Multiscale Modeling of Gas Adsorption and Surface Coverage in Thermocatalytic Systems

TL;DR

This paper presents a multiscale modeling approach combining quantum and classical DFT to accurately predict gas adsorption and surface coverage in thermocatalytic systems under industrial conditions.

Contribution

It introduces a novel integrated framework that accounts for both bond formation and gas molecule interactions, improving surface coverage predictions in catalytic reactions.

Findings

Surface composition depends on chemisorption and molecular accessibility.

The model accurately predicts surface coverage under high-pressure conditions.

The approach links gas-phase environment with surface reactions.

Abstract

Conventional methods for modeling thermocatalytic systems are typically based on the Kohn-Sham density functional theory (KS-DFT), neglecting the inhomogeneous distributions of gas molecules in the reactive environment. However, industrial reactions often take place at high temperature and pressure, where the local densities of gas molecules near the catalyst surface can reach hundreds of times their bulk values. To assess the environmental impacts on surface composition and reaction kinetics, we integrate KS-DFT calculations for predicting surface bonding energy with classical DFT to evaluate gas distribution and the grand potential of the entire reactive system. This multiscale approach accounts for both bond formation and non-bonded interactions of gas molecules with the catalyst surface and reveals that the surface composition is determined not only by chemisorption but also by the accessibility of surface sites and their interactions with the surrounding molecules in the gas phase. This theoretical procedure was employed to establish the relationship between surface coverage, gas-phase composition, and bulk phase thermodynamic conditions with thermocatalytic hydrogenation of CO2 as a benchmark. The computational framework opens new avenues for studying adsorption and coverage on catalytic surfaces under industrially relevant conditions.