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Extracting Chemical Information From Energy-Dispersive X-Ray Spectra by Multivariate Statistical Analysis (MSA)
Published online by Cambridge University Press: 02 July 2020
Extract
The introduction of Multivariate Statistical Analysis techniques such as Principal Component Analysis (PCA) to the study of EDS and EELS spectra has opened up new possibilities for processing spectral data. In conventional EDS analysis each spectrum provides information about the elemental composition of the sample at a specific probe position. Where the signal arises from a single phase this elemental composition corresponds to the chemical composition of the phase. However, where the probe is incident on a multiphase region of the sample it is impossible to make a direct identification of the different chemical phases contributing to the overall spectrum.
With PCA it is no longer necessary to consider the spectra as isolated pieces of information. It is now possible to analyze a series of spectra as a single entity, looking for correlations between the variations in the elemental signals present in the individual spectra.
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- 30 Years of Energy Dispersive Spectrometry in Microanalysis
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- Copyright © Microscopy Society of America