Automated Analysis of SEM X-Ray Spectral Images: A Powerful New Microanalysis Tool
Spectral imaging in the scanning electron microscope (SEM) equipped with an energy-dispersive X-ray (EDX) analyzer has the potential to be a powerful tool for chemical phase identification, but the large data sets have, in the past, proved too large to efficiently analyze. In the present work, we describe the application of a new automated, unbiased, multivariate statistical analysis technique to very large X-ray spectral image data sets. The method, based in part on principal components analysis, returns physically accurate (all positive) component spectra and images in a few minutes on a standard personal computer. The efficacy of the technique for microanalysis is illustrated by the analysis of complex multi-phase materials, particulates, a diffusion couple, and a single-pixel-detection problem.(Received November 6 2001)
(Accepted June 5 2002)
Key Words: spectrum image; spectral image; statistical analysis; principal components analysis; X-ray microanalysis; information extraction; multivariate statistical analysis.
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