Dataset Open Access
Tahmasbi, Hossein;
Knüpfer, Andreas;
Kühne, Thomas Dae-Song;
Mir Hosseini, Seyed Hossein
{
"abstract": "<p>Reference data and scripts generated for\u00a0the \"Benchmarking Universal Machine Learning Interatomic<br>\r\nPotentials on Elemental Systems\" manuscript.</p>",
"author": [
{
"family": "Tahmasbi, Hossein"
},
{
"family": "Kn\u00fcpfer, Andreas"
},
{
"family": "K\u00fchne, Thomas Dae-Song"
},
{
"family": "Mir Hosseini, Seyed Hossein"
}
],
"type": "dataset",
"issued": {
"date-parts": [
[
2026,
4,
9
]
]
},
"DOI": "10.14278/rodare.4596",
"publisher": "Rodare",
"title": "Data publication: Benchmarking Universal Machine Learning Interatomic Potentials on Elemental Systems",
"id": "4596"
}
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| Data volume | 303.5 MB | 303.5 MB |
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| Unique downloads | 18 | 18 |