Diffusion Monte Carlo evaluation of disiloxane linearization barrier

TL;DR

This paper uses diffusion Monte Carlo to accurately predict the linearization barrier of disiloxane, demonstrating its reliability over other computational methods and basis set choices.

Contribution

The study applies fixed-node diffusion Monte Carlo to evaluate the disiloxane barrier, showing its robustness compared to DFT and CCSD(T) methods across different basis sets.

Findings

FNDMC successfully predicts the disiloxane linearisation barrier.

FNDMC results are less basis set dependent than DFT or CCSD(T).

The method proves suitable for studying silicate compounds.

Abstract

The disiloxane molecule is a prime example of silicate compounds containing the Si-O-Si bridge. The molecule is of significant interest within the field of quantum chemistry, owing to the difficulty in theoretically predicting its properties. Herein, the linearisation barrier of disiloxane is investigated using a fixed-node diffusion Monte Carlo (FNDMC) approach, which is currently the most reliable {\it ab initio} method in accounting for an electronic correlation. Calculations utilizing the density functional theory (DFT) and the coupled cluster method with single and double substitutions, including noniterative triples (CCSD(T))are carried out alongside FNDMC for comparison. Two families of basis sets are used to investigate the disiloxane linearisation barrier - Dunning's correlation-consistent basis sets cc-pV$x$Z ($x = $ D, T, and Q) and their core-valence correlated counterparts, cc-pCV$x$Z. It is concluded that FNDMC successfully predicts the disiloxane linearisation barrier and does not depend on the completeness of the basis sets as much as DFT or CCSD(T), thus establishing its suitability.