5 papers
Building a physics-aware AI ecosystem for solid-state hydrogen storage materials
Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu +66
Hydrogen storage remains a central bottleneck for scalable hydrogen energy systems due to the multiscale and coupled nature of the thermodynamics, kinetics, and microstructural evo…
A unified descriptor framework for hydrogen storage capacity and equilibrium pressure in interstitial hydrides
Seong-Hoon Jang, Di Zhang, Xue Jia +9
Hydrogen is a promising energy carrier, yet its practical deployment is limited by the lack of storage materials that simultaneously achieve high storage capacity () and practic…
Digital Hydrogen Platform (DigHyd): A Rigorously Curated Database for Hydrogen Storage Materials Empowered by AI-Assisted Literature Mining
Seong-Hoon Jang, Di Zhang, Xue Jia +8
Solid-state hydrogen storage materials are promising candidates for safe and compact hydrogen storage; however, data-driven discovery in this field remains limited by the availabil…
Competing Hydrogenation Pathways to Metastable CaH Revealed by Machine-Learning-Potential Molecular Dynamics
Ryuhei Sato, Peter I. C. Cooke, Maélie Caussé +8
The synthesis of the high- superhydride CaH has stimulated significant interest in understanding synthesis pathways for metastable hydrides. However, the microscopic mecha…
Physically Interpretable Descriptors Drive the Materials Design of Metal Hydrides for Hydrogen Storage
Seong-Hoon Jang, Di Zhang, Hung Ba Tran +5
Designing metal hydrides for hydrogen storage remains a longstanding challenge due to the vast compositional space and complex structure-property relationships. Herein, for the fir…