Some improvements of the ART method for finding transition pathways on potential energy surfaces

TL;DR

This paper introduces an improved version of the ARTn method that enhances efficiency and robustness in finding transition pathways on potential energy surfaces, with validation on iron defect simulations.

Contribution

A novel variation of the ARTn method is proposed, demonstrating improved local convergence and robustness for transition pathway searches.

Findings

The new algorithm converges reliably near saddle points.

Efficiency is improved compared to the original ARTn method.

Validated on defect transitions in bcc iron.

Abstract

The Activation-Relaxation Technique nouveau (ARTn) is an eigenvector following method for systematic search of saddle points and transition pathways on a given potential energy surface. We propose a variation of this method aiming at improving the efficiency of the local convergence close to the saddle point. We prove the convergence and robustness of this new algorithm. The efficiency of the method is tested in the case of point defects in body centered cubic iron.