Applying Raman Spectrocospy And Multivariate Statistical Analysis To The Characterization Of Minerals

Raman Spectroscopy has become increasingly popular as a method to rapidly identify and characterize minerals, gem stones and other inorganic materials. Raman spectroscopy provides valuable information about the chemical bonds and structure of materials. In fact, the peak locations and intensities observed in a Raman spectrum can often be used to confirm the presence or absence of particular species in a sample. Some modern Raman spectrometers have been designed to analyze samples less than a micron in size while others are designed to rapidly screen bulk material with no sample preparation. Recent advances in software and automated instrument control have greatly reduced the complexity of Raman spectral analysis and provide an easy-to-use tool for analyzing minerals. We will describe the application of several multivariate statistical analysis techniques that have been developed to make use of the spectral libraries. In these techniques the spectrum is treated as a vector and sophisticated mathematical techniques are used to determine which spectral representations in the reference library best match the spectrum from the sample. The DXR Raman microscope was used to 1) Identify minerals by spectral searching, 2) Identifying several species in a sample using multi-component analysis 3) Mapping different species in an aggregate sample and 4) identifying inclusions in a sample.