Spectrum adapted expectation-conditional maximization algorithm for extending high–throughput peak separation method in XPS analysis

Abstract

We introduced the spectrum-adapted expectation-conditional maximization (ECM) algorithm to improve the efficiency of the peak fitting of spectral data by various fitting models. The spectrum-adapted ECM algorithm can perform the peak fitting by using the Pseudo–Voigt mixture model and Doniach–Šunjić–Gauss mixture model which are generally used for the peak fitting in the X-ray photoelectron spectroscopy. Analyses of the synthetic and experimental spectral data showed that the proposed method quickly completed the calculation and estimated well-fitted curves to spectral data. This result suggests that the spectrum adapted ECM algorithm efficiently perform the peak fitting for large number of spectral data sets.

Keywords

• peak fitting
• x-ray photoelectron spectroscopy
• expectation-conditional maximization algorithm
• high-throughput analysis