
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.
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