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        <datestamp>2026-09-14T09:33:42Z</datestamp>
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          <dc:title>Matbench Discovery - Data Files</dc:title>
          <dc:creator>Janosh Riebesell (13245669)</dc:creator>
          <dc:subject>Inorganic materials (incl. nanomaterials)</dc:subject>
          <dc:subject>Structure and dynamics of materials</dc:subject>
          <dc:subject>Cheminformatics and quantitative structure-activity relationships</dc:subject>
          <dc:subject>materials discovery</dc:subject>
          <dc:subject>inorganic crystal stability</dc:subject>
          <dc:subject>machine learning</dc:subject>
          <dc:subject>interatomic potential</dc:subject>
          <dc:subject>Bayesian optimization</dc:subject>
          <dc:subject>high-throughput search</dc:subject>
          <dc:subject>convex hull</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;These are the v1 data files for Matbench Discovery, a benchmark for machine learning energy models on inorganic crystal stability prediction from unrelaxed structures. It contains relaxed structures of the MP training set, initial+relaxed structures of the WBM test set, plus several checkpoints for models trained on this data specifically for this benchmark.&lt;/p&gt;&lt;p dir="ltr"&gt;For a description of each file, see https://matbench-discovery.materialsproject.org/data#--direct-download.&lt;/p&gt;&lt;p dir="ltr"&gt;The full MPtrj training set containing 1.3M structures along with their energies, forces, stresses and magmons is available at &lt;a href="https://figshare.com/articles/dataset/23713842" target="_blank"&gt;https://figshare.com/articles/dataset/23713842.&lt;/a&gt;&lt;/p&gt;</dc:description>
          <dc:date>2023-04-28T03:25:33Z</dc:date>
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          <dc:identifier>10.6084/m9.figshare.22715158.v38</dc:identifier>
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