Building a physics-aware AI ecosystem for solid-state hydrogen storage materials
Abstract
Hydrogen storage remains a central bottleneck for scalable hydrogen energy systems due to the multiscale and coupled nature of the thermodynamics, kinetics, and microstructural evolution of hydrogen storage materials (HSMs). Although artificial intelligence (AI) has accelerated materials discovery, current approaches remain constrained by fragmented data, limited physical consistency, and weak integration with experimental validation. Here, we propose a unified framework that integrates coherent data infrastructure, physics-grounded modeling, and AI-driven inverse design within a closed-loop discovery paradigm. By embedding physical constraints and experimental feedback, this approach enables adaptive, physically consistent optimization, thereby establishing a pathway toward autonomous, digital-twin-enabled discovery of HSMs.
Keywords
Cite
@article{arxiv.2605.03081,
title = {Building a physics-aware AI ecosystem for solid-state hydrogen storage materials},
author = {Seong-Hoon Jang and Yiwen Yao and Chuanyu Liu and Linda Zhang and Di Zhang and Xue Jia and Hung Ba Tran and Eric Jianfeng Cheng and Ryuhei Sato and Yusuke Ohashi and Toyoto Sato and Yusuke Hashimoto and Mark Allendorf and Nongnuch Artrith and Marcello Baricco and Andreas Borgschulte and Darren P. Broom and Ang Cao and Benjamin W. J. Chen and Lixin Chen and Ping Chen and Eun Seon Cho and Stefano Deledda and Zhao Ding and Martin Dornheim and Michael Felderhoff and Yaroslav Filinchuk and George E. Froudakis and Mingxia Gao and Thomas Gennett and Zaiping Guo and Ikutaro Hamada and Jason Hattrick-Simpers and Bjørn C. Hauback and Michael Hirscher and Torben R. Jensen and Baohua Jia and Hyoung Seop Kim and Takahiro Kondo and Kentaro Kutsukake and Xiao-Yan Li and Tongliang Liu and Piao Ma and Jianfeng Mao and Rana Mohtadi and Hyunchul Oh and Mark Paskevicius and Chris J. Pickard and Astrid Pundt and Anibal Ramirez-Cuesta and Hiroyuki Saitoh and Kaihang Shi and Aloysius Soon and Chenghua Sun and Chris Wolverton and Hiroshi Yabu and Weijie Yang and Zhenpeng Yao and Xuebin Yu and Jianxin Zou and Shouyi Hu and Panpan Zhou and Xi Lin and Zhigang Hu and Zhenhao Zhou and Pengfei Ou and Jiayu Peng and Shin-ichi Orimo and Hao Li},
journal= {arXiv preprint arXiv:2605.03081},
year = {2026}
}