Multivariate analysis of ToF‐SIMS data using mass segmented peak lists

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) provides detailed molecular insight into the surface chemistry of a diverse range of material types. Extracting useful and specific information from the mass spectra and reducing the dimensionality of very large datasets are a challenge that has not been fully resolved. Multivariate analysis has been widely deployed to assist in the interpretation of ToF‐SIMS data. Principal component analysis is a popular approach that requires the generation of peak lists for every spectrum. Peak list sizes and the resulting data matrices are growing, complicating manual peak selection and analysis. Here we report the generation of very large ToF‐SIMS peak lists using up‐binning, the mass segmentation of spectral data in the range 0 to 300 m/z in 0.01 m/z intervals. Time‐of‐flight secondary ion mass spectrometry data acquired from a set of 4 standard polymers (polyethylene terephthalate, polytetrafluoroethylene, poly(methyl methacrylate), and low‐density polyethylene) are used to demonstrate the efficacy of this approach. The polymer types are discriminated to a moderate extent by principal component analysis but are easily skewed with saturated species or contaminants present in ToF‐SIMS data. Artificial neural networks, in the form of self‐organising maps, are introduced and provide a non‐linear approach to classifying data and focussing on similarities between samples. The classification outcome achieved is excellent for different polymer types and for spectra from a single polymer type generated by using different primary ions. This method offers great promise for the investigation of more complex systems including polymer classes and blends and mixtures of biological materials.     

Simple statistically based alternatives to MAF for ToF‐SIMS spectral image analysis

The maximum autocorrelation factors technique (MAF) is becoming increasingly popular for the multivariate analysis of spectral images acquired with time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) instruments. In this article, we review the conditions under which the underlying chemical information can be separated from the large‐scale, non‐uniform noise characteristic of ToF‐SIMS data. Central to this pursuit is the ability to assess the covariance structure of the noise. Given a set of replicate images, the noise covariance matrix can be estimated in a straightforward way using standard statistical tools. Acquiring replicate images, however, is not always possible, and MAF solves a subtly different problem, namely, how to approximate the noise covariance matrix from a single image when replicates are not available. This distinction is important; the MAF approximation is not an unbiased statistical estimate of the noise covariance matrix, and it differs in a highly significant way from a true estimate for ToF‐SIMS data. Here, we draw attention to the fact that replicate measurements are made during the normal course of acquiring a ToF‐SIMS spectral image, rendering the MAF procedure unnecessary. Furthermore, in the common case that detector dead‐time effects permit no more than one ion of any specific species to be detected on a single primary ion shot, the noise covariance matrix can be estimated in a particularly simple way, which will be reported. Copyright © 2011 John Wiley & Sons, Ltd.     

Image fusion combining SEM and ToF‐SIMS images

Image fusion allows for the combination of an image containing chemical information but low spatial resolution with a high‐spatial resolution image having little to no chemical information. The resulting hybrid image retains all the information from the chemically relevant original image, with improved spatial resolution allowing for visual inspection of the spatial correlations. In this research, images were obtained from two sample test grids: one of a copper electron microscope grid with a letter ‘A’ in the center (referred to below as the ‘A‐grid’), and the other a Tantalum and Silicon test grid from Cameca that had an inscribed letter ‘C’ (referred to below as the ‘Cameca grid’). These were obtained using scanning electron microscopy (SEM) and time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). Image fusion was implemented with the Munechika algorithm. The edge resolution of the resulting hybrid image was calculated compared with the edge resolution obtained for both the individual ToF‐SIMS and SEM images. The challenges of combining complimentary datasets from different instrumental analytical methods are discussed as well as the advantages of having a hybrid image. The distance across the edge for hybrid images of the A‐Grid and the Cameca grid were determined to be 21 µm and 8 µm, respectively. When these values were compared to the original ToF‐SIMS, SEM and optical microscopy measurements, the fused image had a spatial resolution nearly equal to that obtained in the SEM image for both samples. Copyright © 2014 John Wiley & Sons, Ltd.     

