Peak fitting of x-ray photoelectron spectroscopy (XPS) data is the primary method for identifying and quantifying the chemical states of the atoms near the surface of a sample. Peak fitting is typically based on the minimization of a figure-of-merit, such as the residual standard deviation (RSD). Here, we show that optimal XPS peak fitting is obtained when the peak shape (the synthetic mathematical function that represents the chemical states of the material) best matches the physics and chemistry of the underlying data. However, because this ideal peak shape is often unknown, constraints on the components of a fit are usually necessary to obtain good fits to data. These constraints may include fixing the relative full width at half maxima (peak widths), area ratios, and/or the relative positions of fit components. As shown in multiple examples, while unconstrained, less-than-optimal peak shapes may produce lower RSDs, they often lead to incorrect results. Thus, the “suboptimal” results (somewhat higher RSDs) that are obtained when constraints are applied to less-than-perfect peak shapes are often preferable because they prevent a fit from yielding unphysical or unchemical results. XPS peak fitting is best performed when all the information available about a sample is used, including its expected chemical and physical composition, information from other XPS narrow and survey scans from the same material, and information from other analytical techniques.
Guide to XPS data analysis: Applying appropriate constraints to synthetic peaks in XPS peak fitting
Note: This paper is part of the Special Topic Collection: Reproducibility Challenges and Solutions II with a Focus on Surface and Interface Analysis.
George H. Major, Vincent Fernandez, Neal Fairley, Emily F. Smith, Matthew R. Linford; Guide to XPS data analysis: Applying appropriate constraints to synthetic peaks in XPS peak fitting. J. Vac. Sci. Technol. A 1 December 2022; 40 (6): 063201. https://doi.org/10.1116/6.0001975
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