This study was undertaken to understand the extent and nature of problems in x-ray photoelectron spectroscopy (XPS) data reported in the literature. It first presents an assessment of the XPS data in three high-quality journals over a six-month period. This analysis of 409 publications showing XPS spectra provides insight into how XPS is being used, identifies the common mistakes or errors in XPS analysis, and reveals which elements are most commonly analyzed. More than 65% of the 409 papers showed fitting of XP spectra. An ad hoc group (herein identified as “the committee”) of experienced XPS analysts reviewed these spectra and found that peak fitting was a common source of significant errors. The papers were ranked based on the perceived seriousness of the errors, which ranged from minor to major. Major errors, which, in the opinion of the ad hoc committee, can render the interpretation of the data meaningless, occurred when fitting protocols ignored underlying physics and chemistry or contained major errors in the analysis. Consistent with other materials analysis data, ca. 30% of the XPS data or analysis was identified as having major errors. Out of the publications with fitted spectra, ca. 40% had major errors. The most common elements analyzed by XPS in the papers sampled and researched at an online database, include carbon, oxygen, nitrogen, sulfur, and titanium. A scrutiny of the papers showing carbon and oxygen XPS spectra revealed the classes of materials being studied and the extent of problems in these analyses. As might be expected, C 1s and O 1s analyses are most often performed on sp2-type materials and inorganic oxides, respectively. These findings have helped focus a series of XPS guides and tutorials that deal with common analysis issues. The extent of problematic data is larger than the authors had expected. Quantification of the problem, examination of some of the common problem areas, and the development of targeted guides and tutorials may provide both the motivation and resources that enable the community to improve the overall quality and reliability of XPS analysis reported in the literature.
Chemometrics/informatics and data analysis, in general, are increasingly important topics in x-ray photoelectron spectroscopy (XPS) because of the large amount of information (data/spectra) that are often collected in degradation, depth profiling, operando, and imaging studies. In this guide, we discuss vital, theoretical aspects and considerations for chemometrics/informatics analyses of XPS data with a focus on exploratory data analysis tools that can be used to probe XPS datasets. These tools include a summary statistic [pattern recognition entropy (PRE)], principal component analysis (PCA), multivariate curve resolution (MCR), and cluster analysis. The use of these tools is explained through the following steps: (A) Gather/use all the available information about one's samples, (B) examine (plot) the raw data, (C) developing a general strategy for the chemometrics/informatics analysis, (D) preprocess the data, (E) where to start a chemometrics/informatics analysis, including identifying outliers or unexpected features in datasets, (F) determine the number of abstract factors to keep in a model, (G) return to the original data after a chemometrics/informatics analysis to confirm findings, (H) perform MCR, (I) peak fit the MCR factors, (J) identify intermediates in MCR analyses, (K) perform cluster analysis, and (L) how to start doing chemometrics/informatics in one's work. This guide has Paper II [Avval et al., J. Vac. Sci. Technol. A 40, 063205 (2022)] that illustrates these steps/principles by applying them to two fairly large XPS datasets. In these papers, special emphasis is placed on MCR. Indeed, in this paper and Paper II, we believe that, for the first time, it is suggested and shown that (1) MCR components/factors can be peak fit as though they were XPS narrow scans and (2) MCR can reveal intermediates in the degradation of a material. The other chemometrics/informatics methods are also useful in demonstrating the presence of outliers, a break (irregularity) in one of the datasets, and the general trajectory/evolution of the datasets. Cluster analysis generated a series of average spectra that describe the evolution of one of the datasets.
Near-ambient pressure x-ray photoelectron spectroscopy (NAP-XPS) is a less traditional form of XPS that allows samples to be analyzed at relatively high pressures, i.e., greater than 2500 Pa. With NAP-XPS, a wide variety of unconventional materials can be analyzed, including moderately volatile liquids, biological samples, porous materials, and/or polymeric materials that outgas significantly. Charge compensation with NAP-XPS takes place simply through the residual/background gas in the chamber, which is ionized by the incident x-rays. High quality spectra—high resolution and good signal-to-noise ratios—are regularly obtained. This article is an introduction to a series of papers in Surface Science Spectra on the NAP-XPS characterization of a series of materials. The purpose of these articles is to introduce and demonstrate the versatility and usefulness of the technique.
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
Near-ambient pressure x-ray photoelectron spectroscopy (NAP-XPS) is a less traditional form of XPS that allows samples to be analyzed at relatively high pressures, i.e., greater than 2500 Pa. With NAP-XPS, XPS can probe moderately volatile liquids, biological samples, porous materials, and/or polymeric materials that outgas significantly. In this submission, we show survey, O 1s, C 1s, S 2p, and S 2s NAP-XPS spectra from dimethyl sulfoxide (DMSO), a widely used organic solvent that is miscible with water. The sample was analyzed directly in its native, liquid state at room temperature. In general, both liquid and gas phase peaks are observed in the narrow scans. Due to the importance of DMSO in both chemistry and biology, it is likely that it will appear in future NAP-XPS analyses. Accordingly, these data may serve as a reference for future work.
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