Ethylene epoxidation is industrially and commercially one of the most important selective oxidations. Silver catalysts have been state-of-the-art for decades, their efficiency steadily improving with empirical discoveries of dopants and co-catalysts. Herein, we perform a computational screening of the metals in the periodic table, identify prospective superior catalysts and experimentally demonstrate that Ag/CuPb, Ag/CuCd and Ag/CuTl outperform the pure-Ag catalysts, while they still confer an easily scalable synthesis protocol. Furthermore, we show that to harness the potential of computationally-led discovery of catalysts fully, it is essential to include the relevant in situ conditions e.g., surface oxidation, parasitic side reactions and ethylene epoxide decomposition, as neglecting such effects leads to erroneous predictions. We combine ab initio calculations, scaling relations, and rigorous reactor microkinetic modelling, which goes beyond conventional simplified steady-state or rate-determining modelling on immutable catalyst surfaces. The modelling insights have enabled us to both synthesise novel catalysts and theoretically understand experimental findings, thus, bridging the gap between first-principles simulations and industrial applications. We show that the computational catalyst design can be easily extended to include larger reaction networks and other effects, such as surface oxidations. The feasibility was confirmed by experimental agreement.
Keywords: Catalyst Screening; DFT; Ethylene Epoxidation; Experimental Validation; Modelling.
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