Automated information compression of XPS spectrum using information criteria

Abstract We developed and implemented a fully automated method to perform X-ray photoelectron spectroscopy (XPS) spectral analysis based on the active Shirley method and information criteria. Our method searches a large number of initial fitting models by changing the degree of smoothing, and then optimizes the peak parameters and background parameters to obtain a large number of fitting results. The goodness of those optimized models is ranked using information criteria. As a result of applying this algorithm to measured XPS spectra, we found that, using the Bayesian information criterion (BIC), a simple model with reasonably good agreement and a moderate number of peaks was selected. The model selected by the BIC was close to the result of peak fitting performed by XPS analysis experts.