Footprint-aware Microkinetics Reveal Spatial Correlations with Catalytic Consequences
- 1Laboratory for Chemical Technology, Ghent University, Technologiepark-Zwijnaarde 125, Gent, Belgium, 9052
Abstract
Metal catalysis often involves bulky molecules that cover catalyst surface areas beyond a single exposed metal atom. Common multi-site models account for adsorbate size with simple mean-field correction factors, but neglect how multi-site adsorbates become spatially correlated to avoid overlapping. Here, we combine prior theoretical constructions—the reduction of the Master equation in the fast-diffusion limit and the Widom insertion approach—to develop a footprint-aware microkinetic framework where adsorbates interact through hard exclusion. We use Monte Carlo simulations to construct surrogate models of vacant site clusters and neighboring reactant pairs needed for elementary reaction steps, which introduce missing footprint effects into conventional kinetic models. These models retain explicit kinetic and thermodynamic parameters, support standard mechanistic analyses, and can be reused across temperatures and reaction conditions without repeated configurational sampling. We illustrate the framework using unimolecular and bimolecular reactions of an adsorbate with a seven-site footprint, resembling benzene and phenol. Footprint-induced correlations have two effects relative to mean-field treatments: they (i) enrich the sites surrounding multi-site adsorbates with single-site co-adsorbates or vacancies, and (ii) aggregate empty sites into clusters that accommodate additional multi-site adsorbates. These correlations alter absolute rates, reactant pressure trends, step reversibilities, and degrees of rate control. The correlation effects are most pronounced for bimolecular reactions when surfaces are crowded by multi-site adsorbates and adsorption events at single sites or site pairs are kinetically relevant. For one bimolecular reaction, the mean-field approximation fits footprint-aware rates and elementary-step reversibility across a given range of pressures for a single reactant, but only after reducing the apparent footprint from seven to 3.3 sites and weakening the adsorption free energy by 12 RT. The approximation furthermore predicts different coreactant pressure dependences. Consequently, quantitative model agreement with kinetic trends can conceal physically inaccurate parameters and mechanistic interpretations when accounting for adsorbate size, while neglecting spatial correlations.
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BibTeX
@misc{fischer2026footprintaware,
title = {{Footprint-aware Microkinetics Reveal Spatial Correlations with Catalytic Consequences}},
author = {Ari F. Fischer and Mark Saeys},
howpublished = {ChemRxiv},
year = {2026},
month = oct,
doi = {10.26434/chemrxiv.15011017/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15011017/v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Footprint-aware Microkinetics Reveal Spatial Correlations with Catalytic Consequences
AU - Ari F. Fischer
AU - Mark Saeys
PY - 2026
DA - 2026/10/25
PB - ChemRxiv
DO - 10.26434/chemrxiv.15011017/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15011017/v1
AB - Metal catalysis often involves bulky molecules that cover catalyst surface areas beyond a single exposed metal atom. Common multi-site models account for adsorbate size with simple mean-field correction factors, but neglect how multi-site adsorbates become spatially correlated to avoid overlapping. Here, we combine prior theoretical constructions—the reduction of the Master equation in the fast-diffusion limit and the Widom insertion approach—to develop a footprint-aware microkinetic framework where adsorbates interact through hard exclusion. We use Monte Carlo simulations to construct surrogate models of vacant site clusters and neighboring reactant pairs needed for elementary reaction steps, which introduce missing footprint effects into conventional kinetic models. These models retain explicit kinetic and thermodynamic parameters, support standard mechanistic analyses, and can be reused across temperatures and reaction conditions without repeated configurational sampling. We illustrate the framework using unimolecular and bimolecular reactions of an adsorbate with a seven-site footprint, resembling benzene and phenol. Footprint-induced correlations have two effects relative to mean-field treatments: they (i) enrich the sites surrounding multi-site adsorbates with single-site co-adsorbates or vacancies, and (ii) aggregate empty sites into clusters that accommodate additional multi-site adsorbates. These correlations alter absolute rates, reactant pressure trends, step reversibilities, and degrees of rate control. The correlation effects are most pronounced for bimolecular reactions when surfaces are crowded by multi-site adsorbates and adsorption events at single sites or site pairs are kinetically relevant. For one bimolecular reaction, the mean-field approximation fits footprint-aware rates and elementary-step reversibility across a given range of pressures for a single reactant, but only after reducing the apparent footprint from seven to 3.3 sites and weakening the adsorption free energy by 12 RT. The approximation furthermore predicts different coreactant pressure dependences. Consequently, quantitative model agreement with kinetic trends can conceal physically inaccurate parameters and mechanistic interpretations when accounting for adsorbate size, while neglecting spatial correlations.
ER -