日本金属学会2024年秋期(第175回)講演大会

Presentation information

公募シンポジウム講演

[S9] S9.Digital Transformation Initiative R&D for Magnetic Materials II(1)

Wed. Sep 18, 2024 1:00 PM - 4:35 PM Room B (A002 basement 1st floor Building A Center for Education in Liberal Arts and Sciences)

座長:袖山 慶太郎(NIMS)、岡本 聡(東北大学)

2:00 PM - 2:20 PM

[S9.3] Development of machine learning models for efficient exploration of functional Heusler compounds

*Enda XIAO1, Terumasa TADANO1 (1. NIMS)

Keywords:machine learning、transfer learning、crystal graph model

Models based on crystal graph show superior performance compared to those based on compositional descriptors. We demonstrate low performance due to small set can be improved via transfer learning.