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:	Xinnan Mao, Lu Wang, Yafeng Xu, Pengju Wang, Youyong Li, Jijun Zhao
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/58c5730adde0455c8df85e821dcf5bdc
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spelling	oai:doaj.org-article:58c5730adde0455c8df85e821dcf5bdc2021-12-02T14:26:07ZComputational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution10.1038/s41524-021-00514-82057-3960https://doaj.org/article/58c5730adde0455c8df85e821dcf5bdc2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41524-021-00514-8https://doaj.org/toc/2057-3960Abstract 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.Xinnan MaoLu WangYafeng XuPengju WangYouyong LiJijun ZhaoNature PortfolioarticleMaterials of engineering and construction. Mechanics of materialsTA401-492Computer softwareQA76.75-76.765ENnpj Computational Materials, Vol 7, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
spellingShingle	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765 Xinnan Mao Lu Wang Yafeng Xu Pengju Wang Youyong Li Jijun Zhao Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution
description	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.
format	article
author	Xinnan Mao Lu Wang Yafeng Xu Pengju Wang Youyong Li Jijun Zhao
author_facet	Xinnan Mao Lu Wang Yafeng Xu Pengju Wang Youyong Li Jijun Zhao
author_sort	Xinnan Mao
title	Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution
title_short	Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution
title_full	Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution
title_fullStr	Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution
title_full_unstemmed	Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution
title_sort	computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/58c5730adde0455c8df85e821dcf5bdc
work_keys_str_mv	AT xinnanmao computationalhighthroughputscreeningofalloynanoclustersforelectrocatalytichydrogenevolution AT luwang computationalhighthroughputscreeningofalloynanoclustersforelectrocatalytichydrogenevolution AT yafengxu computationalhighthroughputscreeningofalloynanoclustersforelectrocatalytichydrogenevolution AT pengjuwang computationalhighthroughputscreeningofalloynanoclustersforelectrocatalytichydrogenevolution AT youyongli computationalhighthroughputscreeningofalloynanoclustersforelectrocatalytichydrogenevolution AT jijunzhao computationalhighthroughputscreeningofalloynanoclustersforelectrocatalytichydrogenevolution
_version_	1718391369393766400

Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution

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