The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics.

Traditional force fields cannot model chemical reactivity, and suffer from low generality without re-fitting. Neural network potentials promise to address these problems, offering energies and forces with near accuracy at low cost. However a data-driven approach is naturally inefficient for long-range interatomic forces that have simple physical formulas.