Finding new crystalline compounds using chemical similarity


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{
  "id": "840", 
  "updated": "2021-05-03T08:53:05.086787+00:00", 
  "metadata": {
    "description": "We proposed an efficient high-throughput scheme for the discovery of new stable crystalline phases. Our approach was based on the transmutation of known compounds, through the substitution of atoms in the crystal structure with chemically similar ones. The concept of similarity is defined quantitatively using a measure of chemical replaceability, extracted by data mining experimental databases. In this way we build more than 250k possible crystal phases, with almost 20k that are on the convex hull of stability. This dataset contains the optimized structure and the energy of these 250k materials calculated with the PBE approximation, in a format that is convenient for data-mining or for machine-learning applications.", 
    "contributors": [
      {
        "affiliations": [
          "Institut f\u00fcr Physik, Martin-Luther-Universit\u00e4t Halle-Wittenberg, 06120 Halle (Saale), Germany."
        ], 
        "givennames": "Hai-Chen", 
        "familyname": "Wang"
      }, 
      {
        "email": "silvana.botti@uni-jena.de", 
        "givennames": "Silvana", 
        "affiliations": [
          "Institut f\u00fcr Festk\u00f6rpertheorie und -optik and European Theoretical Spectroscopy Facility, Friedrich-Schiller-Universit\u00e4t Jena, D-07743 Jena, Germany"
        ], 
        "familyname": "Botti"
      }, 
      {
        "email": "miguel.marques@physik.uni-halle.de", 
        "givennames": "Miguel A.", 
        "affiliations": [
          "Institut f\u00fcr Physik, Martin-Luther-Universit\u00e4t Halle-Wittenberg, 06120 Halle (Saale), Germany."
        ], 
        "familyname": "L. Marques"
      }
    ], 
    "title": "Finding new crystalline compounds using chemical similarity", 
    "license_addendum": null, 
    "mcid": "2021.68", 
    "id": "840", 
    "is_last": true, 
    "_oai": {
      "id": "oai:materialscloud.org:840"
    }, 
    "publication_date": "May 03, 2021, 10:53:04", 
    "edited_by": 100, 
    "status": "published", 
    "version": 1, 
    "license": "Creative Commons Attribution 4.0 International", 
    "_files": [
      {
        "key": "README.txt", 
        "size": 1695, 
        "description": "Description of the dataset", 
        "checksum": "md5:31bd94fd2b1c30ef3cfabe24a4cf1fa0"
      }, 
      {
        "key": "step_1.json.bz2", 
        "size": 18824252, 
        "description": "Calculations of step 1", 
        "checksum": "md5:7ed24b95cc0b80305580de69611d6819"
      }, 
      {
        "key": "step_2.json.bz2", 
        "size": 16544743, 
        "description": "Calculations of step 2", 
        "checksum": "md5:e7d22945b5477bec226090cb936038dd"
      }, 
      {
        "key": "step_3.json.bz2", 
        "size": 25879044, 
        "description": "Calculations of step 3", 
        "checksum": "md5:cccc16630b7836a4d88a4f3cb38f651f"
      }, 
      {
        "key": "step_4.json.bz2", 
        "size": 12452140, 
        "description": "Calculations of step 4", 
        "checksum": "md5:083e08a8e610513b7a092b4734c7dff5"
      }, 
      {
        "key": "step_5.json.bz2", 
        "size": 5932788, 
        "description": "Calculations of step 5", 
        "checksum": "md5:d5e5717de87d5954b3d4578a6e5aaf73"
      }, 
      {
        "key": "summary.txt.bz2", 
        "size": 2868518, 
        "description": "Summary of the data", 
        "checksum": "md5:6b6ddfe2dce541758d2bcf0820fba926"
      }
    ], 
    "owner": 364, 
    "keywords": [
      "density-functional theory", 
      "high-throughput", 
      "machine learning"
    ], 
    "references": [
      {
        "type": "Journal reference", 
        "url": "https://www.nature.com/articles/s41524-020-00481-6", 
        "doi": "10.1038/s41524-020-00481-6", 
        "citation": "H.-C. Wang, S. Botti, and M.A.L. Marques, NPJ Comput. Mater. 7, 12 (2021)", 
        "comment": "Paper where the method and the data are described."
      }
    ], 
    "conceptrecid": "839", 
    "doi": "10.24435/materialscloud:96-09"
  }, 
  "revision": 3, 
  "created": "2021-05-02T11:57:17.336584+00:00"
}