Journal
MICROSCOPY AND MICROANALYSIS
Volume 12, Issue 6, Pages 538-544Publisher
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S1431927606060636
Keywords
STEM; X-ray microanalysis; spectral imaging; multivariate statistical analysis; multivariate curve resolution; subpixel spectral deconvolution
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Multivariate statistical analysis methods have been applied to scanning transmission electron microscopy (STEM) energy-dispersive X-ray spectral images. The particular application of the multivariate curve resolution (MCR) technique provides a high spectral contrast view of the raw spectral image. The power of this approach is demonstrated with a microelectronics failure analysis. Specifically, an unexpected component describing a chemical contaminant was found, as well as a component consistent with a foil thickness change associated with the focused ion beam specimen preparation process. The MCR solution is compared with a conventional analysis of the same spectral image data set.
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