Fast and Accurate Prediction of Material Properties with Three-Body Tight-Binding Model for the Periodic Table

Published

April 14, 2023

Author(s)

Kevin Garrity, Kamal Choudhary

Abstract

Parametrized tight-binding models fit to first principles calculations can provide an efficient and accurate quantum mechanical method for predicting properties of molecules and solids. However, well-tested parameter sets are generally only available for a limited number of atom combinations, making routine use of this method difficult. Furthermore, most previous models consider only simple two-body interactions, which limits accuracy. To tackle these challenges, we develop a density functional theory database of nearly one million materials, which we use to fit a universal set of tight-binding parameters for 65 elements and their binary combinations. We include both two-body and three-body effective interaction terms in our model, plus self-consistent charge transfer, enabling our model to work for metallic, covalent, and ionic bonds with the same parameter set. To ensure predictive power, we adopt a learning framework where we repeatedly test the model on new low energy crystal structures and then add them to the fitting dataset, iterating until predictions improve. We distribute the materials database and tools developed in this work publicly.

Citation

Physical Review Materials

Volume

7

Issue

4

Pub Type

Journals

Download Paper

https://doi.org/10.1103/PhysRevMaterials.7.044603

Local Download

Keywords

tight-binding, density functional theory, materials genome

Citation

Garrity, K. and Choudhary, K. (2023), Fast and Accurate Prediction of Material Properties with Three-Body Tight-Binding Model for the Periodic Table, Physical Review Materials, [online], https://doi.org/10.1103/PhysRevMaterials.7.044603, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933815 (Accessed April 27, 2024)