Computationally-driven study of silver-based catalysts for ethylene epoxidation

Silver-catalyzed ethylene epoxidation is the primary industrial route for producing ethylene oxide, yet balancing its activity and selectivity remains a classic challenge in the field. This review systematically summarizes recent progress in this reaction, adopting an atomic-scale perspective that integrates the latest findings from theoretical calculations and experimental characterizations. It critically analyzes the dynamic evolution and structure-activity relationships of various active oxygen species on the silver surface. Building on this, the core strategies for enhancing catalyst performance are outlined, including the tuning of Ag particle morphology and size, promoters, supports, and the reaction environment. Special emphasis is placed on how emerging computational methods, particularly machine learning, offer revolutionary tools for revealing real catalytic interfaces and exploring reaction networks. Finally, by discussing current challenges and future trends, this review aims to provide a comprehensive theoretical reference and forward-looking guidance for the understanding and rational design of higher-performance ethylene epoxidation catalysts.