Data provided by National Institute of Standards and Technology
The chipstb repository is a Python-based automation suite designed to systematically benchmark tight-binding electronic structure models (such as DFTB, TB3PY, and SlaKoNet) against high-accuracy Density Functional Theory (DFT) and experimental reference data. Built upon the JARVIS-Tools infrastructure, the code manages the complete workflow of retrieving crystal structures, executing semi-empirical calculations, and computing statistical error metrics for key properties like bandgaps and bulk moduli.
About this Dataset
Updated: 2026-09-04
Metadata Last Updated:
2025-12-01 00:00:00
Date Created:
N/A
Data Provided by:
Dataset Owner:
N/A
| Title | A computational framework (CHIPS-TB) for evaluating and comparing tight-binding parameterizations across diverse material systems relevant to semiconductor design, focusing on properties such as electronic bandgaps, band structures, and bulk modulus. |
|---|---|
| Description | The chipstb repository is a Python-based automation suite designed to systematically benchmark tight-binding electronic structure models (such as DFTB, TB3PY, and SlaKoNet) against high-accuracy Density Functional Theory (DFT) and experimental reference data. Built upon the JARVIS-Tools infrastructure, the code manages the complete workflow of retrieving crystal structures, executing semi-empirical calculations, and computing statistical error metrics for key properties like bandgaps and bulk moduli. |
| Modified | 2025-12-01 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | Tight-binding model , Benchmarking , Semiconductor |
{
"identifier": "ark:\/88434\/mds2-4073",
"accessLevel": "public",
"contactPoint": {
"hasEmail": "mailto:[email protected]",
"fn": "In Jun Park"
},
"programCode": [
"006:045"
],
"landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-4073",
"title": "A computational framework (CHIPS-TB) for evaluating and comparing tight-binding parameterizations across diverse material systems relevant to semiconductor design, focusing on properties such as electronic bandgaps, band structures, and bulk modulus.",
"description": "The chipstb repository is a Python-based automation suite designed to systematically benchmark tight-binding electronic structure models (such as DFTB, TB3PY, and SlaKoNet) against high-accuracy Density Functional Theory (DFT) and experimental reference data. Built upon the JARVIS-Tools infrastructure, the code manages the complete workflow of retrieving crystal structures, executing semi-empirical calculations, and computing statistical error metrics for key properties like bandgaps and bulk moduli.",
"language": [
"en"
],
"distribution": [
{
"accessURL": "https:\/\/github.com\/usnistgov\/chipstb",
"format": "Python source code",
"description": "A computational framework (CHIPS-TB) for evaluating and comparing tight-binding parameterizations across diverse material systems relevant to semiconductor design, focusing on properties such as electronic bandgaps, band structures, and bulk modulus.",
"title": "CHIPS-TB"
}
],
"bureauCode": [
"006:55"
],
"modified": "2025-12-01 00:00:00",
"publisher": {
"@type": "org:Organization",
"name": "National Institute of Standards and Technology"
},
"theme": [
"Materials:Modeling and computational material science"
],
"keyword": [
"Tight-binding model",
"Benchmarking",
"Semiconductor"
]
}
