Develops a machine-learned potential for magnetism in the Fe-O-H system, indicating enhanced modeling accuracy.
We develop and benchmark a general‐purpose machine‐learned interatomic potential for the Fe‐O‐H ternary system, based on the Atomic Cluster Expansion. Following our approach developed for the Fe‐O system, magnetism is explicitly treated by the model in an Ising‐like manner. This allows efficient incorporation of magnetic degrees of freedom, making the potential applicable to large‐scale atomistic calculations. We demonstrate the capability of the model to accurately describe a wide range of properties and capture basic mechanisms underlying hydrogen‐based reduction of iron oxides, interaction of water with iron and hydrogen embrittlement of metallic iron.
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Bienvenu et al. (2026) studied this question.
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