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Machine learning using structural representations for discovery of high temperature superconductors
PhysicsPhysical Review B

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.... show more
Introduction
Literature Review
Methodology
Key Findings
Discussion
Conclusion
Limitations
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