Building large microkinetic models with first-principles׳ accuracy at reduced computational cost

Abstract

We present a systematic hierarchical multiscale framework for parameterization of large microkinetic models that delivers first-principles׳ accuracy at significantly reduced computational cost. The framework leverages recently introduced first-principles-based semi-empirical methods (FPSEM), such as group additivity and Brønsted–Evans–Polanyi (BEP) relations, for surface reactions, local sensitivity analysis, and a heuristic classification of the order of corrections to produce a hierarchy or family of models of improved accuracy. We demonstrate this approach to the moderate size ethanol steam reforming mechanism on Pt, consisting of 67 species (14 gas, 53 surface) and 160 reversible elementary-like reactions, for which the ‘exact’ density functional theory (DFT)-based model is available. We find that the majority of refined parameters are surface species free energies and lateral interactions, underscoring the importance of thermodynamics in kinetic mechanisms.