Accurate water properties from an efficient ab-initio method

TL;DR

This paper presents an efficient ab-initio method based on a revised Tao-Mo functional that accurately predicts various water properties, outperforming many existing approaches in terms of consistency and reliability.

Contribution

The study introduces a revised Tao-Mo (revTM) functional that enables accurate prediction of water properties, addressing limitations of previous density functional approaches.

Findings

The revTM functional improves accuracy for water energies and structures.

The method effectively captures hydrogen bonding and conformational stability.

It outperforms several popular ab-initio methods in predicting water properties.

Abstract

Accurate prediction of the water properties from a low-cost ab-initio method still a foremost problem for chemists and physicist. Though density functional approaches starting from semilocal to hybrid functionals are tested, those are not efficiently performed for all the properties together, especially, considering energies, conformal ranking, structural and dynamics of water. Also, the inclusion of the long-range van der Waals (vdW) interaction does not improve the ordering stability of isomer. However, relying on the simple revision of the Tao-Mo (revTM) semilocal meta-generalized gradient approximations, we demonstrate that all properties of the water can be accurately predicted. A consistent improvement over several popular ab-initio methods is achieved, indicating the accuracy of this method for describing hydrogen bonding of water.