9:15 AM - 9:30 AM
[22a-A302-1] ML Search for New Superconducting Materials Based on Composition Information and Tc Prediction Map
Keywords:superconductor, critical temperature, machine learning
The substance group predicted by ML and the structural database is inevitably a stable substance synthesized in the past, and its structure is limited. However, if the search range is expanded to the non-equilibrium state, there is a good possibility that the optimum combination of substances that matches the Tc prediction of ML can be found. In this research, we will give an overview of the new superconducting material search model by ML so far, and take a step forward to examine a new material search ML method that covers the non-equilibrium state.