{"@type": "dcat:Dataset", "accessLevel": "public", "accrualPeriodicity": "irregular", "bureauCode": ["006:55"], "contactPoint": {"fn": "In Jun Park", "hasEmail": "mailto:injun.park@nist.gov"}, "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.", "distribution": [{"accessURL": "https://github.com/usnistgov/chipstb", "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.", "format": "Python source code", "title": "CHIPS-TB"}], "identifier": "ark:/88434/mds2-4073", "issued": "2026-04-15", "keyword": ["Benchmarking", "Semiconductor", "Tight-binding model"], "landingPage": "https://data.nist.gov/od/id/mds2-4073", "language": ["en"], "license": "https://www.nist.gov/open/license", "modified": "2025-12-01 00:00:00", "programCode": ["006:045"], "publisher": {"@type": "org:Organization", "name": "National Institute of Standards and Technology"}, "references": ["https://doi.org/10.1021/acs.jpcc.5c08042"], "theme": ["Materials:Modeling and computational material science"], "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."}