| 研究実績の概要 |
Toward the goal of building query-and-learn Machine Learning framework to investigate REFe magnets, there are three objectives were achieved:
(1) develop an active learning-based framework to optimize the quantum calculation cost of querying data in materials discovery. Quantum calculations for SmFe12 with ThMn12-type magnets with various substitution elements were systematically investigated
(2) develop an evolutionary algorithm-based framework to optimize multi-objective crystal structure search. The crystal structure-stability relationship of multiple Sm-Fe families was investigated
(3) develop an Evidence-based similarity measure for materials regarding physical property. The method incorporates measurement uncertainty into the similarity measure under the Dempster-Shafer evidence theory
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