[G] 相安定性・相変態

12:45 〜 13:00

[435] Accelerated Development of Thermodynamic Database using Machine Learning Potential

*Arkapol Saengdeejing¹, Ryoji Sahara¹, Hiori Kino^1,2, Toyohiro Chikyow¹ (1. NIMS、2. ISM)

キーワード：

CALPHAD、Machine learning potential、Phase diagram

Developing CALPHAD-type themodynamic database using the data from machine learning potential. Compared with DFT, the computational resources are significantly lower.