  Parameterized 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.
