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        <identifier>oai:materialscloud.org:1948</identifier>
        <datestamp>2023-10-30T15:50:42Z</datestamp>
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          <dc:contributor>F. T. Cerqueira, Tiago</dc:contributor>
          <dc:contributor>Sanna, Antonio</dc:contributor>
          <dc:contributor>L. Marques, Miguel A.</dc:contributor>
          <dc:creator>F. T. Cerqueira, Tiago</dc:creator>
          <dc:creator>Sanna, Antonio</dc:creator>
          <dc:creator>L. Marques, Miguel A.</dc:creator>
          <dc:date>2023-10-30</dc:date>
          <dc: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&amp;lt;sub&amp;gt;c&amp;lt;/sub&amp;gt;) 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&amp;lt;sub&amp;gt;c&amp;lt;/sub&amp;gt; values exceeding 5 K are further validated using density-functional perturbation theory. As a result, we identify 541 compounds with T&amp;lt;sub&amp;gt;c&amp;lt;/sub&amp;gt; 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&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;, which we predict to be superconducting in the stoichiometric trigonal phase, with a T&amp;lt;sub&amp;gt;c&amp;lt;/sub&amp;gt; exceeding 38 K. LiMoN&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; has been previously synthesized in this phase, further heightening its potential for practical applications.</dc:description>
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          <dc:identifier>https://doi.org/10.24435/materialscloud:qv-bq</dc:identifier>
          <dc:identifier>oai:materialscloud.org:1948</dc:identifier>
          <dc:identifier>mcid:2023.163</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:publisher>Materials Cloud</dc:publisher>
          <dc:relation>https://doi.org/10.48550/arXiv.2307.10728</dc:relation>
          <dc:relation>https://archive.materialscloud.org/communities/mcarchive</dc:relation>
          <dc:relation>https://doi.org/10.24435/materialscloud:sa-cy</dc:relation>
          <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
          <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
          <dc:subject>superconductivity</dc:subject>
          <dc:subject>high-throughput</dc:subject>
          <dc:subject>density-functional perturbation theory</dc:subject>
          <dc:subject>electron-phonon coupling</dc:subject>
          <dc:title>Sampling the materials space for conventional superconducting compounds</dc:title>
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