Spectroscopic parallax is the measure of the distance between two stars or celestial objects and relies on the stellar spectral type and luminosity class defined by the Morgan-Keenan classification system. UV, IR (Infrared), Raman or Optical spectrographic instruments are integrated in many telescopes and are used to obtain information on brightness, temperature (surface), density and velocities. Stars are classified based on their type and on their brightness, which allow us to obtain distances to them, however, with previous classification systems, the star’s size (dwarf, giant or supergiant) and composition (heavy metal versus carbon stars) were also used. The Morgan-Keenan classification offers information on the star colour (very blue, red) and the type, although the infrared wavelengths are approximately > 9000 Å, falling in the near-infrared range; spectra can be ulteriorly divided into continuous, band and linear. Band spectra are usually descriptive of molecular compounds and are the ones that we immersed in, by venturing an interpretation of the Raman-IR band spectra of neutral glycine (or NT glycine). Our method consisted in using vibrational dynamics (VD), the study of atomic oscillations within a molecule, after obtaining experimental vibrations for glycine through Raman or IR literature data. These techniques have been widely used in the past, along with X-ray or neutron scattering diffraction techniques, however, in recent years, researchers have used density functional theory, ab intio, or other computer simulation methods that facilitate band recognition. The goal of this work is to apply vibrational dynamics studies to the structure of NT glycine, and to then compare these values with its IR and Raman frequencies. By analyzing both simulation results and empirical data, we gain important information about the vibration modes of glycine. This study also shows that ‘invisible’ bands can be ‘detected’ with this technique. VD could therefore be used in the measurement of stellar abundances and to refine the quality of experimental Raman-IR data.
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[v1] 2018-11-12 02:05:51
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