[G] 水素・電池関連材料(2)

11:40 〜 11:55

[93] Machine learning and density functional theory for determining formation enthalpy of high-entropy hydrides

○Shivam Dangwal^1,2, Pranav Kumar³, Yuji Ikeda³, Blazej Grabowski³, Kaveh Edalati^1,2 (1. WPI-I2CNER, Kyushu University, Fukuoka, Japan, 2. The Department of Automotive Science, Kyushu University, Fukuoka, Japan, 3. Institute for Materials Science, University of Stuttgart, Stuttgart, Germany)

キーワード：

Solid-state hydrogen storage、Multi-principal element alloys (MPEAs)、Ab initio calculations、Artificial intelligence、High-entropy alloys

This study focuses on determining the formation enthalpy of high-entropy alloys using machine learning with validation from density functional theory and experiments.