<i>Ab initio</i>, artificial neural network predictions and experimental synthesis of mischmetal alloying in Sm–Co permanent magnets
Stefanos Giaremis, Georgios Katsikas, G. Sempros, M. Gjoka, C. Sarafidis, Joseph Kioseoglou
Abstract
simulations. The capability of artificial neural networks to accurately predict the relationship between structure and total magnetization from DFT calculations in the supercell approach that was employed, is also demonstrated. Experimental fabrication and structural and magnetic characterization of the proposed stoichiometry verifies the structural configuration and provides insight for the macroscopic hard magnetic properties of the material. The reduction of magnetic properties was found to be favorable compared to the respective reduction of the raw materials cost, while measurements of the Cure temperature verify that the proposed compound is still suitable for high temperature applications.