Machine Learning based BCS superconductivity Predictor from Normal State Properties

BCS theory is the widely accepted microscopic mechanism for conventional superconductivity. However, despite decades’ research effort, it is still challenging to judge that whether a material is superconducting or not, not to mention a faithful estimation on the superconducting critical temperature Tc. In this study, we employed a few deep learning architectures to correlate the normal state properties to superconductivity. A few normal state properties are found to be closely related to the formation of superconductivity with further link to Tc. Our work might offer an alternative avenue to rapidly identify superconducting materials.