytic cracking of iso-octane for three different zeolites, while our model generator is also applicable to conventional metal catalysts. The obtained microkinetic models identify the dominant reaction pathways and can be employed for rational catalyst and reactor design.