Versailles Project on Advanced Materials and Standards interlaboratory study on intensity calibration for x-ray photoelectron spectroscopy instruments using low-density polyethylene

We report the results of a Versailles Project on Advanced Materials and Standards interlaboratory study on the intensity scale calibration of x-ray photoelectron spectrometers using low-density polyethylene (LDPE) as an alternative material to gold, silver, and copper. An improved set of LDPE reference spectra, corrected for different instrument geometries using a quartz-monochromated Al Kα x-ray source, was developed using data provided by participants in this study. Using these new reference spectra, a transmission function was calculated for each dataset that participants provided. When compared to a similar calibration procedure using the NPL reference spectra for gold, the LDPE intensity calibration method achieves an absolute offset of ∼3.0% and a systematic deviation of ±6.5% on average across all participants. For spectra recorded at high pass energies (≥90 eV), values of absolute offset and systematic deviation are ∼5.8% and ±5.7%, respectively, whereas for spectra collected at lower pass energies (<90 eV), values of absolute offset and systematic deviation are ∼4.9% and ±8.8%, respectively; low pass energy spectra perform worse than the global average, in terms of systematic deviations, due to diminished count rates and signal-to-noise ratio. Differences in absolute offset are attributed to the surface roughness of the LDPE induced by sample preparation. We further assess the usability of LDPE as a secondary reference material and comment on its performance in the presence of issues such as variable dark noise, x-ray warm up times, inaccuracy at low count rates, and underlying spectrometer problems. In response to participant feedback and the results of the study, we provide an updated LDPE intensity calibration protocol to address the issues highlighted in the interlaboratory study. We also comment on the lack of implementation of a consistent and traceable intensity calibration method across the community of x-ray photoelectron spectroscopy (XPS) users and, therefore, propose a route to achieving this with the assistance of instrument manufacturers, metrology laboratories, and experts leading to an international standard for XPS intensity scale calibration

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Zinc and copper, by high sensitivity-low energy ion scattering

Low energy ion scattering (LEIS) is an extremely surface sensitive technique that can quantitatively analyze the outermost atomic layer of a material. In LEIS and high sensitivity-low energy ion scattering (HS-LEIS), straightforward quantitation is available using reference and/or standard materials. Here, we present the HS-LEIS spectra of zinc obtained with 3 keV 4He+ and 4 keV 20Ne+ projectile ions. Zinc is an important material with a wide range of applications. Thus, these spectra should be useful standards/references for future applications. A high purity zinc foil was used for these measurements after the removal of the oxide layer. As a reference for the instrumental sensitivity, the spectra for Cu from a high purity foil are also included with this submission. Atomic sensitivity and relative sensitivity factors for Zn and Cu are reported

Practical guide on chemometrics/informatics in x-ray photoelectron spectroscopy (XPS). I. Introduction to methods useful for large or complex datasets

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

Practical guide on chemometrics/informatics in x-ray photoelectron spectroscopy (XPS). II. Example applications of multiple methods to the degradation of cellulose and tartaric acid

Chemometrics/informatics, and data analysis in general, are increasingly important in x-ray photoelectron spectroscopy (XPS) because of the large amount of information (spectra/data) that is often collected in degradation, depth profiling, operando, and imaging studies. In this guide, we present chemometrics/informatics analyses of XPS data using a summary statistic (pattern recognition entropy), principal component analysis, multivariate curve resolution (MCR), and cluster analysis. These analyses were performed on C 1s, O 1s, and concatenated (combined) C 1s and O 1s narrow scans obtained by repeatedly analyzing samples of cellulose and tartaric acid, which led to their degradation. We discuss the following steps, principles, and methods in these analyses: gathering/using all of the information about samples, performing an initial evaluation of the raw data, including plotting it, knowing which chemometrics/informatics analyses to choose, data preprocessing, knowing where to start the chemometrics/informatics analysis, including the initial identification of outliers and unexpected features in data sets, returning to the original data after an informatics analysis to confirm findings, determining the number of abstract factors to keep in a model, MCR, including peak fitting MCR factors, more complicated MCR factors, and the presence of intermediates revealed through MCR, and cluster analysis. Some of the findings of this work are as follows. The various chemometrics/informatics methods showed a break/abrupt change in the cellulose data set (and in some cases an outlier). For the first time, MCR components were peak fit. Peak fitting of MCR components revealed the presence of intermediates in the decomposition of tartaric acid. Cluster analysis grouped the data in the order in which they were collected, leading to a series of average spectra that represent the changes in the spectra. This paper is a companion to a guide that focuses on the more theoretical aspects of the themes touched on here

