What is it about?

Computational chemistry can be applied to vibrational spectroscopy in different ways, such as for a better characterization and assignment of all the bands of the experimental spectra, as a tool in the identification of the tautomers present in the gas phase and in the solid state through their spectra, and for the simulation of the solid and liquid phase of a compound and the consequent simulation and interpretation of their spectra.

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Why is it important?

The motivation for the application of computational chemistry to vibrational spectroscopy is to make it a more practical tool. From a practical point of view, the main disadvantage of vibrational spectroscopy is the lack of a direct spectrum-structure relation. This makes it impossible or difficult to determinate the structure of a molecule from its vibrational spectrum. However, vibrational spectroscopy has many advantages, such as: greater sensitivity, which makes it possible to detect very small amounts, high applicability to solids, liquids and gasses, as well as to adsorbed layers, etc., lower Instrument costs (in IR), etc. It is thus clear that many of the advantages of vibrational spectroscopy could be increased if a method could be found to reliably predict vibrational spectra. Such a method could be used to calculate the expected spectra of proposed structures. Comparison with the observed spectra would confirm the identity of a product, even that of a completely new molecule. Density Functional Theory (DFT) quantum chemical methods are the most suitable for this purpose.

Perspectives

I hope that this article can give new ideas about the possibilities to use the vibrational spectroscopy to resolve problem, and how can the DFT theoretical methods help in this task

Mauricio Alcolea Palafox
Facultad de Ciencias Quimicas

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This page is a summary of: Computational chemistry applied to vibrational spectroscopy: A tool for characterization of nucleic acid bases and some of their 5-substituted derivatives, Physical Sciences Reviews, August 2017, De Gruyter,
DOI: 10.1515/psr-2016-0132.
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