Extracting local nucleation fields in permanent magnets using machine learning
Microstructural features play an important role in the quality of permanent magnets. The coercivity is greatly influenced by crystallographic defects, like twin boundaries, as is well known for MnAl-C. It would be very useful to be able to predict the macroscopic coercivity from microstructure imagi...
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Veröffentlicht in: | npj computational materials 2020-07, Vol.6 (1), Article 89 |
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Sprache: | eng |
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