![]() ![]() To weaken the effect of variations of minor interest, a data normalization strategy was developed and tested. First attempts to use the method led to poor results, which showed mainly the distance between series of samples analyzed at different moments. PCA was shown to improve the identification of chemical shifts of interest and to reveal correlations between peak components. Examples allowed highlighting the contribution of PCA to data treatment by comparing the results of this data analysis with those obtained by the usual XPS quantification methods. ![]() Given the relevance of principal component analysis (PCA) to the treatment of spectrometric data, we have evaluated potentialities and limitations of such useful statistical approach for the harvesting of information in large sets of X-ray photoelectron spectroscopy (XPS) spectra. ![]()
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