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Computational infrared and Raman spectra by hybrid QM/MM techniques: a study on molecular and catalytic material systems

Guan, Jingcheng, Lu, You, Sen, Kakali, Abdul Nasir, Jamal, Desmoutier, Alec W., Hou, Qing, Zhang, Xingfan, Logsdail, Andrew J. ORCID:, Dutta, Gargi, Beale, Andrew M., Strange, Richard W., Yong, Chin, Sherwood, Paul, Senn, Hans M., Catlow, C. richard A. ORCID:, Keal, Thomas W. and Sokol, Alexey A. 2023. Computational infrared and Raman spectra by hybrid QM/MM techniques: a study on molecular and catalytic material systems. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 381 (2250) , 20220234. 10.1098/rsta.2022.0234

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Vibrational spectroscopy is one of the most well-established and important techniques for characterizing chemical systems. To aid the interpretation of experimental infrared and Raman spectra, we report on recent theoretical developments in the ChemShell computational chemistry environment for modelling vibrational signatures. The hybrid quantum mechanical and molecular mechanical approach is employed, using density functional theory for the electronic structure calculations and classical forcefields for the environment. Computational vibrational intensities at chemical active sites are reported using electrostatic and fully polarizable embedding environments to achieve more realistic vibrational signatures for materials and molecular systems, including solvated molecules, proteins, zeolites and metal oxide surfaces, providing useful insight into the effect of the chemical environment on the signatures obtained from experiment. This work has been enabled by the efficient task-farming parallelism implemented in ChemShell for high-performance computing platforms. This article is part of a discussion meeting issue ‘Supercomputing simulations of advanced materials’.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Cardiff Catalysis Institute (CCI)
Additional Information: License information from Publisher: LICENSE 1: URL:, Type: open-access
Publisher: The Royal Society
ISSN: 1364-503X
Date of First Compliant Deposit: 22 May 2023
Date of Acceptance: 4 April 2023
Last Modified: 18 Jun 2023 08:29

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