Reassessment of the Shirley and model functions within X-ray photoelectron spectroscopy analysis utilizing comprehensive search methodologies of Bayesian inference

Abstract

The analysis of X-ray photoelectron spectra often faces challenges due to the lack of standardization in modeling approaches, background subtraction methods, and computational algorithms within the field of computer science. The interpretation of XPS data significantly relies on the unique expertise and judgment of individual researchers. Therefore, the objective of this study is to highlight the difficulties associated with analytical methods that depend heavily on the discretion of individual scientists, to elucidate the prevailing models and background subtraction techniques, and to suggest improvements to these methodologies. This endeavor aims to enhance the reliability and reproducibility of XPS analysis, thereby contributing to the advancement of research in this area. By utilizing the information criterion as part of a thorough search methodology in Bayesian inference, we show that our sophisticated analytical techniques significantly outperform others in the analysis of actual X-ray photoelectron spectroscopy (XPS) spectra. This improvement is evidenced through enhanced accuracy and reliability in spectral interpretation, underscoring the efficacy of our methods in practical applications of XPS.