Uniqueness Plots. A Simple Graphical Tool for Identifying Poor Peak Fits in X-ray Photoelectron Spectroscopy (original) (raw)
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Surface and Interface Analysis, 2000
Standard test data for x-ray photoelectron spectroscopy (XPS-STD) have been developed for determining bias and random error in peak parameters derived from curve fitting in XPS. The XPS-STD are simulated C 1s spectra from spline polynomial models of measured C 1s polymer spectra. Some have a single peak, but most are doublet spectra. The doublets were created from a factorial design with three factors: peak separation, relative intensity of the component peaks, and fractional Poisson noise. These doublet spectra simulated XPS measurements made on different two-component polymer specimens. This, the second of a three-part study, focuses on bias and random errors in determining peak intensities. We report the errors in results from 20 analysts who used a variety of programs and curve-fitting approaches. Peak intensities were analyzed as a ratio of the intensity of the larger peak in a doublet to the total intensity, or as a ratio of intensities for singlet peaks in separate but related spectra. For spectra that were correctly identified as doublets, bias and random errors in peak intensities depended on the amount of separation between the component peaks and on their relative intensities. Median biases for doublets calculated on a relative, unitless scale from −1 to 1 ranged from −0.33 to 0.17, whereas random errors for doublets calculated on the same scale ranged from 0.016 to 0.18. In most cases the magnitude of the median bias exceeded the median random error. On this scale, errors of −0.33 and 0.18 corresponded to errors of factors of 4 and 2, respectively, in determinations of the relative intensities as a ratio of the larger peak in a doublet to the smaller peak. Analysts may evaluate uncertainties in their own analyses of the XPS-STD by visiting the web site http://www.acg.nist.gov/std/.
Surface and Interface Analysis, 2021
Although the fundamental, theoretical peak shape in X-ray photoelectron spectroscopy (XPS) is Lorentzian, some Gaussian character is observed in most XPS signals. Additional complexity in the form of asymmetry is also found in many XPS signals, which requires more advanced peak shapes than the traditional, symmetric Voigt and Gaussian-Lorentzian sum and product (pseudo-Voigt) functions. Here, we discuss the merits and disadvantages of four approaches that have been used to introduce asymmetry into XPS peak shapes: addition of a decaying exponential tail to a symmetric peak shape, the Doniach-Sunjic peak shape, the double-Lorentzian, DL, function, and This article is protected by copyright. All rights reserved. This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/sia.6958 the LX peak shapes, which include the asymmetric Lorentzian (LA), finite Lorentzian (LF), and square Lorentzian (LS) functions. The Doniach-Sunjic peak shape is the only asymmetric, synthetic peak that has a theoretical basis. However, it has an infinite integral, which it makes it problematic in quantitative work. The mathematical bases for the LX and DL peak shapes are discussed, and practical examples of their use in peak fitting are presented. The case is made for the Voigt function being the most appropriate function for XPS peak fitting, in general, which suggests that a modified Voigt function may be the most reasonable for fitting asymmetric XPS signals. The LX and DL functions include convolution with a Guassian, which, which the exception of the LS function, makes them Voigt-like functions. The sources of asymmetry and its complexity are discussed. It is emphasized that not every asymmetric spectrum should be fit with an asymmetric peak shape. I. INTRODUCTION This paper explains and reviews synthetic peak shapes/mathematical functions that may be used to fit asymmetric X-ray photoelectron spectroscopy (XPS) signals. In particular, it provides examples of fitting asymmetric XPS signals with various peak shapes that are available to the XPS community, while also showing and emphasizing that the Voigt peak shape is a superior shape for peak fitting XPS data. This work follows a recent series of guides that have been published on XPS. These guides have been motivated by the current 'reproducibility crisis', 1-5 which has manifested itself in XPS
Enhancing the interpretation of x-ray photoelectron spectra using numerical methods
Surface and Interface Analysis, 1992
X-ray photoelectron spectroscopy (XPS) has long been used as a surface analytical method for the determination of elemental composition and chemistry of a material. Small-area analysis allows the comparison of different areas of a sample surface, while sputter depth profiling makes it possible to follow the specific chemistry as a function of depth. Often in XPS, peak overlap or subtle changes in chemistry may sometimes make the chemical-state analysis of the elements in a material difficult. By using a variety of numerical methods, it is possible to enhance the analysis and interpretation of surface analytical data. Such numerical methods would include linear least-squares fitting and target factor analysis. By using these methods it is possible to enhance the chemical-state interpretation and in many cases significantly increase the detection limits of specific elements. Several examples of the application of numerical methods are used to illustrate the enhancement of data interpretation of XPS data, with special emphasis on linescans and sputter depth profiles.
Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films, 2020
We present a perspective on the use of XPS relative peak intensities for determining composition in homogeneous bulk materials. Nonhomogenous effects, such as composition variation with depth or severe topography effects (e.g., in nanoparticles), are not discussed. We consider only the use of conventional laboratory-based instruments with x-ray sources, Alkα or Mgkα. We address accuracy (not precision, which is much more straightforward) using relative sensitivity factors, RSFs, obtained either empirically from standards (e-RSF) or from the use of theoretical cross sections, σ, (t-RSF). Issues involved are (1) the uncertainty of background subtraction of inelastically scattered electrons, (2) the accuracy of the RSFs, and (3) the role of XPS peak satellite structure, which affects both (1) and (2) above. The XPS of materials tends to fall into two broad classes: where the signals being used for quantification are “main” peaks, which are narrower and more symmetric, followed by a rel...
