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Key Parameters Affecting Quantitative Analysis of STEM-EDS Spectrum Images

Published online by Cambridge University Press:  08 April 2010

Chad M. Parish  and
Luke N. Brewer
Chad M. Parish*
Affiliation:
Sandia National Laboratories, Albuquerque, NM 87185, USA
Luke N. Brewer
Affiliation:
Sandia National Laboratories, Albuquerque, NM 87185, USA
*
Corresponding author. E-mail: parishcm@ornl.gov
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Abstract

In this article, we use simulated and experimental data to explore how three operator-controllable parameters—(1) signal level, (2) detector resolution, and (3) number of factors chosen for analysis—affect quantitative analyses of scanning transmission electron microscopy–energy dispersive X-ray spectroscopy spectrum images processed by principal component analysis (PCA). We find that improvements in both signal level and detector resolution improve the precision of quantitative analyses, but that signal level is the most important. We also find that if the rank of the PCA solution is not chosen properly, it may be possible to improperly fit the underlying data and degrade the accuracy of results. Additionally, precision is degraded in the case when too many factors are included in the model.

Keywords

STEMX-rayspectrum imagingmultivariate statisticsPCAEDS
Type
Instrumentation and Software: Development and Applications
Information
Microscopy and Microanalysis , Volume 16 , Issue 3 , June 2010 , pp. 259 - 272
Copyright
Copyright © Microscopy Society of America 2010

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