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Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing
2021
Scientific Reports
The macroscopic properties of permanent magnets and the resultant performance required for real implementations are determined by the magnets' microscopic features. However, earlier micromagnetic simulations and experimental studies required relatively a lot of work to gain any complete and comprehensive understanding of the relationships between magnets' macroscopic properties and their microstructures. Here, by means of supervised learning, we predict reliable values of coercivity (μ0Hc) and
doi:10.1038/s41598-021-83315-9
pmid:33589666
fatcat:ct5b7nadwzhqjlmuahlegd4vmy