High-entropy catalysts for electrochemical water-electrolysis of hydrogen evolution and oxygen evolution reactions

Abstract

High entropy materials (HEMs) have developed rapidly in the field of electrocatalytic water-electrolysis for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) due to their unique properties. In particular, HEM catalysts are composed of many elements. Therefore, they have rich active sites and enhanced entropy stability relative to single atoms. In this paper, the preparation strategies and applications of HEM catalysts in electrochemical water-electrolysis are reviewed to explore the stabilization of HEMs and their catalytic mechanisms as well as their application in support green hydrogen production. First, the concept and four characteristics of HEMs are introduced based on entropy and composition. Then, synthetic strategies of HEM catalysts are systematically reviewed in terms of the categories of bottom-up and top-down. The application of HEMs as catalysts for electrochemical water-electrolysis in recent years is emphatically discussed, and the mechanisms of improving the performance of electrocatalysis is expounded by combining theoretical calculation technology and ex-situ/in situ characterization experiments. Finally, the application prospect of HEMs is proposed to conquer the challenges in HEM catalyst fabrications and applications.

Key words： high-entropy; electrocatalysis; synthetic methods; water-electrolysis; hydrogen and oxygen evolutions

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (Grant No. 51572166), the Program for Eastern Scholar (Grant No. TP2014041), and the China Postdoctoral Science Foundation (Grant No. 2021M702073).

Competing interests

Jiujun Zhang is a duputy editor-in-chief of Frontiers in Energy, who was excluded from the peer-review process and all editorial decisions related to the acceptance and publication of this article. Peer-review was handled independently by the other editors to minimise bias.

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