# Functional form of the superconducting critical temperature from machine learning

@article{Xie2019FunctionalFO,
title={Functional form of the superconducting critical temperature from machine learning},
author={Stephen R. Xie and Gregory R. Stewart and James J. Hamlin and P. J. Hirschfeld and Richard G. Hennig},
journal={Physical Review B},
year={2019},
volume={100},
pages={174513}
}
Predicting the critical temperature $T_c$ of new superconductors is a notoriously difficult task, even for electron-phonon paired superconductors for which the theory is relatively well understood. Early attempts by McMillan and Allen and Dynes to improve on the weak-coupling BCS formula led to closed-form approximate relations between $T_c$ and various measures of the phonon spectrum and the electron-phonon interaction appearing in Eliashberg theory. Here we propose that these approaches can… Expand
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