Retracted: Mass analysis by Ar‐GCIB‐dynamic SIMS for organic materials

Generally, dynamic secondary ion mass spectrometry (SIMS) has been mainly used as one of the most powerful tools for inorganic mass analysis. On the other hand, an Ar gas cluster ion beam (GCIB) has been developed and spread as a processing tool for surface flattening and also a projectile for time‐of‐flight (ToF) SIMS. In this study, we newly introduced an Ar‐GCIB as a primary ion source to a commercially available dynamic SIMS apparatus, and investigated mass spectra of amino acid films (such as Arginine and Glycine) and polymer films (Polyethylene: PE and Polypropylene: PP) as organic model samples. As a result, each characteristic fragment peak indicating the original molecular organic structure was observed in the acquired mass spectra. In addition, their own molecular ions of the amino acids were also clearly observed. Mass spectra of PE/PP blended‐polymer films acquired using Ar‐GCIB‐dynamic SIMS could be identified between pure PE and PE:PP = 1:3 mixture by applying principal component analysis (PCA).     

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.     

Fluorine plasma treatment of bare and nitrilotris(methylene)triphosphonic acid (NP) protected aluminum: an XPS and ToF‐SIMS study

Nitrilotris(methylene)triphosphonic acid (NP) is a technologically important molecule that has been used for years as a corrosion inhibitor and/or adhesion promoter on aluminum and other metal surfaces. However, to the best of our knowledge, the detailed surface characterization of NP adsorbed on aluminum, or on any other surface, has not been reported. Herein, we report an X‐ray photoelectron spectroscopy and time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) analysis of a series of untreated and NP‐coated aluminum substrates that were exposed to the downstream products of a fluoroalkane + oxygen plasma for different amounts of time (from 0 to 20 s). As indicated by P 2p, N 1s, Al 2p, O 1s, and F 1s narrow scans, even a 4‐s plasma treatment significantly damages the NP protective layer and converts the native aluminum oxide into aluminum oxyfluoride. Heat treatment of the fluorine plasma‐treated samples in the air substantially converts the aluminum oxyfluoride back to aluminum oxide, while similar heating under vacuum results in little change to the materials. A slow loss of fluorine from the samples occurs over the course of weeks when they are stored in the air. A ToF‐SIMS analysis reveals sets of signals that are consistent with no surface treatment, NP treatment, or fluorine plasma treatment. A principal component analysis of the negative ion ToF‐SIMS spectra from the samples shows the expected differentiation of the samples. Copyright © 2014 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.     

Differentiating diterpene resin acids using ToF‐SIMS and principal component analysis: new tools for assessing the geochemistry of amber

Amber is a polymerized plant resin having remarkable preservation potential in the geological record. Numerous analytical techniques have been applied to the study of amber organic chemistry in order to extract paleobotanical information. However, only exploratory work has been conducted using time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS), despite its immense potential due to the high mass resolution and range that can be analyzed concurrently. Detailed assessments of ion fragmentation patterns are prerequisite, given that amber is comprised of a challenging range of terpenoids, carboxylic acids, alcohols, and associated esters. In recent work, we demonstrated the applicability and efficiency of ToF‐SIMS as a tool to investigate amber chemical composition. However, only two diterpene resin acid standards were considered in this preliminary study, namely abietic acid and communic acid. We now extend this work by documenting the ToF‐SIMS spectra of ten additional diterpene resin acids and ask whether ToF‐SIMS analysis can distinguish subtle differences within a larger set of diterpenoids. Both positive and negative ToF‐SIMS spectra were produced, although negative polarity appears particularly promising for differentiating diterpene resin acids. Principal component analysis (PCA) was used to distill the data and verified that purified diterpenes have distinct ToF‐SIMS spectra that can be applied to amber chemotaxonomy as well as to the analysis of modern resins of known botanical origin. While this work is pertinent to the study of the composition and histories of ambers, the mass spectra of the 12 diterpene standards could prove valuable to any system where diterpenoid chemistry plays a role. Copyright © 2014 John Wiley & Sons, Ltd.     

How does soaking wood in various pH buffers impact ToF‐SIMS spectra?

During the production of biofuels and/or bioproducts, wood and other lignocellulosic materials are frequently exposed to buffers during enzyme treatments. Buffer pH varies according to the activity profiles of the enzyme(s) used. Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) is an increasingly valuable analytical tool for the surface analysis of lignocellulosic solids, allowing for characterization of the lignin and polysaccharides at the surface, along with other components such as protein and inorganic salts. Despite the use of ToF‐SIMS to characterize dilute acid and alkali pretreatments of wood, the exposure of wood to buffers of intermediate pH range has not been studied as it relates to ToF‐SIMS analysis. This leads to the question: “How does soaking wood in various pH buffers impact ToF‐SIMS spectra?” Accordingly, a softwood (spruce) and hardwood (birch) were soaked in universal buffers ranging from pH 5 to 10, and then positive ion ToF‐SIMS spectra were acquired from the washed wood. Deacetylation was evident for both wood species above pH 8. Additionally, at higher pH, birch ToF‐SIMS spectra revealed a relative loss in polysaccharide peaks attributed to hemicellulose and an increase in lignin peaks. This study provides a basis for understanding the pH‐dependent alteration of wood solids in aqueous solution, which is important for understanding the controls in enzyme treatments.     

