Raman spectroscopy is used in many varied fields – in fact, it can be used in any application where non-destructive, microscopic, chemical analysis and imaging is required. Whether the goal is qualitative or quantitative data, Raman analysis can provide key information easily and quickly. It can be used to rapidly characterize the chemical composition and structure of a sample, whether solid, liquid, gas, gel, slurry or powder.
The discussion below highlights some key areas where the use of Raman is well established, and its value greatly appreciated.
Pharmaceuticals and Cosmetics
Geology and Mineralogy
Carbon Materials
Semiconductors
Life Sciences
Spectra of TiO2
In most cases Raman scattering is sensitive to material phase, polymorphism and solid form. Thus, even though two materials may have identical chemical formulae, their different crystal structure or phase will often result in distinct spectra. Phase changes are often clearly distinguished within the spectrum, but other structural differences such as polymorphism can reveal themselves only through very subtle spectral changes. In this case, it is often necessary to work with high spectral resolution to allow the minor changes to be confidently characterized.
Spectra of polycrystalline (red) and monocrystalline Si (green). Analysis of crystallinity of a material.
In most cases Raman scattering is sensitive to the degree of crystallinity in a sample. Typically a crystalline material yields a spectrum with very sharp, intense Raman peaks, while an amorphous material will show broader, less intense Raman peaks. These two states (e.g., fully amorphous, or fully crystalline) can be considered as spectral extremes, and a Raman spectrum from an intermediate state (e.g., partially crystalline) will have characteristics which are intermediate in terms of peak intensity and width (sharpness). Differences between intermediate states can be subtle, and it is often useful to have high spectral resolution capability so that minor spectral changes can be confidently characterized.
Using software peak fitting routines, it is possible to accurately calculate peak width and intensity, which can then be used, with calibration and comparison with other techniques, as a quantitative measure of crystallinity. Similar analysis of Raman maps allows images of degree of crystallinity to be produced.
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