Dataset Open Access
Kumar, Sandeep;
Tahmasbi, Hossein;
Ramakrishna, Kushal;
Lokamani, Mani;
Nikolov, Svetoslav;
Tranchida, Julien;
Wood, Mitchell A.;
Cangi, Attila
{
"id": 2369,
"conceptrecid": "2368",
"metadata": {
"title": "Training scripts and input data sets: Transferable Interatomic Potential for Aluminum from Ambient Conditions to Warm Dense Matter",
"doc_id": "1",
"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>",
"creators": [
{
"orcid": "0000-0002-6398-0427",
"affiliation": "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), G\u00f6rlitz, Germany",
"name": "Kumar, Sandeep"
},
{
"orcid": "0000-0002-3072-8217",
"affiliation": "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), G\u00f6rlitz, Germany",
"name": "Tahmasbi, Hossein"
},
{
"orcid": "0000-0003-4211-2484",
"affiliation": "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), G\u00f6rlitz, Germany",
"name": "Ramakrishna, Kushal"
},
{
"orcid": "0000-0001-8679-5905",
"affiliation": "Center for AdHelmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany",
"name": "Lokamani, Mani"
},
{
"affiliation": "Computational Multiscale Department, Sandia National Laboratories, 87185 Albuquerque, NM, United States",
"name": "Nikolov, Svetoslav"
},
{
"affiliation": "CEA, DES, IRESNE, DEC, SESC, LM2C, F-13108 Saint-Paul-Lez-Durance, France",
"name": "Tranchida, Julien"
},
{
"affiliation": "Computational Multiscale Department, Sandia National Laboratories, 87185 Albuquerque, NM, United States",
"name": "Wood, Mitchell A."
},
{
"orcid": "0000-0001-9162-262X",
"affiliation": "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf (HZDR), G\u00f6rlitz, Germany",
"name": "Cangi, Attila"
}
],
"communities": [
{
"id": "rodare"
}
],
"access_right_category": "success",
"doi": "10.14278/rodare.2369",
"keywords": [
"Machine Learning Potential",
"Warm Dense Matter"
],
"relations": {
"version": [
{
"count": 1,
"last_child": {
"pid_value": "2369",
"pid_type": "recid"
},
"index": 0,
"parent": {
"pid_value": "2368",
"pid_type": "recid"
},
"is_last": true
}
]
},
"license": {
"id": "other-open"
},
"pub_id": "37282",
"publication_date": "2023-07-18",
"related_identifiers": [
{
"scheme": "url",
"identifier": "https://www.hzdr.de/publications/Publ-37282",
"relation": "isIdenticalTo"
},
{
"scheme": "url",
"identifier": "https://www.hzdr.de/publications/Publ-36890",
"relation": "isReferencedBy"
},
{
"scheme": "doi",
"identifier": "10.14278/rodare.2368",
"relation": "isVersionOf"
}
],
"access_right": "open",
"resource_type": {
"title": "Dataset",
"type": "dataset"
}
},
"stats": {
"volume": 6246636000.0,
"unique_downloads": 101.0,
"version_unique_downloads": 101.0,
"unique_views": 732.0,
"downloads": 111.0,
"version_unique_views": 732.0,
"version_views": 806.0,
"version_downloads": 111.0,
"version_volume": 6246636000.0,
"views": 806.0
},
"owners": [
679
],
"doi": "10.14278/rodare.2369",
"updated": "2023-09-06T14:49:26.254228+00:00",
"created": "2023-07-18T15:51:28.648840+00:00",
"files": [
{
"checksum": "md5:712ff9eb621f369db248d84f34fdbfcb",
"key": "FitSNAP.tar.xz",
"size": 56276000,
"type": "xz",
"bucket": "907a0a20-10dd-464e-a4e3-aba99357eab7",
"links": {
"self": "https://rodare.hzdr.de/api/files/907a0a20-10dd-464e-a4e3-aba99357eab7/FitSNAP.tar.xz"
}
}
],
"revision": 5,
"conceptdoi": "10.14278/rodare.2368",
"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"
}
}
| All versions | This version | |
|---|---|---|
| Views | 806 | 806 |
| Downloads | 111 | 111 |
| Data volume | 6.2 GB | 6.2 GB |
| Unique views | 732 | 732 |
| Unique downloads | 101 | 101 |