The statistics of ToF‐SIMS data revisited and introduction of the empirical Poisson correction

Generation of time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) data involves two overarching processes: secondary ion production and secondary ion detection. The interpretation of ToF‐SIMS data is facilitated if the intensities of the as‐measured mass spectra are proportional to the abundances of the species under investigation. While secondary ion yield is normally taken to be a linear process, ion detection is not owing to detector dead‐time effects. Consequently, methods have been devised that attempt to linearize, or correct, data that are affected by the dead time. In this article, we review the statistics of ToF‐SIMS data generation and confirm a report in the literature that abundance estimates from so‐called Poisson corrections are biased. We show that these corrections are only unbiased asymptotically and that a rigorous probabilistic analysis can quantitatively account for the observed bias. Two sources of bias are identified, one having a statistical basis and one due to the form of the correction equation at high ion detection rates. Based on insights gained from this analysis, we propose a new correction equation, the empirical Poisson correction, which largely eliminates the statistical bias. The performance of the proposed correction is illustrated by reanalyzing 14 experimentally measured datasets that suffer from varying levels of dead‐time effects. Copyright © 2016 John Wiley & Sons, Ltd.     

The accuracy and precision of the advanced Poisson dead‐time correction and its importance for multivariate analysis of high mass resolution ToF‐SIMS data

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) data collected in single ion counting mode suffers from dead‐time effects that lead to potentially confusing artefacts when common multivariate analysis (MVA) methods are applied to the data. These artefacts can be eliminated by applying an advanced Poisson dead‐time correction that accounts for the signal intensity in the dead‐time window preceding each time channel. Because this correction is nonlinear, it changes the noise distribution in the data. In this work, the accuracy of this dead‐time correction and the noise characteristics of the corrected data have been analysed for spectra with small numbers of primary ion pulses. A simple but accurate equation for estimating the standard deviation in the advanced dead‐time corrected data has been developed. Based on these results, a scaling procedure to enable successful MVA of advanced dead‐time corrected ToF‐SIMS data has been developed. The improvements made possible by using the advanced dead‐time correction and our recommended scaling are presented for principal components analysis of a ToF‐SIMS image of aerosol particles on polytetrafluoroethylene. Recommendations are made for using the advanced dead time correction and scaling ToF‐SIMS data in order optimize the outcomes of MVA. Copyright © 2014 John Wiley & Sons, Ltd.     

Extraction of hidden information of ToF‐SIMS data using different multivariate analyses

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) is a powerful tool for determining surface information of complex systems such as polymers and biological materials. However, the interpretation of ToF‐SIMS raw data is often difficult. Multivariate analysis has become effective methods for the interpretation of ToF‐SIMS data. Some of multivariate analysis methods such as principal component analysis and multivariate curve resolution are useful for simplifying ToF‐SIMS data consisting of many components to that explained by a smaller number of components. In this study, the ToF‐SIMS data of four layers of three polymers was analyzed using these analysis methods. The information acquired by using each method was compared in terms of the spatial distribution of the polymers and identification. Moreover, in order to investigate the influence of surface contamination, the ToF‐SIMS data before and after Ar cluster ion beam sputtering was compared. As a result, materials in the sample of multiple components, including unknown contaminants, were distinguished. Copyright © 2014 John Wiley & Sons, Ltd.     

Quantitative analysis of styrene‐pentafluorostyrene random copolymers by ToF‐SIMS and XPS

Poly(styrene) (PS), poly(2,3,4,5,6‐pentafluorostyrene) (5FPS) and their random copolymers were prepared by bulk radical polymerization. The spin‐cast polymer films of these polymers were analyzed using X‐ray photoelectron spectroscopy (XPS) and time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). The surface and bulk compositions of these copolymers were found to be same, implying that surface segregation did not occur. The detailed analysis of ToF‐SIMS spectra indicated that the ion fragmentation mechanism is similar for both PS and 5FPS. ToF‐SIMS quantitative analysis using absolute peak intensity showed that the SIMS intensities of positive styrene fragments, particularly C₇H₇⁺, in the copolymers are higher than the intensities expected from a linear combination of PS and 5FPS, while the SIMS intensities of positive pentafluorostyrene fragments are smaller than expected. These results indicated the presence of matrix effects in ion formation process. However, the quantitative approach using relative peak intensity showed that ion intensity ratios are linearly proportional to the copolymer mole ratio when the characteristic ions of PS and 5FPS are selected. This suggests that quantitative analysis is still possible in this copolymer system. Copyright © 2005 John Wiley & Sons, Ltd.     

