[17p-A401-1~15] 23.1 Joint Session N "Informatics"

[17p-A401-1] Evaluation of Ionic Conductivity in LLZO using Neural Network Potential

〇Takeichiro Nishikawa¹, Takashi Yoshida¹, Hirofumi Horikawa¹, Gen Li¹, Yousuke Isowaki¹, Yasuhiro Harada¹, Yuki Nagai^2,3, Mitsuhiro Itakura² (1.Toshiba R&D Center, 2.Japan Atomic Energy Agency, 3.RIKEN)

Keywords:neural network, molecular dynamics, materials informatics

We performed machine learning molecular dynamics(MLMD) on Li7La3Zr2O12. From the visualized results, it was confirmed that Li moves in gropus, that means collective migration mechanism was reproduced. In addition, the frequency distribution of the measurement results of Li ionic conductivity near room temperature was created from academic papers, and we confirmed that the ionic conductivity obtained by executing MLMD at 300 K corresponds to the highest bin in the frequency distribution.