ArticleScientific reports2025
Automated identification of the origin of energy loss in nonoriented electrical steel by feature extended Ginzburg-Landau free energy framework.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Domain-specific simulated data enhances knife-mark noise suppression in microscopy images of materials.Microscopy (Oxford, England) · 2026Article
- Explainable analysis of the complex maze magnetic domain structure through extension of the Landau free energy model by adding an entropy feature.Scientific reports · 2026Article
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Authors and funding
15 authors.
Funding
Abstract
This study presents the automated identification of the complex magnetization reversal process in nonoriented electrical steel (NOES) using the feature extended Ginzburg-Landau (eX-GL) free energy framework. eX-GL provides a robust connection between microscopic magnetic domains and macroscopic magnetic hysteresis using a data science perspective. This method employs physically meaningful features to analyze the energy landscape, providing insights into the mechanisms behind function. We obtained features representing both the microstructure and energy of the domain wall. The causes of iron loss were traced to the original domain structure, through which we could successfully distinguish and visualize the role of pinning as a promoting and resisting factor. We found that the reversal process was governed not only by general grain boundary pinning but also by segmented magnetic domains within the grain. This method revealed the complex interplay between magnetism and metallography and introduced a new means for transformative material design, bridging structures and functions.
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