Surface studies of halloysite nanotubes by XPS and ToF‐SIMS

This report provides detailed experimental results of thermal and surface characterization on untreated and surface‐treated halloysite nanotubes (HNTs) obtained from two geographic areas. Surface characterization techniques, including XPS and time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) were used. ToF‐SIMS surface analysis experiments were performed with both atomic and cluster ion beams. Higher ion yields and more high‐mass ions were obtained with the cluster ion beams. Static ToF‐SIMS spectra were analyzed with principal component analysis (PCA). Morphological diversities were observed in the samples although they mainly contained tubular structures. Thermogravimetric data indicated that aqueous hydrogen peroxide solution could remove inorganic salt impurities, such as alkali metal salts. The amount of grafting of benzalkonium chloride of HNT surface was determined by thermogravimetic analysis. PCA of ToF‐SIMS spectra could distinguish the samples mined from different geographical locations as well as among surface‐treated and untreated samples. Copyright © 2010 John Wiley & Sons, Ltd.     

Mitigating dead‐time effects during multivariate analysis of ToF‐SIMS spectral images

ToF‐SIMS spectra are formed by bombarding a surface with a pulse of primary ions and detecting the resultant ionized surface species using a time‐of‐flight mass spectrometer. Typically, the detector is a time‐to‐digital converter. Once an ion is detected using such detectors, the detector becomes insensitive to the arrival of additional ions for a period termed as the (detector) dead‐time. Under commonly used ToF‐SIMS data acquisition conditions, the time interval over which ions arising from a single chemical species reach the detector is on the order of the detector dead‐time. Thus, only the first ion reaching the detector at any given mass is counted. The event registered by the data acquisition system, then, is the arrival of one or more ions at the detector. This behavior causes ToF‐SIMS data to violate, in the general case, the assumption of linear additivity that underlies many multivariate statistical analysis techniques. In this article, we show that high‐mass‐resolution ToF‐SIMS spectral‐image data follow a generalized linear model, and we propose a data transformation and scaling procedure that enables such data sets to be successfully analyzed using standard methods of multivariate image analysis. Copyright © 2008 John Wiley & Sons, Ltd.     

Quantification and methodology issues in multivariate analysis of ToF‐SIMS data for mixed organic systems

Multivariate methods, such as principal component analysis (PCA) and multivariate curve resolution (MCR), are often employed to aid the analysis of large complex data sets such as time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) images. There is, however, much confusion over the most appropriate choice of method for any given application and the effects of data preprocessing, which is exacerbated by the confusing terminologies and the use of jargon in this field. In the present study, a simple model system consisting of a ToF‐SIMS image of an immiscible polymer blend is used to evaluate PCA and MCR in the accurate identification, localisation and quantification of the phase‐separated polymer domains, using four data preprocessing methods (no scaling, normalisation, variance scaling and Poisson scaling). This highlights significant issues and challenges in the quantitative multivariate analysis of mixed organic systems, including the discrimination of chemically significant features from experimental noise, the resolution of weak chemical contributions and potential bias introduced by data preprocessing. Multivariate analysis using Poisson scaling, identified as the most suitable data preprocessing method for both PCA and MCR, demonstrates a marked improvement upon traditional (manual) analysis and provides valuable additional information that is difficult to detect using traditional analysis. Using these results, we present recommendations for the optimum use of multivariate analysis by analysts and provide guidance on selecting the most appropriate methods. Confusing terminology is also clarified. © Crown copyright 2008. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd.     

