Quantitative compositional analysis using thermal emission spectroscopy: Application to igneous and metamorphic rocks

The mineral composition of a suite of igneous and metamorphic rocks was determined using the thermal infrared emission spectra of these rocks in a linear spectral deconvolution algorithm. This algorithm assumes that the infrared spectrum of each rock is a linear mixture of the component mineral spectra weighted by volume abundance. A diverse suite of 36 common rock-forming and accessory minerals was used in the deconvolution. The model was tested by comparing the mineralogy derived from the infrared spectrum with petrographically estimated abundances for 45 igneous and 51 metamorphic rock samples. The mineral abundances derived from these two techniques agree to within ±7-15% for the primary minerals feldspar, pyroxene, quartz, and calcite/ dolomite and ±9-17% for secondary minerals such as micas and amphiboles. These differences are comparable to the error for traditional thin section mode estimates, which are ±5-15% for major minerals and ≤5% for minor minerals. The detection limit for the primary and secondary minerals found in the rocks analyzed ranged from 5 to 10%. Each major rock type studied here was easily distinguished by its spectral characteristics. The best results, in both the qualitative determination of the rock type and dominant minerals and the quantitative reproduction of absorption features and mineral composition, were obtained for igneous rock samples. For metamorphic rocks, pelite and quartzo-feldspathic samples gave slightly better results than calcareous or mafic samples. A controlled analysis, in which the end-member suite was reduced based on an initial estimate of the rock type, only improved the results by several percent for most primary and secondary minerals. The quality of the obtained results demonstrates that a linear deconvolution of infrared emission spectra provides an accurate, rapid technique for determining the quantitative mineral composition of rock samples in a laboratory and has application to future in situ measurements.