Area-Selective Atomic Layer Deposition of ZnO on Si\SiO₂ Modified with Tris(dimethylamino)methylsilane

Delayed atomic layer deposition (ALD) of ZnO, i.e., area selective (AS)-ALD, was successfully achieved on silicon wafers (Si\SiO2) terminated with tris(dimethylamino)methylsilane (TDMAMS). This resist molecule was deposited in a home-built, near-atmospheric pressure, flow-through, gas-phase reactor. TDMAMS had previously been shown to react with Si\SiO2 in a single cycle/reaction and to drastically reduce the number of silanols that remain at the surface. ZnO was deposited in a commercial ALD system using dimethylzinc (DMZ) as the zinc precursor and H2O as the coreactant. Deposition of TDMAMS was confirmed by spectroscopic ellipsometry (SE), X-ray photoelectron spectroscopy (XPS), and wetting. ALD of ZnO, including its selectivity on TDMAMS-terminated Si\SiO2 (Si\SiO2\TDMAMS), was confirmed by in situ multi-wavelength ellipsometry, ex situ SE, XPS, and/or high-sensitivity/low-energy ion scattering (HS-LEIS). The thermal stability of the TDMAMS resist layer, which is an important parameter for AS-ALD, was investigated by heating Si\SiO2\TDMAMS in air and nitrogen at 330 °C. ALD of ZnO takes place more readily on Si\SiO2\TDMAMS heated in the air than in N2, suggesting greater damage to the surface heated in the air. To better understand the in situ ALD of ZnO on Si\SiO2\TDMAMS and modified (thermally stressed) forms of it, the ellipsometry results were plotted as the normalized growth per cycle. Even one short pulse of TDMAMS effectively passivates Si\SiO2. TDMAMS can be a useful, small-molecule inhibitor of ALD of ZnO on Si\SiO2 surfaces.</p

A tag-and-count approach for quantifying surface silanol densities on fused silica based on atomic layer deposition and high-sensitivity low-energy ion scattering

Surface silanols (SiOH) are important moieties on glass surfaces. Here we present a tag-and-count approach for determining surface silanol densities, which consists of tagging surface silanols with Zn via atomic layer deposition (ALD) followed by detection of the zinc by high sensitivity-low energy ion scattering (HS-LEIS). Shards of fused silica were hydroxylated with aqueous hydrofluoric acid (HF) and then heated to 200, 500, 700, or 900 °C. These heat treatments increasingly condense and remove surface silanols. The samples then underwent one ALD cycle with dimethylzinc (DMZ) or diethylzinc (DEZ) followed by water. As expected, fused silica surfaces heated to higher temperatures showed lower Zn coverages. When fused silica surfaces treated at 200 °C were exposed to DMZ for two different dose times, the same sub-monolayer quantity of Zn was obtained by X-ray photoelectron spectroscopy (XPS). Surface cleaning/preparation immediately before HS-LEIS, including atomic oxygen treatment and annealing, played a critical role in these efforts. Surfaces treated with DMZ generally showed slightly higher Zn signals by LEIS. Using this methodology, a value of 4.59 OH/nm2 was found for fully hydroxylated fused silica. Both this result and those obtained at 500, 700, and 900 °C are in very good agreement with literature values