Perspective on improving the quality of surface and material data analysis in the scientific literature with a focus on x-ray photoelectron spectroscopy (XPS)
Authors: Major George H. , Pinder Joshua W. , Austin Daniel E. , Baer Donald R. , Castle Steven L. , Čechal Jan , Clark B. Maxwell , Cohen Hagai , Counsell Jonathan , Herrera-Gomez Alberto , Govindan Pavitra , Kim Seong H. , Morgan David J. , Opila Robert L. , Powell Cedric J. , Průša Stanislav , Roberts Adam , Rocca Mario , Shirahata Naoto , Šikola Tomáš , Smith Emily F. , So Regina C. , Stovall John E. , Strunk Jennifer , Teplyakov Andrew , Terry Jeff , Weber Stephen G. , Linford Matthew R. 
Published: May 2023

Due to significant advances in instrumentation, many previously specialized techniques have become “routine” in user facilities. However, detailed knowledge held by experts has often not been relayed to general users, so they often rely on entry-level information, basic principles, and comparison with literature results for data analysis. As a result, major errors in the data analysis of multiple surface and material analysis techniques, including in x-ray photoelectron spectroscopy (XPS), have been appearing in the scientific literature. Representative examples of serious errors in XPS data analysis are shown in this work. We suggest that surface and material analysis, and perhaps even science in general, are in a state of “pre-crisis.” We use two (logistic) models from population biology to suggest that bad analyses self-correct if they remain below a critical number. However, beyond a threshold, the literature can become useless because of the perpetuation of faulty analyses and concomitant loss of its self-correcting ability. XPS is used by scientists in many communities because of the power of the technique and high-quality instrumentation that is commercially available. Those who make new surfaces and materials face unique challenges because of the large number of surface and material analytical techniques that are often needed to characterize their materials. Graduate students and post-docs are often provided with only minimal instruction on using surface and material characterization methods. High fees for instruments may affect both the quality and the quantity of the data people collect. The Prisoner's Dilemma is a model from game theory that describes situations with reward structures that encourage uncooperative behavior and lead to suboptimal outcomes. However, the outcomes of Prisoner's Dilemma are not inevitable—their consequences change if their reward structures change. The current system does not appear to incentivize detailed learning of surface and material characterization techniques and careful material characterization. Prisoner's dilemmas appear to lead to other undesirable consequences in science. The concerns raised in this work suggest that many manuscripts are incompletely reviewed at present. The different stakeholders in this problem, including authors, research advisers, subject matter experts, reviewers, scientists who notice examples of faulty data analysis, editors, journals and publishers, funding agencies, scientific societies, leaders at universities and research centers, and instrument vendors, can improve the current situation. This work provides specific recommendations for each of these stakeholders. For example, we believe that authors are primarily responsible for the correctness of their work, not reviewers or editors; we question the wisdom of listing the names of the editor and reviewers on a paper; we are grateful for the significant contributions that have been made by subject matter experts to produce standards and tutorial information; the high cost of instrument time at some institutions may limit student access and result in suboptimal analyses; staff scientists often need to be better recognized for their intellectual contributions to studies; publishers may wish to allow selective reviewing of specific sections of papers related to material characterization; the reviewing at some open access journals may be inadequate; while it had its shortcomings, the pre-open access model of publishing incentivized the production and publication of high-quality work; audits of the products (scientific papers) of funding agencies may be necessary; collaboration needs to be encouraged to a greater extent at some institutions; and instrument vendors should not suggest to potential customers that surface characterization, e.g., by XPS, is trivial or simple.