Approximate Reconstruction of Torsional Potential Energy Surface based on Voronoi Tessellation

TL;DR

This paper introduces a Voronoi tessellation-based method to more accurately reconstruct torsional potential energy surfaces in molecules, especially when local minima are unevenly distributed, improving upon existing periodic approximations.

Contribution

The authors propose a novel Voronoi tessellation approach to better approximate torsional potentials by incorporating local minima distribution and asymmetric barriers, enhancing accuracy over traditional methods.

Findings

Improved accuracy in potential energy surface reconstruction for complex molecules.

Effective handling of non-uniform local minima distributions.

Promising results in higher-dimensional torsional cases.

Abstract

Torsional modes within a complex molecule containing various functional groups are often strongly coupled so that the harmonic approximation and one-dimensional torsional treatment are inaccurate to evaluate their partition functions. A family of multi-structural approximation methods have been proposed and applied in recent years to deal with the torsional anharmonicity.However, these methods approximate the exact "almost periodic" potential energy as a summation of local periodic functions with symmetric barrier positions and heights. In the present theoretical study, we illustrated that the approximation is inaccurate when torsional modes present non-uniformly distributed local minima. Thereby, we proposed an improved method to reconstruct approximate potential to replace the periodic potential by using information of the local minima and their Voronoi tessellation. First, we established asymmetric barrier heights by introducing two periodicity parameters and assuming that the exact barrier positions are at the boundaries of Voronoi cells. Second, we used multiplicatively weighted Voronoi tessellation to refine the barrier heights and positions by defining a structure-related distance metric. The proposed method has been tested for a few higher-dimensional cases, all of which show promising improved accuracy.