Sampling the materials space for conventional superconducting compounds
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"updated": "2023-10-30T14:50:42.952368+00:00",
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"contributors": [
{
"givennames": "Tiago",
"affiliations": [
"CFisUC, Department of Physics, University of Coimbra, Rua Larga, 3004-516 Coimbra, Portugal"
],
"email": "tiagoc@uc.pt",
"familyname": "F. T. Cerqueira"
},
{
"givennames": "Antonio",
"affiliations": [
"Max-Planck-Institut f\u00fcr Mikrostrukturphysik, Weinberg 2, D-06120 Halle, Germany"
],
"email": "antonio.sanna@mpi-halle.mpg.de",
"familyname": "Sanna"
},
{
"givennames": "Miguel A.",
"affiliations": [
"Research Center Future Energy Materials and Systems of the University Alliance Ruhr and Interdisciplinary Centre for Advanced Materials Simulation, Ruhr University Bochum, Universit\u00e4tsstra\u00dfe 150, D-44801 Bochum, Germany"
],
"email": "miguel.marques@rub.de",
"familyname": "L. Marques"
}
],
"title": "Sampling the materials space for conventional superconducting compounds",
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"keywords": [
"superconductivity",
"high-throughput",
"density-functional perturbation theory",
"electron-phonon coupling"
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"references": [
{
"comment": "Preprint where the data is discussed",
"doi": "10.48550/arXiv.2307.10728",
"citation": "Tiago F. T. Cerqueira, Antonio Sanna, Miguel A. L. Marques, arXiv:2307.10728 [cond-mat.supr-con]",
"url": "https://arxiv.org/abs/2307.10728",
"type": "Preprint"
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"description": "We perform a large scale study of conventional superconducting materials using a machine-learning accelerated high-throughput workflow. We start by creating a comprehensive dataset of around 7000 electron-phonon calculations performed with reasonable convergence parameters. This dataset is then used to train a robust machine learning model capable of predicting the electron-phonon and superconducting properties based on structural, compositional, and electronic ground-state properties. Using this machine, we evaluate the transition temperature (T<sub>c</sub>) of approximately 200000 metallic compounds, all of which on the convex hull of thermodynamic stability (or close to it) to maximize the probability of synthesizability. Compounds predicted to have T<sub>c</sub> values exceeding 5 K are further validated using density-functional perturbation theory. As a result, we identify 541 compounds with T<sub>c</sub> values surpassing 10 K, encompassing a variety of crystal structures and chemical compositions. This work is complemented with a detailed examination of several interesting materials, including nitrides, hydrides, and intermetallic compounds. Particularly noteworthy is LiMoN<sub>2</sub>, which we predict to be superconducting in the stoichiometric trigonal phase, with a T<sub>c</sub> exceeding 38 K. LiMoN<sub>2</sub> has been previously synthesized in this phase, further heightening its potential for practical applications.",
"status": "published",
"license": "Creative Commons Attribution 4.0 International",
"conceptrecid": "1947",
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"mcid": "2023.163",
"edited_by": 576,
"id": "1948",
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"doi": "10.24435/materialscloud:qv-bq"
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"revision": 25,
"created": "2023-10-24T07:53:39.712324+00:00"
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