[1E07-09] Properties of Fuel and Debris, and Fuel Fabrication Technology

3:00 PM - 3:15 PM JST(6:00 AM - 6:15 AM UTC)

[1E08] New Developments in Nuclear Fuel Research through Integration with Data Science(20)Thermophysical Properties of U2NiC3 Fabricated by Spark Plasma Sintering: Comparison with Machine Learning Predictions

*Hironobu Nakamura¹, Yifan Sun², Masaya Kumagai^2,3,4, Ken Kurosaki², Yuji Ohishi¹ (1. Osaka Univ., 2. Kyoto Univ., 3. SAKURA internet, 4. RIKEN)

Keywords:

nuclear fuel materials,machine learning,thermal conductivity,U2NiC3

Based on machine learning predictions of the thermal conductivity of uranium compounds, U₂NiC₃ was selected as a candidate material. The compound was synthesized using arc melting and spark plasma sintering to produce a nearly single-phase, high-density sample. The temperature dependence of the thermal conductivity was measured using the laser flash method and compared with the predictions by the machine learning model.