CO Coadsorption Effects on Water-Gas Shift Reaction over Cu Clusters on Cu(111): Insights from Machine Learning Force Field and Microkinetic Modeling

Key Points

• To explore the catalytic implications of CO-induced Cu clustering on the water-gas shift reaction using advanced modeling techniques.
• Utilized machine learning force field for accurate simulations
• Employed density functional theory for electronic structure calculations
• Implemented microkinetic modeling to analyze reaction kinetics
• Identified significant changes in catalytic activity due to CO coadsorption
• Demonstrated enhanced efficiency in the water-gas shift reaction with Cu clusters
• Established a framework linking machine learning with catalytic performance predictions

Abstract