Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

1 code implementation • 27 Mar 2020 • Max Veit, David M. Wilkins, Yang Yang, Robert A. DiStasio Jr., Michele Ceriotti

In this work, we choose to represent this quantity with a physically inspired ML model that captures two distinct physical effects: local atomic polarization is captured within the symmetry-adapted Gaussian process regression (SA-GPR) framework, which assigns a (vector) dipole moment to each atom, while movement of charge across the entire molecule is captured by assigning a partial (scalar) charge to each atom.

GPR Molecular Property Prediction