Quantification of the Coercivity Factor in Soft Magnetic Materials at Different Frequencies Using Topological Data Analysis

被引:0
|
作者
Nagaoka, Ryunosuke [1 ]
Masuzawa, Ken [1 ]
Taniwaki, Michiki [1 ]
Foggiatto, Alexandre Lira [1 ]
Yamazaki, Takahiro [1 ]
Obayashi, Ippei [2 ]
Hiraoka, Yasuaki [3 ]
Mitsumata, Chiharu [1 ]
Kotsugi, Masato [1 ]
机构
[1] Tokyo Univ Sci, Dept Mat Sci & Technol, Tokyo 1258585, Japan
[2] Okayama Univ, Ctr Artificial Intelligence & Math Data Sci, Okayama 7008530, Japan
[3] Kyoto Univ, Inst Adv Study, Kyoto 6068501, Japan
基金
日本学术振兴会;
关键词
Coercivity; iron loss; machine learning; magnetic domain; magnetic-optical Kerr effect (MOKE);
D O I
10.1109/TMAG.2024.3408002
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The kinetics of magnetic domain structure in soft magnetic materials is crucial for the understanding of their functional properties, such as coercivity and loss. We have developed a high-speed and real-time magnetic domain measurement system based on the magnetic-optical Kerr effect (MOKE) microscope. High-speed evolution of domain structures of yttrium iron garnet (YIG) thin film under ac magnetic field and its frequency-dependent hysteresis curves were measured by the system. Subsequently, we combined persistent homology (PH) with principal component analysis (PCA), a dimensionality reduction method, to extract topological information on domain structure and analyze the complex magnetization process. We successfully extracted physically meaningful features of the frequency-dependent magnetic domain structures. As a result, using the machine-learning outputted features, the coercivity contributing factors of the magnetization reversal process were visualized onto domain structures. We also found that the occurrence of the coercivity factors increases along excitation magnetic field frequency, indicating the increase of loss. These findings provide new insight into the relationship between coercivity and magnetic domain structure dynamics.
引用
收藏
页码:1 / 1
页数:5
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