Exploratory methodology for retrieving oxidation state information from X-ray resonant Raman scattering spectrometry.

Abstract

It has been observed recently that the resonant Raman scattering (RRS) peak of an X-ray spectrum contains information about the chemical environment of the irradiated matter. This information is extracted with complex processing of the spectrum data. Principal component analysis (PCA) is a statistical multivariate technique that allows exploring the variance-covariance structure of a set of data, through a few linear combinations of the original variables. This methodology can be applied to obtain information from RRS spectra. To analyze its potentiality, several measurements of different oxides in surface nanolayers were measured in total reflection conditions using synchrotron radiation. Multivariate analysis techniques, in particular, PCA, were used to obtain the information encrypted in the RRS peak, and to establish a new methodology, simpler and more accurate. The results show that multivariate analysis techniques are suitable for the analysis of this kind of spectra, foreseeing its application in future research.