Obtaining Oxidation State Information from X-Ray RRS Spectroscopy trough Principal Component Analysis

J. ROBLEDO; H. J. SÁNCHEZ; J. J. LEANI; C. A. PÉREZ

Carlos Paz

Conferencia; SARX 2014; 2014

FaMAF

It has been observed recently that the Resonant Raman Scattering (RRS) [1] peak of an x-ray spectrum contains information about the chemical environment of the irradiated matter [2,3]. This information is obtained with a methodology that involves a very complex processing of the spectrum data. Principal Component Analysis (PCA) [4] is a statistical multivariate technique that analyzes the variancecovariance structure of a set of data, through a few linear combinations of the original variables. This methodology can be applied to analyze RRS spectra. To explore its potentiality, several measurements of different oxides in surface nanolayers were measured in total reflection conditions using synchrotron radiation from beamline D09B-XRF of LNLS, Campinas Brazil (5). 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 and precise. Results show that the PCA based method proposed is a suitable method for the analysis of this kind of spectra, foreseeing its application in future researches.