Article by Mark Sparrow, an expert in Raman Spectroscopy analysis, electron and optical microscopy, EDS, FTIR spectroscopy, thermal methods and mercury porosimetry.
Why is it Important to Identify the Polymorphs of Crystalline Silica?
Silicon dioxide, or crystalline silica, is one of the most common minerals on earth and is mostly obtained by the mining and purification of quartz.
It is also a major constituent of sand. Silica is used in the production of glass, optical fibers for telecommunication, and as a raw material for many ceramics. Silica’s high melting point makes it ideal as mold material (sand casting) in the manufacture of metal components. While most of the forms of silica are harmless to our health, crystalline silica dust particles become small enough to be inhaled when finely divided, and can be hazardous.
In addition to the size of the particles, whether or not a particle is hazardous depends on its polymorph of SiO2. There are four SiO2 polymorphs: quartz, cristobalite, tridymite, and moganite in addition to amorphous SiO2, so it is important to be able to distinguish these different forms. One of the few techniques that can accurately identify the different forms of crystalline silica is Raman spectroscopy.
What is Different about Raman Spectroscopy?
Raman spectroscopy provides rapid and reliable identification of SiO2 polymorphs with little or no sample preparation–benefits that assist industry in providing accurate quality assurance, process control and formulation. We can easily identify the SiO2 polymorphs by providing a direct correlation between the spectra (signature “fingerprint”) generated and the polymorph structure.
They each have very different signatures. Sample analysis is easily achieved by simply depositing the mineral powder sample in question onto a suitable substrate. The powder particles are located using edge detection, then they are automatically scanned by the Raman. The resultant spectra are compared to the spectra in Figure 1 to determine the correct polymorph. Particles that match up to the spectra of interest can then be flagged for further investigation.
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