Artificial Intelligence‐Driven Innovations in Hydrogen Storage Technology

In the global transition towards sustainable energy sources, hydrogen energy has emerged as an indispensable pillar in reshaping the energy landscape, owing to its environmental sustainability, zero emissions, and high efficiency. Nevertheless, the large‐scale deployment of hydrogen energy is confronted with substantial technical barriers in storage and transportation. Although contemporary research has shifted focus to the development of highly efficient hydrogen storage materials, conventional material design concepts remain predominantly empirical, typically relying on trial‐and‐error methodologies. Importantly, the widespread application of artificial intelligence technologies in accelerating materials discovery and optimization has attracted considerable attention. This review provides a comprehensive overview of the latest advancements in hydrogen storage technologies, with an emphasis on the synergistic application of high‐throughput screening and machine learning in solid‐state hydrogen storage materials. These approaches demonstrate exceptional potential in accurately predicting hydrogen storage properties, optimizing material performance, and accelerating the development of innovative hydrogen storage materials. Specifically, we discuss in detail the essential role of artificial intelligence in developing hydrogen storage materials such as metal hydrides, alloys, carbon materials, metal–organic frameworks, and zeolites. Moreover, underground hydrogen storage is further explored as a scalable renewable energy storage solution, particularly in terms of optimizing storage parameters and performance prediction. By systematically analyzing the limitations of existing hydrogen storage approaches and the transformative potential of artificial intelligence‐driven methods, this review offers insights into the discovery and optimization of high‐performance hydrogen storage materials, contributing to sustainable global energy development and technological innovation.

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Institutions

Publication Details

Journal
Energy & environment materials
Published
2025-05-29
DOI
https://doi.org/10.1002/eem2.70041
Citations
13
Primary Topic
Hydrogen Storage and Materials
Type
article
Field-Weighted Citation Impact
6.73

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article

Artificial Intelligence‐Driven Innovations in Hydrogen Storage Technology

Yusong Ding, Yan Zhao, Ling Tong, Ying Liu et al.
13 citations
Energy & environment materials
Hydrogen Storage and Materials
6.73
article

Artificial Intelligence‐Driven Innovations in Hydrogen Storage Technology

Yusong Ding, Yan Zhao, Ling Tong, Ying Liu, Xiaolin Liu
article en
13 citations

Abstract

In the global transition towards sustainable energy sources, hydrogen energy has emerged as an indispensable pillar in reshaping the energy landscape, owing to its environmental sustainability, zero emissions, and high efficiency. Nevertheless, the large‐scale deployment of hydrogen energy is confronted with substantial technical barriers in storage and transportation. Although contemporary research has shifted focus to the development of highly efficient hydrogen storage materials, conventional material design concepts remain predominantly empirical, typically relying on trial‐and‐error methodologies. Importantly, the widespread application of artificial intelligence technologies in accelerating materials discovery and optimization has attracted considerable attention. This review provides a comprehensive overview of the latest advancements in hydrogen storage technologies, with an emphasis on the synergistic application of high‐throughput screening and machine learning in solid‐state hydrogen storage materials. These approaches demonstrate exceptional potential in accurately predicting hydrogen storage properties, optimizing material performance, and accelerating the development of innovative hydrogen storage materials. Specifically, we discuss in detail the essential role of artificial intelligence in developing hydrogen storage materials such as metal hydrides, alloys, carbon materials, metal–organic frameworks, and zeolites. Moreover, underground hydrogen storage is further explored as a scalable renewable energy storage solution, particularly in terms of optimizing storage parameters and performance prediction. By systematically analyzing the limitations of existing hydrogen storage approaches and the transformative potential of artificial intelligence‐driven methods, this review offers insights into the discovery and optimization of high‐performance hydrogen storage materials, contributing to sustainable global energy development and technological innovation.

Energy & environment materialsVol. 8(5)
Sichuan University (CN), Wuhan University (CN)
National Natural Science Foundation of China, Natural Science Foundation for Young Scientists of Shanxi Province
Openalex Percentile: Top 3%
Hydrogen Storage and Materials
6.73
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