Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution
Abstract Here, we report a density functional theory (DFT)-based high-throughput screening method to successfully identify a type of alloy nanoclusters as the electrocatalyst for hydrogen evolution reaction (HER). Totally 7924 candidates of Cu-based alloy clusters of Cu55-n M n (M = Co, Ni, Ru, and...
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/58c5730adde0455c8df85e821dcf5bdc |
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| Sumario: | Abstract Here, we report a density functional theory (DFT)-based high-throughput screening method to successfully identify a type of alloy nanoclusters as the electrocatalyst for hydrogen evolution reaction (HER). Totally 7924 candidates of Cu-based alloy clusters of Cu55-n M n (M = Co, Ni, Ru, and Rh) are optimized and evaluated to screening for the promising catalysts. By comparing different structural patterns, Cu-based alloy clusters prefer the core–shell structures with the dopant metal in the core and Cu as the shell atoms. Generally speaking, the HER performance of the Cu-based nanoclusters can be significantly improved by doping transition metals, and the active sites are the bridge sites and three-fold sites on the outer-shell Cu atoms. Considering the structural stability and the electrochemical activity, core–shell CuNi alloy clusters are suggested to be the superior electrocatalyst for hydrogen evolution. A descriptor composing of surface charge is proposed to efficiently evaluate the HER activity of the alloy clusters supported by the DFT calculations and machine-learning techniques. Our screening strategy could accelerate the pace of discovery for promising HER electrocatalysts using metal alloy nanoclusters. |
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