CHIPS-TB: Evaluating Tight-Binding Models For Metals, Semiconductors, and Insulators
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866915637911093248 |
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| author | Park, In Jun Choudhary, Kamal |
| author_facet | Park, In Jun Choudhary, Kamal |
| contents | As semiconductor technologies continue to scale down to the nanoscale, the efficient prediction of material properties becomes increasingly critical. The tight-binding (TB) method is a widely used semi-empirical approach that offers a computationally tractable alternative to Density Functional Theory (DFT) for large-scale electronic structure calculations. However, conventional TB models often suffer from limited transferability and lack standardized benchmarking protocols. In this study, we introduce 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. We assess model parameterizations including Density Functional Tight-Binding (DFTB)-based MatSci, PBC, PTBP, SlaKoNet and TB3PY against OptB88vdW, TBmBJ-DFT and experimental reference data from the JARVIS-DFT database for 50+ materials pertinent to semiconductor applications. The CHIPS-TB code will be made publicly available on GitHub and benchmarks will be available on JARVIS-Leaderboard. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_20740 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | CHIPS-TB: Evaluating Tight-Binding Models For Metals, Semiconductors, and Insulators Park, In Jun Choudhary, Kamal Materials Science As semiconductor technologies continue to scale down to the nanoscale, the efficient prediction of material properties becomes increasingly critical. The tight-binding (TB) method is a widely used semi-empirical approach that offers a computationally tractable alternative to Density Functional Theory (DFT) for large-scale electronic structure calculations. However, conventional TB models often suffer from limited transferability and lack standardized benchmarking protocols. In this study, we introduce 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. We assess model parameterizations including Density Functional Tight-Binding (DFTB)-based MatSci, PBC, PTBP, SlaKoNet and TB3PY against OptB88vdW, TBmBJ-DFT and experimental reference data from the JARVIS-DFT database for 50+ materials pertinent to semiconductor applications. The CHIPS-TB code will be made publicly available on GitHub and benchmarks will be available on JARVIS-Leaderboard. |
| title | CHIPS-TB: Evaluating Tight-Binding Models For Metals, Semiconductors, and Insulators |
| topic | Materials Science |
| url | https://arxiv.org/abs/2511.20740 |