An investigation of hydrogen depth profiling using ToF‐SIMS

Hydrogen depth distributions in silicon, zinc oxide, and glass are of great interest in material research and industry. Time‐of‐flight SIMS has been used for hydrogen depth profiling for many years. However, some critical information, such as optimal instrumental settings and detection limits, is not easily available from previous publications. In this work, optimal instrumental settings and detection limits of hydrogen in silicon, zinc oxide, and common glass were investigated. The recommended experimental settings for hydrogen depth profiling using time‐of‐flight SIMS are: (i) keeping pressure in the analysis chamber as low as possible, (ii) using a cesium beam for sputtering and monitoring the H^– signal, (iii) employing monatomic ion analysis beams with the highest currents, and (iv) using interlace mode. In addition, monatomic secondary ions from a matrix are recommended as references to normalize the H^– signal. Detection limits of hydrogen are limited by the pressure of residual gases in the analysis chamber. The base pressure of the analysis chamber (with samples) is about 7 × 10^?10 mbar in this study, and the corresponding detection limits of hydrogen in silicon, zinc oxide, and common glass are 1.3 × 10¹⁸ atoms/cm³, 1.8 × 10¹⁸ atoms/cm³, and 5.6 × 10¹⁸ atoms/cm³, respectively. Copyright © 2011 John Wiley & Sons, Ltd.     

ToF‐SIMS characterisation of methane‐ and hydrogen‐plasma‐modified graphite using principal component analysis

Time of flight secondary ion mass spectrometry (ToF‐SIMS) has been used to determine the extent of surface modification of highly ordered pyrolytic graphite (HOPG) samples that were exposed to radio‐frequency methane and hydrogen plasmas. The ToF‐SIMS measurements were examined with the multivariate method of principal component analysis (PCA), to maximise the amount of spectral information retained in the analysis. This revealed that the plasma (methane or hydrogen plasma) modified HOPG exhibited greater hydrogen content than the pristine HOPG. The hydrogen content trends observed from the ToF‐SIMS studies were also observed in elastic recoil detection analysis measurements. The application of the ToF‐SIMS PCA method also showed that small hydrocarbon fragments were sputtered from the hydrogen‐plasma‐treated sample, characteristic of the formation of a plasma‐damaged surface, whereas the methane‐plasma‐treated surface sputtered larger hydrocarbon fragments, which implies the growth of a polymer‐like coating. Scanning tunnelling microscopy measurements of the modified surfaces showed surface features that are attributable to either etching or film growth after exposure to the hydrogen or methane plasma. Copyright © 2009 John Wiley & Sons, Ltd.     

Cationisation of oligomeric alkylethoxylate surfactants in ToF‐SIMS analysis

Variable cationisation of the alkylethoxylate surfactant Synperonic A7^? has been observed during a ToF‐SIMS study of its interaction with a leaf surface, either by itself or as a component in a simple herbicide formulation. Depending on the conditions, cationisation predominantly by K⁺, Na⁺ and H⁺ was found. By deliberate surfactant solution doping with alkali bromides, the cationisation channel could be manipulated. Comparison of the apparent molecular weight dependence, derived from the ToF‐SIMS spectra, with that measured by HPLC‐MS, showed a further dependence on the cationising species, with Na⁺ giving the best match. An understanding of these effects is critical to the correct interpretation of the spectra from this surfactant. Copyright © 2007 John Wiley & Sons, Ltd.     

Peak‐fitting of high resolution ToF‐SIMS spectra: a preliminary study

Peak‐fitting has been performed on a series of peaks obtained by time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) analysis in order to assess whether information may be obtained from this procedure on the samples' characteristics. A variety of samples were examined including a range of treatments for aluminium leading to different surface roughnesses, polymer films with a range of polydispersities, molecular weight (MW) and thicknesses as well as aluminium samples with adsorbed adhesion promoters on the surface. Variation of peak‐fitting was assessed by varying the peak intensity, full width at half maximum (FWHM) and peak asymmetry. Although further studies are needed it is possible to say that the peak width increases with roughness whereas peak asymmetry seems to be related to oxide thickness. Polymer characteristics do not seem to influence the width whereas the peak asymmetry increases either versus MW or polydispersity. A possible assumption is that the peak asymmetry relates to the ion formation processes. Additional work with varying polymer films thickness indicates that both FWHM and peak asymmetry may be related to sample charging and this could be used for assessment of film thicknesses. Finally, peak‐fitting was used to obtain a more reliable peak area when peaks are too close in mass to use current methods. Copyright © 2009 John Wiley & Sons, Ltd.     

