Extracting microkinetic insights from macroscopic measurements: A power law modelling framework for catalytic reaction mechanism analysis

Identifying catalytic reaction mechanisms is essential for the optimisation of chemical reactors and the design of efficient catalysts. While power law models are widely used in an industrial context for their simplicity, they are considered to be empirical and have, therefore, been underutilised for the development of mechanistic insights. This study introduces a novel framework that extends the theoretical analysis of power law models to enable reaction mechanism discrimination using experimentally accessible parameters including apparent reaction orders and activation energies. By establishing a direct physicochemical link between macroscopic kinetic parameters and microkinetic states (surface coverages), a set of generalisable conditional rules is developed to systematically identify dominant reaction pathways, rate-limiting steps, and most abundant reaction intermediates. This represents the first application of a mechanistic power law modelling approach to complex catalytic systems involving significant negative reaction orders and dual-site mechanisms. The framework is validated on two catalytic reactions exhibiting unusual macroscopic behaviour namely ethane hydrogenolysis over silica-supported Group VIII metals and the water–gas shift reaction over Pt/CeO 2 . Results demonstrate that this methodology simplifies the analysis of multi-route and multi-site reaction networks, providing mechanistic explanations for variations in kinetic parameters with respect to operating conditions. This approach offers a new, efficient tool for reaction mechanism analysis, reducing reliance on exhaustive microkinetic modelling while enhancing both knowledge discovery and practical application.