Spectrum adapted expectation-conditional maximization algorithm for extending high–throughput peak separation method in XPS analysis. Issue 1 (1st January 2021)

• Record Type: Journal Article
• Authors: Matsumura, Tarojiro; Nagamura, Naoka; Akaho, Shotaro; Nagata, Kenji; Ando, Yasunobu
• Is Part Of: Science and Technology of Advanced Materials: Methods. Volume 1:Issue 1(2021)
• Page Start: 45
• Page End: 55
• Publication Date: 2021-01-01
• Subjects: Peak fitting -- X-ray photoelectron spectroscopy -- expectation-conditional maximization algorithm -- high-throughput analysis
• DOI: 10.1080/27660400.2021.1899449
• Languages: English
• ISSNs: 2766-0400

Abstract

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. Graphical Abstract: uf0001