Physics

Machine learning using structural representations for discovery of high temperature superconductors

L. Novakovic, A. Salamat, et al.

This research conducted by Lazar Novakovic, Ashkan Salamat, and Keith V Lawler delves into the innovative application of machine learning to uncover high-temperature superconductors. Utilizing advanced structural representations to navigate the vast compositional phase space, the study highlights how pressure influences polymorphisms critical to superconductivity, achieving impressive accuracy in predicting transition temperatures.