CHIPS-TB: Evaluating Tight-Binding Models for Metals, Semiconductors, and Insulators

Published

February 4, 2026

Author(s)

In Jun Park, Kamal Choudhary

Abstract

As semiconductor technologies continue to scale to the nanoscale, the efficient prediction of material properties becomes increasingly critical. The tight-binding (TB) method is a widely used semiempirical 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 parametrizations across diverse material systems relevant to semiconductor design, focusing on properties such as electronic bandgaps, band structures, and bulk modulus. We assess model parametrizations 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.

Citation

Journal of Physical Chemistry C

Volume

130

Issue

7

Pub Type

Journals

Download Paper

https://doi.org/10.1021/acs.jpcc.5c08042

Local Download

Keywords

Tight-binding model, Benchmarking, Semiconductor

Citation

Park, I. and Choudhary, K. (2026), CHIPS-TB: Evaluating Tight-Binding Models for Metals, Semiconductors, and Insulators, Journal of Physical Chemistry C, [online], https://doi.org/10.1021/acs.jpcc.5c08042, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=960265 (Accessed March 11, 2026)