September 30, 2022 Dataset Open Access

Fiedler, Lenz; Schmerler, Steve; Modine, Normand; Vogel, Dayton J.; Popoola, Gabriel A.; Thompson, Aidan; Rajamanickam, Sivasankaran; Cangi, Attila

JSON Export

{
  "doi": "10.14278/rodare.1851", 
  "owners": [
    354
  ], 
  "files": [
    {
      "type": "zip", 
      "size": 5992336, 
      "checksum": "md5:d7e8a25ec24f5273042c1c469c7caae0", 
      "links": {
        "self": "https://rodare.hzdr.de/api/files/a7d766b9-2422-4f12-8062-91d64d6f6b97/size_transfer_cleaned.zip"
      }, 
      "key": "size_transfer_cleaned.zip", 
      "bucket": "a7d766b9-2422-4f12-8062-91d64d6f6b97"
    }
  ], 
  "stats": {
    "volume": 2810405584.0, 
    "unique_downloads": 60.0, 
    "version_unique_downloads": 60.0, 
    "unique_views": 128.0, 
    "downloads": 469.0, 
    "version_unique_views": 128.0, 
    "version_views": 579.0, 
    "version_downloads": 469.0, 
    "version_volume": 2810405584.0, 
    "views": 579.0
  }, 
  "links": {
    "badge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.1851.svg", 
    "doi": "https://doi.org/10.14278/rodare.1851", 
    "conceptbadge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.1850.svg", 
    "conceptdoi": "https://doi.org/10.14278/rodare.1850", 
    "bucket": "https://rodare.hzdr.de/api/files/a7d766b9-2422-4f12-8062-91d64d6f6b97", 
    "html": "https://rodare.hzdr.de/record/1851", 
    "latest": "https://rodare.hzdr.de/api/records/1851", 
    "latest_html": "https://rodare.hzdr.de/record/1851"
  }, 
  "id": 1851, 
  "conceptrecid": "1850", 
  "updated": "2022-11-08T08:21:35.368718+00:00", 
  "created": "2022-10-21T13:18:19.669348+00:00", 
  "metadata": {
    "creators": [
      {
        "name": "Fiedler, Lenz", 
        "affiliation": "HZDR / CASUS", 
        "orcid": "0000-0002-8311-0613"
      }, 
      {
        "name": "Schmerler, Steve", 
        "affiliation": "HZDR", 
        "orcid": "0000-0003-1354-0578"
      }, 
      {
        "name": "Modine, Normand", 
        "affiliation": "Sandia National Laboratories"
      }, 
      {
        "name": "Vogel, Dayton J.", 
        "affiliation": "Sandia National Laboratories", 
        "orcid": "0000-0003-3612-0699"
      }, 
      {
        "name": "Popoola, Gabriel A.", 
        "affiliation": "Elder Research, Inc."
      }, 
      {
        "name": "Thompson, Aidan", 
        "affiliation": "Sandia National Laboratories", 
        "orcid": "0000-0002-0324-9114"
      }, 
      {
        "name": "Rajamanickam, Sivasankaran", 
        "affiliation": "Sandia National Laboratories", 
        "orcid": "0000-0002-5854-409X"
      }, 
      {
        "name": "Cangi, Attila", 
        "affiliation": "HZDR / CASUS", 
        "orcid": "0000-0001-9162-262X"
      }
    ], 
    "communities": [
      {
        "id": "rodare"
      }
    ], 
    "publication_date": "2022-09-30", 
    "relations": {
      "version": [
        {
          "index": 0, 
          "is_last": true, 
          "count": 1, 
          "last_child": {
            "pid_value": "1851", 
            "pid_type": "recid"
          }, 
          "parent": {
            "pid_value": "1850", 
            "pid_type": "recid"
          }
        }
      ]
    }, 
    "license": {
      "id": "CC-BY-4.0"
    }, 
    "related_identifiers": [
      {
        "scheme": "url", 
        "identifier": "https://www.hzdr.de/publications/Publ-35305", 
        "relation": "isIdenticalTo"
      }, 
      {
        "scheme": "doi", 
        "identifier": "10.14278/rodare.1850", 
        "relation": "isVersionOf"
      }
    ], 
    "doi": "10.14278/rodare.1851", 
    "pub_id": "35305", 
    "doc_id": "1", 
    "version": "1.0.0", 
    "resource_type": {
      "type": "dataset", 
      "title": "Dataset"
    }, 
    "access_right_category": "success", 
    "access_right": "open", 
    "title": "Scripts and Models for \"Predicting electronic structures at any length scale with machine learning\"", 
    "description": "<pre><strong>Scripts and Models for &quot;Predicting the Electronic Structure of Matter on Ultra-Large Scales&quot;</strong>\n\nThis data set contains scripts and models to reproduce the results of our manuscript &quot;Physics-informed Machine Learning \nModels for Scalable Density Functional Theory Calculations&quot;. The scripts are supposed to be used in conjunction\nwith the ab-initio data sets also published alongside our research article. \n\n<em>Requirements</em>\n<em>\n</em>python&gt;=3.7.x\nmala&gt;=1.1.0\nase\nnumpy\n\n<em>Contents</em>\n\n| Folder name      | Description                                      |\n|------------------|--------------------------------------------------|\n| data_analysis/   | Run script for RDF calculations        |\n| model_inference/ | Run script to run inference based on MALA models |\n| model_training/  | Run script to train MALA models                  |\n| trained_models/  | Trained models for beryllium and aluminium       |\n</pre>"
  }, 
  "conceptdoi": "10.14278/rodare.1850", 
  "revision": 5
}