Data provided by National Institute of Standards and Technology
Data types to include: formation energy, bandgaps, band offsets, work function, surface energy, defect formation energy, IV-curves, STEM images, electrical measurements, surface roughness, thermal properties, phonons
About this Dataset
Updated: 2026-09-19
Metadata Last Updated:
2025-01-14 00:00:00
Date Created:
N/A
Data Provided by:
Dataset Owner:
N/A
| Title | CHIPS-FF: Evaluating Universal Machine Learning Force Fields for Material Properties |
|---|---|
| Description | Data types to include: formation energy, bandgaps, band offsets, work function, surface energy, defect formation energy, IV-curves, STEM images, electrical measurements, surface roughness, thermal properties, phonons |
| Modified | 2025-01-14 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | Density functional theory , force-field , machine learning , semiconductors , interfaces , defects |
{
"identifier": "ark:\/88434\/mds2-3691",
"accessLevel": "public",
"contactPoint": {
"hasEmail": "mailto:[email protected]",
"fn": "Daniel Wines"
},
"programCode": [
"006:045"
],
"landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-3691",
"title": "CHIPS-FF: Evaluating Universal Machine Learning Force Fields for Material Properties",
"description": "Data types to include: formation energy, bandgaps, band offsets, work function, surface energy, defect formation energy, IV-curves, STEM images, electrical measurements, surface roughness, thermal properties, phonons",
"language": [
"en"
],
"distribution": [
{
"accessURL": "https:\/\/github.com\/usnistgov\/chipsff",
"title": "CHIPS-FF GitHub"
}
],
"bureauCode": [
"006:55"
],
"modified": "2025-01-14 00:00:00",
"publisher": {
"@type": "org:Organization",
"name": "National Institute of Standards and Technology"
},
"theme": [
"Chemistry:Theoretical chemistry and modeling",
"Materials:Modeling and computational material science",
"Physics:Atomic, molecular, and quantum",
"Physics:Condensed matter"
],
"keyword": [
"Density functional theory",
"force-field",
"machine learning",
"semiconductors",
"interfaces",
"defects"
]
}
