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Multivariate statistical analysis of micro-X-ray fluorescence spectral images

  • Mark A. Rodriguez (a1), Paul G. Kotula (a1), James J. M. Griego (a1), Jason E. Heath (a1), Stephen J. Bauer (a1) and Daniel E. Wesolowski (a1)...


Multivariate statistical analysis (MSA) is applied to the extraction of chemically relevant signals acquired with a micro-X-ray fluorescence (μ-XRF) mapping (full-spectral imaging) system. The separation of components into individual histograms enables separation of overlapping peaks, which is useful in qualitatively determining the presence of chemical species that have overlapping emission lines, and holds potential for quantitative analysis of constituent phases via these same histograms. The usefulness of MSA for μ-XRF analysis is demonstrated by application to a geological rock core obtained from a subsurface compressed air energy storage (CAES) site. Coupling of the μ-XRF results to those of quantitative powder X-ray diffraction analysis enables improved detection of trace phases present in the geological specimen. The MSA indicates that the spatial distribution of pyrite, a potentially reactive phase by oxidation, has low concentration and thus minimal impact on CAES operations.


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