Quantifying the impact of vibrational nonequilibrium in plasma catalysis: Insights from a molecular dynamics model of dissociative chemisorption
Kristof M. Bal, Erik C. Neyts

TL;DR
This study uses molecular dynamics and machine learning to quantify how vibrational nonequilibrium influences dissociative chemisorption on nickel catalysts, revealing mode-specific effects and surface structure dependencies.
Contribution
It introduces a coupled modeling approach combining plasma-induced vibrational nonequilibrium with molecular dynamics and machine learning to analyze catalytic dissociation.
Findings
High vibrational efficacy at low temperatures.
Bend vibrations dominate methane dissociation.
Surface structure significantly affects vibrational impact.
Abstract
The rate, selectivity and efficiency of plasma-based conversion processes is strongly affected by nonequilibrium phenomena. High concentrations of vibrationally excited molecules are such a plasma-induced effect. It is frequently assumed that vibrationally excited molecules are important in plasma catalysis because their presence lowers the apparent activation energy of dissociative chemisorption reactions and thus increases the conversion rate. A detailed atomic-level understanding of vibrationally stimulated catalytic reactions in the context of plasma catalysis is however lacking. Here, we couple a recently developed statistical model of a plasma-induced vibrational nonequilibrium to molecular dynamics simulations, enhanced sampling methods, and machine learning techniques. We quantify the impact of a vibrational nonequilibrium on the dissociative chemisorption barrier of H2 and CH4…
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