Investigation of Asian lacquer films using ToF‐SIMS and complementary analytical techniques

Lacquer has been used in Asian countries for thousands of years as a natural coating material owing to its durable, adhesive, decorative, and protective properties. Protection and restoration of lacquer‐coated cultural remains has become an important subject, and identification of the lacquer types in old lacquer‐wares has also become very important for conservation and restoration research. This paper provides identification of several molecular species of vegetal‐source Asian lacquers with the aim of providing a methodology for application in the field of cultural heritage. Several chemical markers of the vegetal species in Asian lacquers were identified using a methodology consistent with the sampling restrictions required for cultural‐heritage objects. Surface analytical methods such as time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS), X‐ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy were used to characterize Korean, Chinese, and Vietnamese lacquers; avoiding time‐consuming and destructive extraction processes. These ToF‐SIMS results provided the structural characterization of a series of catechol derivatives. The ToF‐SIMS spectra of Rhus vernicifera from Korea and China, and Rhus succedanea from Vietnam indicated a series of urushiol and laccol repeat units, respectively, in the mass range of m/z 0–1800. Because of its sensitivity, specificity, and speed of analysis, the ToF‐SIMS technique can be used to investigate cultural lacquer‐coated treasures as well as to discriminate among different Asian lacquer coatings or binding mediums for the conservation or restoration of lacquer‐ware. Copyright © 2016 John Wiley & Sons, Ltd.     

Development of an automated in situ fracture stage for a ToF‐SIMS system

The design philosophy and implementation of an ultra high vacuum (UHV), PC controlled, automated in situ fracture stage for a surface analysis system is described. ToF‐SIMS spectra are shown to illustrate the improvement in spectral quality obtained from micro‐compact tension (CT) tests of polymer matrix fracture surfaces produced using the fracture stage in UHV compared to those obtained from a sample tested at air. This system is flexible in that by changing the capacity of the load cell it is possible to reduce or increase maximum loads as the specimen type and material demands. The stage has been designed with instrumental flexibility in mind, utilising commercial SEM‐stub type sample mounts, and can thus be used for AES/SAM and XPS investigations, as well as ToF‐SIMS analysis, in the authors' laboratory. Copyright © 2008 John Wiley & Sons, Ltd.     

Investigation of ionic liquids under Bi‐ion and Bi‐cluster ions bombardment by ToF‐SIMS

A systematic study of five different imidazolium‐based room temperature ionic liquids, 1‐butyl‐3‐methylimidazolium acetate, 1‐butyl‐3‐methylimidazolium nitrate, 1‐butyl‐3‐methylimidazolium iodide, 1‐butyl‐3‐methylimidazolium hexafluorophosphate and 1‐butyl‐3‐methylimidazolium bis(trifluoromethylsulfonyl)imide were carried out by means of time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) in positive and negative ion mode. The compounds were measured under Bi‐ion and Bi‐cluster ions (Bi_2–7⁺, Bi_{3, 5}²⁺) bombardment, and spectral information and general rules for the fragmentation pattern are presented. Evidence for hydrogen bonding, due to high molecular secondary cluster ions, could be found. Hydrogen bonding strength could be estimated by ToF‐SIMS via correlation of the anionic yield enhancement with solvent parameters. Copyright © 2010 John Wiley & Sons, Ltd.     

