Nudged elastic band calculations accelerated with Gaussian process regression based on inverse interatomic distances

Abstract

Calculations of minimum energy paths for atomic rearrangements using the nudged elastic band method can be accelerated with Gaussian process regression to reduce the number of energy and atomic force evaluations needed for convergence. Problems can arise, however, when configurations with large forces due to short distance between atoms are included in the data set. Here, a significant improvement to the Gaussian process regression approach is obtained by basing the difference measure between two atomic configurations in the covariance function on the inverted inter-atomic distances and by adding a new early stopping criterion for the path relaxation phase. This greatly improves the performance of the method in two applications where the original formulation does not work well: a dissociative adsorption of an H2 molecule on a Cu(110) surface and a diffusion hop of an H2O molecule on an ice Ih(0001) surface. Also, the revised method works better in the previously analyzed benchmark application to rearrangement transitions of a heptamer island on a surface, requiring fewer energy and force evaluations for convergence to the minimum energy path.