Efficient simulation of resonance Raman spectra with tight-binding approximations to density functional theory

Sahar Ashtari-Jafari, Zahra Jamshidi, Lucas Visscher*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Resonance Raman spectroscopy has long been established as one of the most sensitive techniques for detection, structure characterization, and probing the excited-state dynamics of biochemical systems. However, the analysis of resonance Raman spectra is much facilitated when measurements are accompanied by Density Functional Theory (DFT) calculations that are expensive for large biomolecules. In this work, resonance Raman spectra are therefore computed with the Density Functional Tight-Binding (DFTB) method in the time-dependent excited-state gradient approximation. To test the accuracy of the tight-binding approximations, this method is first applied to typical resonance Raman benchmark molecules, such as β-carotene, and compared to results obtained with pure and range-separated exchange-correlation functionals. We then demonstrate the efficiency of the approach by considering a computationally challenging heme variation. Overall, we find that the vibrational frequencies and excited-state properties (energies and gradients) that are needed to simulate the spectra are reasonably accurate and suitable for interpretation of experiments. We can therefore recommend DFTB as a fast computational method to interpret resonance Raman spectra.

Original languageEnglish
Article number0107220
Pages (from-to)1-9
Number of pages9
JournalJournal of Chemical Physics
Volume157
Issue number8
Early online date22 Aug 2022
DOIs
Publication statusPublished - 28 Aug 2022

Bibliographical note

Funding Information:
We acknowledge the developer group of Software for Chemistry and Materials (SCM) and computing resources of the Vrije Universiteit Amsterdam. Z.J. acknowledges the Holland Research School for Molecular Chemistry for a fellowship.

Publisher Copyright:
© 2022 Author(s).

Funding

We acknowledge the developer group of Software for Chemistry and Materials (SCM) and computing resources of the Vrije Universiteit Amsterdam. Z.J. acknowledges the Holland Research School for Molecular Chemistry for a fellowship.

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