Beyond activity: from machine learning screening to stability decoding on the study of self-supported metal phosphides in alkaline hydrogen evolution reaction

Abstract

With rapid consumption of fossil fuels, the development of renewable energy is urgent. The hydrogen production technology in alkaline water electrolysis has received widespread attention due to its environmental friendliness and high efficiency. Self-supported transition metal phosphides (TMPs) have shown great potential as alkaline hydrogen evolution reaction (HER) catalysts owing to their low cost, high activity, and superior stability. In addition, compared to traditional powder materials, self-supporting electrode materials could be favorable for enhancement of the conductivity, activity, and durability. Herein, the latest development of self-supported TMPs in alkaline HER was reviewed. Firstly, the application of machine learning in the screening of high-performance TMPs-based HER catalysts was highlighted. Then, the preparation methods and reaction principles for constructing self-supported TMPs on substrates were summarized. Subsequently, different modulation strategies and structure-activity relationships were emphasized to improve the performance of self-supported TMPs. Afterward, a detailed decoding of the key factors influencing the stability of TMPs in alkaline HER and the corresponding improvement strategies. Finally, a brief overview of the challenges and research directions of future exploration for self-supported TMPs in alkaline HER was given. This review is of great significance for constructing highly active self-supported TMPs hydrogen production electrodes.