High-entropy alloys for solid hydrogen storage: a review

被引：69

作者：

Luo, Long ^{[1
,2
,3
,4
]}

Chen, Liangpan ^{[4
]}

Li, Lirong ^{[5
]}

Liu, Suxia ^{[4
]}

Li, Yiming ^{[4
]}

Li, Chuanfei ^{[5
]}

Li, Linfeng ^{[5
]}

Cui, Junjie ^{[5
]}

Li, Yongzhi ^{[2
,5
]}

机构：

[1] Inner Mongolia Univ Sci & Technol, Analyt & Testing Ctr, Baotou 014010, Peoples R China

[2] Shanghai Jiao Tong Univ, Baotou Mat Res Inst, Baotou 014010, Peoples R China

[3] Northeastern Univ, Sch Mat Sci & Engn, Shenyang 110819, Peoples R China

[4] Inner Mongolia Univ Sci & Technol, Sch Mat & Met, Baotou 014010, Peoples R China

[5] Inner Mongolia Univ Sci & Technol, Sch Sci, Baotou 014010, Peoples R China

来源：

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY | 2024年 / 50卷

基金：

中国国家自然科学基金;

关键词：

Metal hydrides; Hydrogen storage; HEAs; Multiprincipal-element alloys; Microstructure; LEARNING BASED PREDICTION; RECENT PROGRESS; ENERGY-STORAGE; METAL-HYDRIDES; PHASE; MICROSTRUCTURE; EMBRITTLEMENT; RESISTANCE; SORPTION; KINETICS;

D O I：

10.1016/j.ijhydene.2023.07.146

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

The development of materials has coincided with the development of human civilization. In recent years, high-entropy alloys (HEAs) have been extensively applied to structural and functional materials owing to their unique physical and chemical properties. Therefore, HEAs have emerged as a promising materials. This review summarizes recent research progress on HEAs for hydrogen storage. First, the history and basic concepts of HEAs are systematically introduced. Furthermore, recent developments in the field of HEA-based hydrogen storage are reviewed and discussed. The preparation process, design methods, microstructures, and hydrogen-storage performance of HEAs are systematically compared and summarized. Other hydrogen-related applications are also presented. Finally, the shortcomings of the HEAs currently used in hydrogen-storage applications are highlighted, and future development directions are outlined.(c) 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

引用

页码：406 / 430

页数：25

共 167 条

[1] Predicting hydrogen storage in MOFs via machine learning [J].