Efficient correlation-corrected vibrational self-consistent field computation of OH-stretch frequencies using a low-scaling algorithm

Benoit, David M.

Abstract

The authors present a new computational scheme to perform accurate and fast direct correlation-corrected vibrational self-consistent field (CC-VSCF) computations for a selected number of vibrational modes, which is aimed at predicting a few vibrations in large molecular systems. The method is based on a systematic selection of vibrational mode-mode coupling terms, leading to the direct ab initio construction of a sparse potential energy surface. The computational scaling of the CC-VSCF computation on the generated surface is then further reduced by using a screening procedure for the correlation- correction contributions. The proposed method is applied to the computation of the OH-stretch frequency of five aliphatic alcohols. The authors investigate the influence of different pseudopotential and all-electron basis sets on the quality of the correlated potential energy surfaces computed and on the OH-stretch frequencies calculated for each surface. With the help of these test systems, the authors show that their method offers a computational scaling that is two orders of magnitude lower than a standard CC-VSCF method and that it is of equal accuracy. © 2006 American Institute of Physics.

Citation

Benoit, D. M. (2006). Efficient correlation-corrected vibrational self-consistent field computation of OH-stretch frequencies using a low-scaling algorithm. The Journal of chemical physics, 125(24), Article 244110. https://doi.org/10.1063/1.2423006

• Journal Article Type: Article
• Publication Date: Dec 1, 2006
• Deposit Date: Nov 21, 2019
• Publicly Available Date: Nov 21, 2019
• Journal: Journal of Chemical Physics
• Print ISSN: 0021-9606
• Publisher: American Institute of Physics
• Peer Reviewed: Peer Reviewed
• Volume: 125
• Issue: 24
• Article Number: 244110
• DOI: https://doi.org/10.1063/1.2423006
• Public URL: https://hull-repository.worktribe.com/output/516672
• Contract Date: Nov 21, 2019