Identifying and minimizing buffer interferences in ToF‐SIMS analyses of lignocellulose

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) has demonstrated applicability to the analysis of lignocellulosic samples including pulp, paper, plants, and wood. One such application is to use ToF‐SIMS as a tool for detecting the activity of enzymes applied to degrade or modify plant biomass. The use of buffers for pH control of these enzymatic reactions can pose problems due to the nature of the ToF‐SIMS measurement. Specifically, inorganic species (e.g. salts) from buffer components could introduce several concerns for quantitative or semi‐quantitative ToF‐SIMS analysis. First, salts can produce additional peaks in the mass spectra, which may overlap with lignocellulose peaks of interest (mass interference). Second, salts can alter the chemical environment, or ‘matrix’, altering the ionization probability of lignocellulose‐related secondary ions during the sputtering mechanism of the ToF‐SIMS measurement (matrix effects). Third, salts may physically coat the lignocellulose surface, decreasing the signal from the lignocellulose, causing poor signal‐to‐noise in the analysis. The current work presents a simple approach for identifying interferences due to buffers, using both principal component analysis (PCA) and previously established lignocellulose‐relevant peak ratios. Furthermore, a simple acetic acid rinsing protocol is compared to distilled water rinsing and is evaluated and for its effectiveness in removing buffer‐related salts. The data shows that briefly rinsing lignocellulose samples in dilute acetic acid can be effective in restoring the validity of lignocellulose composition interpretations using ToF‐SIMS. Copyright © 2014 John Wiley & Sons, Ltd.     

Characterization of size‐segregated aerosols using ToF‐SIMS imaging and depth profiling

Size‐segregated particles were collected with a ten‐stage micro‐orifice uniform deposit impactor from a busy walkway in a downtown area of Hong Kong. The surface chemical compositions of aerosol samples from each stage were analyzed using time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) operated in the static mode. The ToF‐SIMS spectra of particles from stage 2 (5.6–10 µm), stage 6 (0.56–1 µm), and stage 10 (0.056–0.1 µm) were compared, and the positive ion spectra from stage 2 to stage 10 were analyzed with principal component analysis (PCA). Both spectral analysis and PCA results show that the coarse‐mode particles were associated with inorganic ions, while the fine particles were associated with organic ions. PCA results further show that the particle surface compositions were size dependent. Particles from the same mode exhibited more similar surface features. Particles from stage 2 (5.6–10 µm), stage 6 (0.56–1 µm), and stage 10 (0.056–0.1 µm) were further selected as representatives of the three modes, and the chemical compositions of these modes of particles were examined using ToF‐SIMS imaging and depth profiling. The results reveal a non‐uniform chemical distribution from the outer to the inner layer of the particles. The coarse‐mode particles were shown to contain inorganic salts beneath the organics surface. The accumulation‐mode particles contained sulfate, nitrate, ammonium salts, and silicate in the regions below a thick surface layer of organic species. The nucleation‐mode particles consisted mainly of soot particles with a surface coated with sulfate, hydrocarbons, and, possibly, fullerenic carbon. The study demonstrated the capability of ToF‐SIMS depth profiling and imaging in characterizing both the surface and the region beneath the surface of aerosol particles. It also revealed the complex heterogeneity of chemical composition in size and depth distributions of atmospheric particles. Copyright © 2014 John Wiley & Sons, Ltd.     

XPS and ToF‐SIMS characterization of a Finemet surface: effect of cooling

The surface composition of amorphous Finemet, Fe₇₃Si_15.8B_7.2Cu₁Nb₃, was studied by X‐ray photoelectron spectroscopy (XPS) and time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). The as‐received sample in the original state and after Ar⁺ sputter‐cleaning was analyzed at room temperature as well as after cooling to ? 155 °C. In the cooled state, the surface oxide layer composed of oxides of the alloy constituents was found to become enriched with elemental iron and depleted of elemental silicon, boron, oxygen and carbon as compared to the state at room temperature. Interaction of residual water vapor and hydrogen with the complex oxide layer occurring at low temperatures is believed to be responsible for the enhanced formation of surface hydroxides of the alloy constituents. The processes resulting in the observed redistribution of the elements on the surface of Finemet at low temperatures are discussed. Copyright © 2006 John Wiley & Sons, Ltd.