[23p-D215-1~16] 11.1 Fundamental properties

[23p-D215-2] New superconductor search by crystal structure database and machine learning

〇Kaname Matsumoto¹, Akihisa Tokunaga¹, Tomoya Horide¹ (1.Kyutech)

Keywords:superconductor, critical temperature, machine learning

There is an increasing momentum to search for new high-temperature superconducting materials that exceed the Tc of cuprate superconductors under normal pressure. Such high-Tc superconducting materials may exist in previously unexplored multidimensional materials, unknown natural superlattices, and designed artificial superlattices. The "new substance search space" is extremely vast. To tackle this problem, we have developed a machine learning superconducting Tc prediction method based on a superconducting database. This time, assuming a "multidimensional material search space", we applied our machine learning Tc prediction technology to find candidate materials for the material group in the open crystal structure database.