Speeding up the Detection of Adsorbate Lateral Interactions in Graph-Theoretical Kinetic Monte Carlo Simulations

Kinetic Monte Carlo (KMC) has become an indispensable tool in heterogeneous catalyst discovery, but realistic simulations remain computationally demanding on account of the need to capture complex and long-range lateral interactions between adsorbates. The Zacros software package (https://zacros.org) adopts a graph-theoretical cluster expansion (CE) framework that allows such interactions to be computed with a high degree of generality and fidelity. This involves solving a series of subgraph isomorphism problems in order to identify relevant interaction patterns in the lattice. In an effort to reduce the computational burden, we have adapted two well-known subgraph isomorphism algorithms, namely, VF2 and RI, for use in KMC simulations and implemented them in Zacros. To benchmark their performance, we simulate a previously established model of catalytic NO oxidation, treating the O* lateral interactions with a series of progressively larger CEs. For CEs with long-range interactions, VF2 and RI are found to provide impressive speedups relative to simpler algorithms. RI performs best, giving speedups reaching more than 150× when combined with OpenMP parallelization. We also simulate a recently developed methane cracking model, showing that RI offers significant improvements in performance at high surface coverages

Assessing the Impact of Adlayer Description Fidelity on Theoretical Predictions of Coking on Ni(111) at Steam Reforming Conditions

Methane steam reforming is an important industrial process for hydrogen production, employing Ni as a low-cost, highly active catalyst, which, however, suffers from coking due to methane cracking. Coking is the accumulation of a stable poison over time, occurring at high temperatures; thus, to a first approximation, it can be treated as a thermodynamic problem. In this work, we developed an Ab initio kinetic Monte Carlo (KMC) model for methane cracking on Ni(111) at steam reforming conditions. The model captures C−H activation kinetics in detail, while graphene sheet formation is described at the level of thermodynamics, to obtain insights into the “terminal (poisoned) state” of graphene/coke within reasonable computational times. We used cluster expansions (CEs) of progressively higher fidelity to systematically assess the influence of effective cluster interactions between adsorbed or covalently bonded C and CH species on the “terminal state” morphology. Moreover, we compared the predictions of KMC models incorporating these CEs into mean-field microkinetic models in a consistent manner. The models show that the “terminal state” changes significantly with the level of fidelity of the CEs. Furthermore, high-fidelity simulations predict C−CH island/rings that are largely disconnected at low temperatures but completely encapsulate the Ni(111) surface at high temperatures