Semi-Automated Creation of Density Functional Tight Binding Models Through Leveraging Chebyshev Polynomial-based Force Fields
Nir Goldman, Kyoung Eun Kweon, Babak Sadigh, Tae Wook Heo, Rebecca K., Lindsey, C. Huy Pham, Laurence E. Fried, B\'alint Aradi, Kiel Holliday, Jason, R. Jeffries, Brandon C. Wood

TL;DR
This paper introduces a semi-automated method for creating transferable Density Functional Tight Binding (DFTB) models using Chebyshev polynomial-based force fields, enabling efficient and accurate simulations across various conditions.
Contribution
The authors develop a rapid-screening workflow that leverages Chebyshev polynomial-based force fields to systematically generate and improve DFTB models for complex systems.
Findings
Model accurately predicts bulk and surface properties of TiH₂
Small training set suffices for broad thermodynamic conditions
Method is easy to implement and adaptable
Abstract
Density Functional Tight Binding (DFTB) is an attractive method for accelerated quantum simulations of condensed matter due to its enhanced computational efficiency over standard Density Functional Theory approaches. However, DFTB models can be challenging to determine for individual systems of interest, especially for metallic and interfacial systems where different bonding arrangements can lead to significant changes in electronic states. In this regard, we have created a rapid-screening approach for determining systematically improvable DFTB interaction potentials that can yield transferable models for a variety of conditions. Our method leverages a recent reactive molecular dynamics force field where many-body interactions are represented by linear combinations of Chebyshev polynomials. This allows for the efficient creation of multi-center representations with relative ease,…
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