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Automated Analysis of SEM X-Ray Spectral Images: A Powerful New Microanalysis Tool

Published online by Cambridge University Press:  31 January 2003

Paul G. Kotula ,
Michael R. Keenan  and
Joseph R. Michael
Paul G. Kotula
Affiliation:
Materials Characterization Department, Sandia National Laboratories, P.O. Box 5800, MS 0886, Albuquerque, NM 87185-0886, USA
Michael R. Keenan
Affiliation:
Materials Characterization Department, Sandia National Laboratories, P.O. Box 5800, MS 0886, Albuquerque, NM 87185-0886, USA
Joseph R. Michael
Affiliation:
Materials Characterization Department, Sandia National Laboratories, P.O. Box 5800, MS 0886, Albuquerque, NM 87185-0886, USA
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Abstract

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.

Keywords

spectrum imagespectral imagestatistical analysisprincipal components analysisX-ray microanalysisinformation extractionmultivariate statistical analysis
Type
Instrumentation and Technique
Information
Microscopy and Microanalysis , Volume 9 , Issue 1 , February 2003 , pp. 1 - 17
Copyright
© 2003 Microscopy Society of America

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