Abstract
Selective ethane dehydrogenation (EDH) is an attractive on-purpose strategy for industrial ethylene production. Design of an effective, stable, and earth-abundant catalyst to replace noble metal Pt is the main obstacle for its large-scale application. Herein, we report an experimentally validated theoretical framework to discover promising catalysts for EDH, which combines descriptor-based microkinetic modeling, high-throughput computations, machine-learning concepts, and experiments. Our approach efficiently evaluates 1,998 bimetallic alloys by using accurately calculated C and CH3 adsorption energies and identifies a small number of new promising noble-metal-free catalysts for selective EDH. A Ni3Mo alloy predicted to be promising is successfully synthesized, and experimentally proven to outperform Pt in selective ethylene production from EDH, representing an important contribution to the improvement of light alkane dehydrogenation to olefins. These results will provide essential additions in the discovery and application of earth-abundant materials in catalysis.
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