Fast and accurate prediction of material properties with three-body tight-binding model for the periodic table

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, many previous models consider only simple two-body interactions, which limits accuracy. To tackle these challenges, we develop a density functional theory database of nearly 1 000 000 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 data set, iterating until predictions improve. We distribute the materials database and tools developed in this paper publicly.

Automated summary

Parametrized tight-binding models can efficiently and accurately predict properties of molecules and solids, but limited availability of well-tested parameter sets hinders routine use. To overcome this, a density functional theory database of nearly 1,000,000 materials is developed to fit a universal set of tight-binding parameters for 65 elements and their binary combinations, including two-body and three-body effective interaction terms. The model allows for metallic, covalent, and ionic bonds with the same parameter set and is continuously improved using a learning framework.