[17p-P04-1~10] 23 Joint Session N "Informatics" (Poster)

[17p-P04-7] Exploring catalysts for ammonia synthesis using databases and machine learning models

〇(M1)Takuya Horita¹, Ryoji Asahi¹ (1.Nagoya Univ.)

Keywords:

catalysts for ammonia synthesis,machine learning,first-principles calculations

Ammonia is a useful chemical for fertilizer. However, the conventional ammonia synthesis process emits high CO2 emissions, so new catalytic materials have been explored to realize ammonia synthesis under mild conditions. We performed screening on the material database using a machine learning model to obtain materials that could exhibit high catalytic activity. We also performed first-principles calculations on the obtained materials to confirm validity of the calculation results of the machine learning models and to examine the detailed reaction path.