Identification of superconductivity mechanisms and prediction of new materials using Density Functional Theory (DFT) calculations

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Abstract

Superconductivity at room temperature or higher is considered a fundamentally viable goal, which may bring significant benefits to society, if achieved. However, methods to predict and design new superconductors remain largely empirical, without extensive guidance from computational quantum chemistry techniques, such as Density Functional Theory (DFT). This paper presents our progress, using DFT, towards a predictive tool for superconductivity from knowledge of the crystal structure. Excellent correlations between predicted and experimentally determined values have been demonstrated for MgB 2 under a wide range of external conditions, including isotopic forms, metal substitutions, pressure and temperature effects. Model ideas have recently been shown to work equally well for hydrogen sulphide (H 3 S), which is the current record holder for the highest T c (at 200K), albeit requiring very high pressures (∼160 GPa). Consistent patterns across families of superconductors, as determined from DFT calculations, are emerging that suggest a method to predict T c seems possible.

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Alarco, J. A., Talbot, P. C., & Mackinnon, I. D. R. (2018). Identification of superconductivity mechanisms and prediction of new materials using Density Functional Theory (DFT) calculations. In Journal of Physics: Conference Series (Vol. 1143). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/1143/1/012028

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