Curve Fitting in XPS: Resources for Good Practices and Tools for Avoiding Mistakes

Surface Analysis Spotlight: XPS

by Kateryna Artyushkova

     Senior Staff Scientist

One of the main objectives of the curve fitting of XPS data is to extract chemical information about the sample being examined. Both novices and experts will agree that curve-fitting spectra is one of the most challenging components of performing XPS analysis.

Most specialists working with XPS data experienced skepticism while introducing results of XPS curve fits to their colleagues from the non-surface analysis community. This skepticism is mainly caused by the impression that any spectrum can be fitted with infinite combinations of peaks of different widths and shapes with the same goodness of fit. Hence, it is impossible to derive accurate chemical and, most important, quantitative information based on curve fitting results. To support this skepticism, the scientific literature is indeed filled with poorly fitted spectra and, therefore, incorrectly interpreted XPS data.1 

Despite computational advances and higher accessibility of software resources, it has been challenging to develop a  chemically and physically meaningful approach to curve fitting. In a study of XPS data in three high-profile journals, it was observed that roughly 60% of the papers using XPS analyzed the data using some type of curve fitting.1 Furthermore, errors, misconceptions, and bad curve fitting practices accounted for most of the serious problems in both the measured XPS data and the spectral analysis that were identified in more than 40% of the papers analyzed.

There has been a substantial effort in addressing these problems, and we, at Physical Electronics, are committed to helping out customers and others to avoid some of the common pitfalls in XPS data analysis and reporting.

The recent collection of XPS guides published in the JVSTA journal aims to help scientists identify problematic and erroneous data and provide directions and related information regarding best practices. Paper “Practical guide for curve fitting in X-ray photoelectron spectroscopy”, which has an impressive 12000 reads, discusses the physics and chemistry involved in generating XPS spectra, describes good practices for peak fitting and provides examples of appropriate use along with tools for avoiding mistakes.

Moreover, recently we had a webinar on XPS curve fitting in which we discussed the theory being XPS curve fitting and demonstrated practical approaches for analyzing XPS core regions. We showed useful examples of handling overlapping peaks, fitting transition metal spectra, appropriately constraint spin-orbit split peak ratios and energy separation, and others. You can watch it on our YouTube channel.

You can always contact our scientists if you have any questions related to curve-fitting or are interested in attending a short course on curve fitting.

Please fill out this survey if you are interested in attending a short course on curve fitting.

1Linford, M. (2020). Proliferation of Faulty Materials Data Analysis in the Literature. Microscopy and Microanalysis, 26 (1), doi:10.1017/S1431927619015332

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