Enhancing the Accuracy of Density Functional Tight Binding Models Through ChIMES Many-body Interaction Potentials

TL;DR

This paper introduces a method combining DFTB with ChIMES many-body potentials to rapidly develop accurate, transferable semi-empirical models for various materials, significantly reducing computational costs while maintaining high accuracy.

Contribution

The authors present a systematic approach using ChIMES to enhance DFTB models with many-body interactions, improving transferability and accuracy across different materials.

Findings

DFTB/ChIMES models achieve accuracy comparable to hybrid functionals and coupled cluster methods.

The approach reduces the number of parameters needed by two orders of magnitude compared to neural network models.

Models demonstrate strong transferability and computational efficiency across diverse thermodynamic conditions.

Abstract

Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. Our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.