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.     

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.     

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.     

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.     

Thermal degradation mechanism of poly(arylene sulfone)s by stepwise Py‐GC/MS

The thermal degradation of poly(ether sulfone) (PES) and polysulfone (PSF) was studied with a combination of thermogravimetric analysis and stepwise pyrolysis–gas chromatography/mass spectrometry techniques with consecutive heating of the samples at fixed temperature intervals (100 °C) to achieve narrow‐temperature pyrolysis conditions. The individual mass chromatograms of various pyrolysates were correlated with pyrolysis temperatures to elucidate the pyrolysis mechanism. The major mechanism for both PES and PSF was a one‐stage pyrolysis involving main‐chain random scission and carbonization. The major products SO₂ and phenol were released from the sulfone and ether groups in PES. The major products SO₂, phenol, and 1‐methyl‐4‐phenoxybenzene were released from the sulfone, ether, and isopropylene groups in PSF. In the PES, the thermal stability of the sulfone and ether groups was identical to the maximum thermogravimetric loss rate. In the PSF, the thermal stability was in the following order: sulfone < ether < isopropylene. The temperature of the maximum thermogravimetric loss rate was similar to the maximum evolution of phenol. However, there was a considerable difference in the thermal behavior of both polymers; the correlation of the polymer structure to the degradation mechanism is discussed. © 2000 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 38: 583–593, 2000     

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.     

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.     

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.     

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.     

Molecular ME‐ToF‐SIMS yield as a function of DHB matrix layer thicknesses obtained from brain sections coated by sublimation/deposition techniques

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) can be used to image biological samples with nanometer‐scale resolution, albeit with the drawback that it often cannot detect large molecular signals. One way to increase secondary ion molecular yield is to chemically modify the surface in the so‐called matrix‐enhanced SIMS (ME‐SIMS) approach, which is based on embedding analyte molecules in low‐weight organic matrices. In this study, a solvent‐free sample preparation technique was employed using sublimation/deposition for coating a mouse brain section with a thin layer of a 2,5‐dihydroxybenzoic acid (DHB) matrix. Using this preparation technique, signal enhancements of up to a factor of 18 could be detected. It was found that the matrix layer thickness plays an important role in the efficiency of yield enhancement. Also, a complex influence of the matrix layer on various signals was observed. Copyright © 2015 John Wiley & Sons, Ltd.     

Multivariate statistical analysis of non‐mass‐selected ToF‐SIMS data

Cluster LMIGs are now regarded as the standard primary ion guns on time‐of‐flight secondary ion mass spectrometers (ToF‐SIMS). The ToF‐SIMS analyst typically selects a bombarding species (cluster size and charge) to be used for material analysis. Using standard data collection protocols where the analyst uses only a single primary bombarding species, only a fraction of the ion‐beam current generated by the LMIG is used. In this work, we demonstrate for the first time that it is possible to perform ToF‐SIMS analysis when all of the primary ion intensity (clusters) are used; we refer to this new data analysis mode as non‐mass‐selected (NMS) analysis. Since each of the bombarding species has a different mass‐to‐charge ratio, they strike the sample at different times, and as a result, each of the bombarding species generates a spectrum. The resulting NMS ToF‐SIMS spectrum contains contributions from each of the bombarding species that are shifted in time. NMS spectra are incredibly complicated and would be difficult, if not impossible, to analyze using univariate methodology. We will demonstrate that automated multivariate statistical analysis (MVSA) tools are capable of rapidly converting the complicated NMS data sets into a handful of chemical components (represented by both spectra and images) that are easier to interpret since each component spectrum represents a unique and simpler chemistry. Copyright © 2008 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.     

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.     

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.     

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.     

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.     

Subsurface investigation of the surface modification of polydimethylsiloxane by 172‐nm vacuum ultraviolet irradiation using ToF‐SIMS and VUV spectrometry

We investigate the mechanism of polydimethylsiloxane (PDMS) surface modification by 172‐nm vacuum ultraviolet (VUV) light. Time‐of‐flight secondary ion mass spectrometry and optical spectrometry are used to measure the chemical composition and VUV transmittance of the PDMS before and after surface modification, respectively. For modified samples of bulk PDMS, the VUV transmittance and the depth of the modified region increased with increasing VUV dose. This can be explained by the following self‐reinforcing cycle of (1) modification of PDMS by VUV light to a more silica‐like composition, (2) improvement of the VUV light transparency, and (3) deeper modification. For thin‐film samples of PDMS formed on sapphire substrates, the transmittance at 172 nm also increased with increasing VUV dose and exceeded that of sapphire in the region from 172 to 300 nm. Finally, thin‐film samples of PDMS formed on silicon substrates, which function as a VUV reflector, were also investigated. For these samples, the secondary ion depth profiles for several chemical species in the PDMS were oscillatory, probably due to the interference of the incident and reflected VUV light. These results strongly suggest that the photon energy of the VUV light plays an important role in modifying PDMS.     

The characteristic fragment ions and visualization of cationic starches on pulp fiber using ToF‐SIMS

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) was used to investigate the distribution of cationic starch on pulp fiber. To identify the characteristic fragment ions of the cationic starches, deuterium‐labeled cationic starches were prepared and analyzed using ToF‐SIMS. The starch 2‐hydroxypropyltrimethylammonium chloride derivative generated characteristic fragments at m/z 58 and 59, which were identified as [H₂C?N(CH₃)₂]⁺ and [N(CH₃)₃]^+·, respectively. The fragmentation patterns were also suggested. From the imaging analysis, the adsorption of the cationic starch on fibers was uneven on individual fibers, as well as between fibers. This may have been on account of fiber morphology and structure. On examining scanning electron microscope (SEM) images, the quaternary ammonium starch derivative (QS) did not penetrate the fiber. No migration of cationic starch was observed under various drying conditions. Copyright © 2007 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.