Development and Applications of a Magnetism‐Aware General‐Purpose Atomic Cluster Expansion Potential for the Fe‐O‐H Ternary System
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.
Authors
- Mira Todorova (ORCID: https://orcid.org/0000-0002-8053-9350)
- Jörg Neugebauer (ORCID: https://orcid.org/0000-0002-7903-2472)
- Ralf Drautz (ORCID: https://orcid.org/0000-0001-7101-8804)
- Matous Mrovec (ORCID: https://orcid.org/0000-0001-8216-2254)
- Baptiste Bienvenu (ORCID: https://orcid.org/0000-0002-7906-8838)
- Dierk Raabe
Institutions
- Max-Planck-Institut für Nachhaltige Materialien (DE)
- Ruhr University Bochum (DE)
Publication Details
- Journal
- Advanced Science
- Published
- 2026-07-27
- DOI
- https://doi.org/10.1002/advs.76709
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Alexander von Humboldt-Stiftung
- European Commission
- Deutsche Forschungsgemeinschaft