The alignment of spectrometers and quantitative measurements in X-ray photoelectron spectroscopy
Journal of Electron Spectroscopy and Related Phenomena, 1997
The alignment of the sample in X-ray photoelectron spectrometers is usually made to optimize the spectral intensities. There are two important classes of spectrometer: (i) those in which the analyser acceptance area is independent of the analysed electron kinetic energy; and (ii) those in which this area varies. Model experiments show how an example of a VG ESCALAB II conforms to class (i) whereas an example of an SSI X-probe is of class (ii) and shows an analyser acceptance area which depends approximately inversely on the emitted electron kinetic energy. This latter result means that the SSI X-probe spectrometer must be aligned for the electrons of the highest kinetic energy (smallest analyser acceptance area). A misalignment of 0.1 mm in the sample height can cause a 10% change in the relative intensities between 0 and 1000 eV binding energies. This dependence of the analyser acceptance area with energy is an effect likely to be common in the advanced electron optical systems of modern electron spectrometers and should be understood in order to use such spectrometers effectively. Such dependencies should be determined by analysts for their own instruments in the operating mode that is used for conducting work in which the repeatability of intensity measurements is important.
On line shape analysis in X-ray photoelectron spectroscopy
Surface Science, 2001
Any solid state X-ray photoelectron spectrum (XPS) contains contributions due to multiple inelastic scattering in the bulk, surface excitations, energy losses originating from the screening of the ®nal state hole (intrinsic losses), and, for non-monochromatized incident radiation, ghost lines originating from the X-ray satellites. In the present paper it is shown how all these contributions can be consecutively removed from an experimental spectrum employing a single general deconvolution procedure. Application of this method is possible whenever the contributions mentioned above are uncorrelated. It is shown that this is usually true in XPS to a good approximation. The method is illustrated on experimental non-monochromatized MgKa spectra of Au acquired at dierent detection angles but for the same angle of incidence of the X-rays. Ó
Analysis of X-ray spectra by iterative least squares (AXIL): New developments
X‐Ray …, 1994
The functionality of the computer package AXIL (Analysis of X-ray spectra by Iterative Least squares), suitable for the evaluation of energy-dispersive X-ray spectra, has been extended in a number of ways. First, a background modelling algorithm, based on the use of mutually orthogonal polynomials was introduced to replace the linear or exponential polynomials employed previously. Second, the Gaussian photopeak model employed in previous versions of the program was extended to include the non-Gaussian parts of the characteristic peaks and related background contributions. Both innovations are shown to improve the performance of the spectrum evaluation procedure. Third, the user-friendliness of the evaluation program was enhanced (a) by allowing a PC plug-in MCA card to be directly controlled from within the program and (b) by extending the command-interface to allow for repeated execution of series of commands by means of control loops. A brief description of these changes is given; as an application, the accurate evaluation of micro-XRF images is discussed.
Applied Surface Science, 2018
X-ray photoelectron spectroscopy (XPS) is arguably the most important vacuum technique for surface chemical analysis, and peak fitting is an indispensable part of XPS data analysis. Functions that have been widely explored and used in XPS peak fitting include the Gaussian, Lorentzian, Gaussian-Lorentzian sum (GLS), Gaussian-Lorentzian product (GLP), and Voigt functions, where the Voigt function is a convolution of a Gaussian and a Lorentzian function. In this article we discuss these functions from a graphical perspective. Arguments based on convolution and the Central Limit Theorem are made to justify the use of functions that are intermediate between pure Gaussians and pure Lorentzians in XPS peak fitting. Mathematical forms for the GLS and GLP functions are presented with a mixing parameter m. Plots are shown for GLS and GLP functions with mixing parameters ranging from 0 to 1. There are fundamental differences between the GLS and GLP functions. The GLS function better follows the 'wings' of the Lorentzian, while these 'wings' are suppressed in the GLP. That is, these two functions are not interchangeable. The GLS and GLP functions are compared to the Voigt function, where the GLS is shown to be a decent approximation of it. Practically, both the GLS and the GLP functions can be useful for XPS peak fitting. Examples of the uses of these functions are provided herein.
The equivalent width as a figure of merit for XPS narrow scans
Journal of Electron Spectroscopy and Related Phenomena, 2014
X-ray Photoelectron Spectroscopy (XPS) is a widely used surface analytical tool that provides information about the near surface regions of materials. And while indispensable for XPS data analysis, peak fitting of narrow scans is often a fairly subjective exercise. Herein we introduce the equivalent width (EW) as an additional and less subjective figure of merit for XPS narrow scans. We believe that this parameter will prove particularly useful for analyzing series of similar or nominally identical spectra, perhaps as a component of an expert software system for the machine interpretation of spectra. It also appears to be useful, shedding light on the chemical state of materials, when additional information about a sample is known. The EW XPS is simply defined as the area of a narrow scan divided by the height of the maximum of its peak envelope.