Materials Informatics for the Development and Discovery of Future Magnetic 
Materials

Okabe, Ryotaro; Li, Mingda; Iwasaki, Yuma; Regnault, Nicolas; Felser, Claudia; Shirai, Masafumi; Kovacs, Alexander; Schrefl, Thomas; Hirohata, Atsufumi

doi:10.1109/LMAG.2023.3320888

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Materials Informatics for the Development and Discovery of Future Magnetic Materials

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Felser, Claudia
Claudia Felser, Inorganic Chemistry, Max Planck Institute for Chemical Physics of Solids, Max Planck Society;

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Citation

Okabe, R., Li, M., Iwasaki, Y., Regnault, N., Felser, C., Shirai, M., et al. (2023). Materials Informatics for the Development and Discovery of Future Magnetic Materials. IEEE Magnetics Letters, 14: 2500305, pp. 1-5. doi:10.1109/LMAG.2023.3320888.

Cite as: https://hdl.handle.net/21.11116/0000-000D-E32F-F

Abstract

This report summarizes the recent development of magnetic materials search using artificial intelligence (AI) and machine learning (ML). The report briefly introduces ML and AI approaches to materials discovery, and the authors offer a flowchart to aid the selection of relevant approaches for their material search. The report also covers the authors' recent research activities in magnetism and quantum materials, including topological materials, Heusler alloys, interfaces and permanent magnets. This overview is based on a recent symposium at IEEE Intermag 2023. Author