Fast and accurate Fe–H machine-learning interatomic potential for elucidating hydrogen embrittlement mechanisms

International Journal of Hydrogen Energy 2026

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Authors: Kazuma Ito

DOI: 10.1016/j.ijhydene.2026.155600

Cited by: 3

References: 100

Fields of Study & Subjects

Hydrogen embrittlement and corrosion behaviors in metals Hydrogen Storage and Materials Machine Learning in Materials Science

References 100