Spectroscopy is a group of investigative techniques based on matter-light interactions, and Raman spectroscopy is a subcategory focused on the distinct infrared or visible light scattering caused by the molecular-level transfer of energy from a light beam to a sample.
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In Raman spectroscopy, scattered light is detected by a spectrometer to identify the “chemical fingerprint” of the test sample. By using spectral data, a material can be recognized or classified.
The results of a Raman spectroscopy analysis are usually represented graphically, with the intensity of the scattered light (y-axis) plotted against the frequency of light (x-axis). Also considered an indication of energy, frequency is usually measured by a unit known as the wavenumber, which is represented as reciprocal centimetres (cm-1). Frequencies are plotted in relation to that of the laser, since the change in energy of the light is of interest.
A light beam is made up of many waves of light, each with different frequencies all propagating along the same path. Each frequency plays a part in the total intensity of the beam (I), which is represented as photons per time interval. The strength of a light beam is the value that is ultimately assessed with a spectrometer, with the intensity distribution of all detected frequencies known as the beam's spectrum.
When a light beam strikes matter, it interacts with it in a very particular way based on the interaction between various light waves and the molecules of the sample. Raman spectroscopy is a kind of technique used to describe matter by using a particular type of energy exchange known as "scattering".
Scattering takes place when a powerful light source, usually a laser, strikes a sample, and a portion of the laser light is scattered in various directions. Most of the scattered light has the identical wavelength as the original 'incident' light, but a minor share of the light can hit the sample in a manner that it transfers small quantities of energy. The resulting shift in energy seen in the scattered light can be identified as shifts in frequency and wavelength.
When it comes to identifying the chemical and physical composition of a sample, there are two main scattering processes used in Raman spectroscopy: Rayleigh and Stokes Raman.
Rayleigh scattering does not modify the energy of molecules. In a Raman spectroscopy, Rayleigh-scattered light should be somehow removed from the gathered light because it interferes with Raman-useful signals.
Stokes Raman scattering involves light transferring energy to the molecules of a sample. The structure of the scattered light is highly reliant on the exact kind of molecule. While Stokes scattering is the most frequently used process to obtain a Raman spectrum, its occurrence is many orders of magnitude less probable than Rayleigh scattering, making it challenging to identify.
The common practice to plotting Raman spectra is intensity, or "Count Rate", on the y-axis and the frequency of the "Raman Shift" along the x-axis.
Raman shift is the difference in frequency between the laser light and the scattered light. This difference is unrelated to laser's wavelength and expressed as wavenumbers.
Count Rate is the quantity of events the spectrometer detects for the particular Raman shift per second and is relative to the strength of light detected.
One method of interpreting Raman spectra is the recognition of molecular functional groups, which are distinct subunits of a molecule. The vibrations of functional groups appear in Raman spectra at distinctive Raman shifts. These characteristic shifts allow for an unknown compound to be linked to a known class of substances.
A different procedure for analysis involves looking at the "fingerprint region” of particular spectrum. Aside from the vibrations of particular functional groups, "molecular skeleton" vibrations can be seen in Raman spectra. Skeletal vibrations are generally seen at wavenumbers below 1500 cm-1 and have a substance-specific pattern. This area is the most critical portion of the spectrum for identification.
A third approach involves the use of interpretation software that has a spectral database and a comparison algorithm. This software generates a matching factor that can range from 0 (“no match”) to 100 ("perfect match”). User typically define a threshold for deeming a test sample a suitable match to a known substance.
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