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Recent achievements in developing representative micromagnetic models are to be presented. First, a TEM image-based finite element model of FePt granular media allowed us to elucidate the effect of nanodefects on magnetic properties and to realize the micromagnetic approximation of hysteresis loops assisted by machine learning [1,2]. Second, the similar TEM-based approach was used to explain the suppressed coercivity in SmFe12-based anisotropic thin films and to guide toward its remarkable enhancement [3]. Finally, the most challenging large-scale finite element model was constructed for Nd-Fe-B hot-deformed magnets based on the FIB-SEM tomographic data obtained for a real sample. With this model, we were able to reproduce the experimental coercivity and to explain its microstructural origins. Thus, the combination of advanced microstructure characterization techniques, state-of-the-art data processing algorithms including machine learning, and GPU-accelerated micromagnetic simulations can bring a new horizon in the design of high-performance magnetic materials.

権利情報:

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キーワード: Micromagnetic simulations, Nd-Fe-B magnets, FePt media, SmFe12-based films

会議: The 11th Pacific Rim International Conference on Advanced Materials and Processing (PRICM 11) (2023-11-19 - 2023-11-23)

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原稿種別: 論文以外のデータ

MDR DOI: https://doi.org/10.48505/nims.4855

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更新時刻: 2024-10-17 08:30:08 +0900

MDRでの公開時刻: 2024-10-17 08:30:09 +0900