Mode-Tracking Based Stationary-Point Optimization

TL;DR

This paper introduces a transition-state optimization method that efficiently finds saddle points in large molecules by calculating only specific eigenvectors, improving speed and applicability over traditional full Hessian diagonalization.

Contribution

The authors develop a Mode-Tracking based protocol that accelerates transition-state searches by focusing on targeted eigenvectors, suitable for large molecules and complex reaction pathways.

Findings

Efficient transition-state optimization for molecules with hundreds of atoms.

Applicable to cases with large structural differences from the initial guess.

Facilitates explorative reaction pathway studies through manual vector construction.

Abstract

In this work, we present a transition-state optimization protocol based on the Mode-Tracking algorithm [J. Chem. Phys. 118 (2003) 1634]. By calculating only the eigenvector of interest instead of diagonalizing the full Hessian matrix and performing an eigenvector following search based on the selectively calculated vector, we can efficiently optimize transition-state structures. The initial guess structures and eigenvectors are either chosen from a linear interpolation between the reactant and product structures, from a nudged-elastic band search, from a constrained-optimization scan, or from the minimum-energy structures. Alternatively, initial guess vectors based on chemical intuition may be defined. We then iteratively refine the selected vectors by the Davidson subspace iteration technique. This procedure accelerates finding transition states for large molecules of a few hundred atoms. It is also beneficial in cases where the starting structure is very different from the transition-state structure or where the desired vector to follow is not the one with lowest eigenvalue. Explorative studies of reaction pathways are feasible by following manually constructed molecular distortions.