A Practical Guide to Predict Resonance Raman Spectra Using DFT Across
Various Software Platforms
Abstract
Raman spectroscopy, when combined with Density Functional Theory (DFT)
calculations, is a powerful method for investigating the vibrational
properties of a broad range of molecular systems. When the Raman laser’s
wavelength resonates with the molecule’s electronic transitions
absorption, certain vibrational peaks are significantly amplified in the
resulting spectrum. This effect, known as Resonance Raman (rR)
spectroscopy, enhances the detection of molecular features and allows
the observation of species at low concentrations. However, predicting rR
spectra through DFT presents significant computational challenges. The
theoretical modeling of rR spectra is more complex than non-resonant
Raman spectra and less documented in the literature. This guide aims to
address this gap by providing detailed and practical instructions for
predicting rR spectra using various computational chemistry software,
including ORCA, Gaussian, and ADF. The methods outlined are designed to
help researchers accurately model rR spectra, providing deeper insights
into molecular structure, reactivity, and chemical transformations.