Probabilistic microkinetic modeling: Species balance equations for a catalyst surface containing multiple short-range order parameters to capture spatial correlations

Abstract

Adsorbed molecules on a catalyst almost always arrange themselves in a manner that is far from perfectly random, which gives rise to spatial correlations. These correlations are a result of the interactions between the adsorbed species (adspecies) as well as elementary processes such as diffusion and reaction events that shape the adspecies arrangements. Despite their importance, spatial correlations are usually ignored while writing species balance equations for the modeling of heterogeneous catalytic systems. Recently, we have introduced a probabilistic microkinetic modeling (p-MKM) framework that aims at incorporating spatial correlations in the form of a short-ranged order (SRO) parameter into species balance equations. Here, we extend the approach to catalytic systems of higher complexity, namely, longer interactions and multiple species. This is made possible by including multiple pair probabilities in the p-MKM model for the first time. The interplay between different SRO parameters is probed. An important consideration is how many pair probabilities should be included to capture the underlying complexity with sufficient accuracy.