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A new asymmetric Pseudo-Voigt function for more efficient fitting of XPS lines

Authors

  • Martin Schmid,

    Corresponding author
    1. Lehrstuhl für Physikalische Chemie II, Universität Erlangen-Nürnberg, Erlangen, Germany
    2. Harvard University, Department of Chemistry and Chemical Biology, Cambridge, USA
    • Correspondence to: Martin Schmid, Harvard University, Department of Chemistry and Chemical Biology, 12 Oxford Street, 02138 Cambridge, MA, USA. E-mail: mschmid@fas.harvard.edu

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  • Hans-Peter Steinrück,

    1. Lehrstuhl für Physikalische Chemie II, Universität Erlangen-Nürnberg, Erlangen, Germany
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  • J. Michael Gottfried

    1. Philipps-Universität Marburg, Fachbereich Chemie, Hans-Meerwein-Straße, Marburg, Germany
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Errata

This article is corrected by:

  1. Errata: A new asymmetric Pseudo-Voigt function for more efficient fitting of XPS lines Volume 47, Issue 11, 1080, Article first published online: 22 September 2015

Abstract

Asymmetric peak profiles for the application in spectroscopy can be obtained in a simple way by substituting the usually constant full width at half maximum parameter in Pseudo-Voigt functions with an energy-dependent expression, for instance of sigmoidal shape. While this approach has been successfully applied to vibrational spectra, we find that the resulting curves are less suitable for least-squares fits of X-ray photoelectron spectroscopy (XPS) data. However, if one additionally allows a variable displacement of the sigmoidal step relative to the peak, excellent fitting results can be obtained. We demonstrate the applicability of our extended approach on several inherently asymmetric XPS lines, i.e. the C 1s signal of graphite and C2H2/Pd(100), the 3d5/2–3d3/2 doublet of palladium, and the 4f7/2–4f5/2 doublet of platinum. Comparison of the corresponding fit results with the results obtained by the application of more elaborate, theory-based line profiles (Doniach-Šunjić and Mahan functions) shows that the modified Pseudo-Voigt function gives practically identical results in terms of peak shape and area, while requiring much less computational effort since no convolution procedures are required for its calculation. Thus, this function is most suitable for application in one of the following situations: (i) the peak shape of a given signal is known but cannot be calculated with ease, and (ii) the theoretical peak shape is not (yet) known, however, one wants to perform a first quantitative screening of the data at issue. Copyright © 2014 John Wiley & Sons, Ltd.

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