Dataset Open Access

Training scripts and input data sets: Transferable Interatomic Potential for Aluminum from Ambient Conditions to Warm Dense Matter

Kumar, Sandeep; Tahmasbi, Hossein; Ramakrishna, Kushal; Lokamani, Mani; Nikolov, Svetoslav; Tranchida, Julien; Wood, Mitchell A.; Cangi, Attila


JSON Export

{
  "conceptdoi": "10.14278/rodare.2368", 
  "metadata": {
    "creators": [
      {
        "name": "Kumar, Sandeep", 
        "orcid": "0000-0002-6398-0427", 
        "affiliation": "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), G\u00f6rlitz, Germany"
      }, 
      {
        "name": "Tahmasbi, Hossein", 
        "orcid": "0000-0002-3072-8217", 
        "affiliation": "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), G\u00f6rlitz, Germany"
      }, 
      {
        "name": "Ramakrishna, Kushal", 
        "orcid": "0000-0003-4211-2484", 
        "affiliation": "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), G\u00f6rlitz, Germany"
      }, 
      {
        "name": "Lokamani, Mani", 
        "orcid": "0000-0001-8679-5905", 
        "affiliation": "Center for AdHelmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany"
      }, 
      {
        "name": "Nikolov, Svetoslav", 
        "affiliation": "Computational Multiscale Department, Sandia National Laboratories, 87185 Albuquerque, NM, United States"
      }, 
      {
        "name": "Tranchida, Julien", 
        "affiliation": "CEA, DES, IRESNE, DEC, SESC, LM2C, F-13108 Saint-Paul-Lez-Durance, France"
      }, 
      {
        "name": "Wood, Mitchell A.", 
        "affiliation": "Computational Multiscale Department, Sandia National Laboratories, 87185 Albuquerque, NM, United States"
      }, 
      {
        "name": "Cangi, Attila", 
        "orcid": "0000-0001-9162-262X", 
        "affiliation": "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), G\u00f6rlitz, Germany"
      }
    ], 
    "access_right": "open", 
    "related_identifiers": [
      {
        "identifier": "https://www.hzdr.de/publications/Publ-37282", 
        "scheme": "url", 
        "relation": "isIdenticalTo"
      }, 
      {
        "identifier": "https://www.hzdr.de/publications/Publ-36890", 
        "scheme": "url", 
        "relation": "isReferencedBy"
      }, 
      {
        "identifier": "10.14278/rodare.2368", 
        "scheme": "doi", 
        "relation": "isVersionOf"
      }
    ], 
    "description": "<p>Here, we provide FitSNAP and DAKOTA input scripts and DFT-MD training data sets used for the generation of transferable SNAP ML-IAP for aluminum.</p>", 
    "license": {
      "id": "other-open"
    }, 
    "doi": "10.14278/rodare.2369", 
    "relations": {
      "version": [
        {
          "count": 1, 
          "parent": {
            "pid_type": "recid", 
            "pid_value": "2368"
          }, 
          "is_last": true, 
          "index": 0, 
          "last_child": {
            "pid_type": "recid", 
            "pid_value": "2369"
          }
        }
      ]
    }, 
    "title": "Training scripts and input data sets: Transferable Interatomic Potential for Aluminum from Ambient Conditions to Warm Dense Matter", 
    "publication_date": "2023-07-18", 
    "pub_id": "37282", 
    "resource_type": {
      "title": "Dataset", 
      "type": "dataset"
    }, 
    "access_right_category": "success", 
    "communities": [
      {
        "id": "rodare"
      }
    ], 
    "keywords": [
      "Machine Learning Potential", 
      "Warm Dense Matter"
    ], 
    "doc_id": "1"
  }, 
  "conceptrecid": "2368", 
  "revision": 5, 
  "links": {
    "badge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.2369.svg", 
    "doi": "https://doi.org/10.14278/rodare.2369", 
    "conceptbadge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.2368.svg", 
    "conceptdoi": "https://doi.org/10.14278/rodare.2368", 
    "bucket": "https://rodare.hzdr.de/api/files/907a0a20-10dd-464e-a4e3-aba99357eab7", 
    "html": "https://rodare.hzdr.de/record/2369", 
    "latest": "https://rodare.hzdr.de/api/records/2369", 
    "latest_html": "https://rodare.hzdr.de/record/2369"
  }, 
  "created": "2023-07-18T15:51:28.648840+00:00", 
  "stats": {
    "volume": 1238072000.0, 
    "unique_downloads": 22.0, 
    "version_unique_downloads": 22.0, 
    "unique_views": 147.0, 
    "downloads": 22.0, 
    "version_unique_views": 147.0, 
    "version_views": 174.0, 
    "version_downloads": 22.0, 
    "version_volume": 1238072000.0, 
    "views": 174.0
  }, 
  "doi": "10.14278/rodare.2369", 
  "updated": "2023-09-06T14:49:26.254228+00:00", 
  "owners": [
    679
  ], 
  "id": 2369, 
  "files": [
    {
      "bucket": "907a0a20-10dd-464e-a4e3-aba99357eab7", 
      "links": {
        "self": "https://rodare.hzdr.de/api/files/907a0a20-10dd-464e-a4e3-aba99357eab7/FitSNAP.tar.xz"
      }, 
      "checksum": "md5:712ff9eb621f369db248d84f34fdbfcb", 
      "key": "FitSNAP.tar.xz", 
      "size": 56276000, 
      "type": "xz"
    }
  ]
}
174
22
views
downloads
All versions This version
Views 174174
Downloads 2222
Data volume 1.2 GB1.2 GB
Unique views 147147
Unique downloads 2222

Share

Cite as