Implementing the Blowers-Masel Approximation to Scale Activation Energy Based on Reaction Enthalpy in Mean-field Micro-kinetic Modeling for Catalytic Methane Partial Oxidation

Mean-field micro-kinetic modeling is a powerful tool for catalyst design and the simulation of catalytic processes. The reaction enthalpies in a micro-kinetic model often need to be adjusted when changing species’ binding energies to model differ- ent catalysts, when performing thermodynamic sensitivity analyses, and when fitting experimental data. When altering reaction enthalpies, the activation energies should also be reasonably altered, to ensure realistic reaction rates. The Blowers-Masel ap- proximation (BMA) relates the reaction barrier to the reaction enthalpy. Unlike the Brønsted-Evans-Polani (BEP) relationship, the BMA requires less data because only one parameter, the intrinsic activation energy, needs to be determined. We validate this novel application of BMA relations to model surface reactions by comparing against density functional theory (DFT) data taken from literature. By incorporating the BMA rate description into the open-source Cantera software we enable a new work- flow, demonstrated herein, allowing rapid screening of catalysts using linear scaling relationships (LSRs) and BMA kinetics within the process simulation software. For demonstration purposes, a catalyst screening for catalytic methane partial oxidation (CMPO) on 81 hypothetical metals is conducted. We compare the results with and without BMA-corrected rates. The heat maps of various descriptors (e.g. CH4 conver- sion, syngas yield) show that using BMA rates instead of Arrhenius rates (with constant activation energies) changes which metals are most active. Heat maps of sensitivity analyses can help identify which reactions or species are most influential in shaping the descriptor map patterns. Our findings indicate that while using BMA-adjusted rates didn't markedly affect the most sensitive reactions, it did change the most influential species.