ToF‐SIMS characterization of glyoxal surface oxidation products by hydrogen peroxide: A comparison between dry and liquid samples

As one of the simplest volatile organic compounds, glyoxal and its oxidation products were considered to be important precursors to aqueous secondary organic aerosol formation. Herein, we analyzed products from glyoxal oxidation by hydrogen peroxide in dry and liquid samples using time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). ToF‐SIMS spectra and spectral principal component analysis (PCA) were used to investigate surface oxidation products. Dry samples were prepared on clean silicon wafers. Liquid samples consisting of glyoxal and hydrogen peroxide (H₂O₂) were introduced to a vacuum compatible microfluidic reactor prior to UV illumination or dark aging followed by in situ liquid SIMS analysis. A number of reaction products were observed in both dry and liquid samples; different oligomers and carboxylic acids could be formed depending on reaction conditions. In addition, hydrolyzed products were observed in the liquid samples, but not in the dry samples. Although dry samples reveal some products of the aqueous process, they are not fully representative as results from those of the aqueous samples. Our findings suggest that the ability to characterize the liquid surface reaction products provides more realistic information of the reaction products associated with aqueous secondary organic aerosol formation in the atmosphere. Meanwhile, the high mass resolution spectra from the dry sample SIMS measurement are helpful to identify oxidation products in the liquid samples.     

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.     

ToF‐SIMS multivariate characterization of surface modification of polymers by N2?H2 atmospheric pressure dielectric barrier discharge

Time of flight secondary ion mass spectrometry (ToF‐SIMS) is a powerful tool for the surface characterization of plasma‐modified surface. However, the SIMS fragmentation patterns of the resulting surface are quite complex and a full interpretation may be prohibitive. As a result, many studies are turning to multivariate statistical methods to simplify the interpretation. In this study, a principal component analysis (PCA) was used to obtain a more detailed interpretation of the surface modification of polymers by an atmospheric pressure plasma. The dataset was obtained from three polymers with different chemical compositions [namely, polyethylene, polyvinylidene fluoride, and poly(tetrafluoroethylene)], where each material was treated with an atmospheric pressure dielectric barrier discharge (DBD) in an atmosphere composed of different N₂/H₂ ratios. The results are discussed in terms of the suitability of ToF‐SIMS analysis combined with PCA for the discrimination between the three polymers and the possibility to create a predictive model that would describe the plasma surface modification, independent of the polymer substrate chemical composition. Copyright © 2010 John Wiley & Sons, Ltd.     

Surface properties of polypropylene following a novel industrial surface‐treatment process

Polypropylene (PP) is used in many automotive applications where good paint adhesion is of primary importance. PP is widely known for its low surface energy which impacts negatively on its adhesion strength. PP surfaces were modified using a new industrial surface‐treatment process known as the Accelerated Thermo‐molecular adhesion Process (ATmaP). ATmaP grafts functional groups to the polymer surface derived from an atomised and vapourised nitrogen‐containing coupling agent. The surface properties and adhesion performance of PP samples treated using the ATmaP process and two different flame processes were compared using XPS, time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) and mechanical testing (pull‐up tests). The latter showed that ATmaP improved adhesion strength significantly in comparison with conventional flame treatments. XPS showed an increase in oxygen and nitrogen concentration on the surface of ATmaP‐treated samples compared with untreated and flame‐treated samples. Principal components analysis (PCA) of the ToF‐SIMS data revealed the major phenomena occurring during the surface treatment of PP samples. Early stage events, including the chain scission of the PP backbone chain and the subsequent reaction of these chains with the surrounding air, are captured by the first principal component (PC1). The increase in the concentration of NO surface functional groups resulting from ATmaP treatment is captured by the second principal component (PC2). Copyright © 2008 John Wiley & Sons, Ltd.     

Hidden information in principal component analysis of ToF‐SIMS data: On the use of correlation loadings for the identification of significant signals and structure elucidation

In this paper, an improved approach to interpret results of principal component analysis (PCA) of time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) spectra is presented. Signals are typically observed in different intensity ranges in a single ToF‐SIMS spectrum due to different sensitivity factors and surface concentrations. This can complicate the PCA interpretation, because loadings are reported to be strongly affected by these intensity changes. In contrast, it is shown here that correlation loadings are unaffected by these differences. In particular, correlation loadings were successfully used to identify signals with relatively low intensity but high significance. These signals may be overlooked when only loadings are used. This is particularly true in failure analysis, where ToF‐SIMS is used to screen for initially unknown signals that may be relevant for the characteristics/failure of a product. As a model study, the concept was applied to investigate ageing of Li‐ion batteries by ToF‐SIMS. In this data set, the significance of impurities that affect the quality of Li‐ion batteries was identified only by correlation loadings, whereas the loadings were found to overestimate the influence of other matrix signals. In addition, correlation loadings aid in the chemical identification and helped to successfully assign unknown peaks.     

Spectral characterisation of eight glycerolipids and their detection in natural samples using time‐of‐flight secondary ion mass spectrometry

In recent years, time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) with cluster ion sources has opened new perspectives for the analysis of lipid biomarkers in geobiology and organic geochemistry. However, published ToF‐SIMS reference spectra of relevant compounds are still sparse, and the influence of the chemical environment (matrix) on the ionisation of molecules and their fragmentation is still not well explored. This study presents ToF‐SIMS spectra of eight glycerolipids as common target compounds in biomarker studies, namely ester‐ and ether‐bound phosphatidylethanolamine, ester‐ and ether‐bound phosphatidylcholine, ester‐bound phosphatidylglycerol, ester‐ and ether‐bound diglycerides and archaeol, obtained with a Bi cluster ion source. For all of these compounds, the spectra obtained in positive and negative analytical modes showed characteristic fragments that could clearly be assigned to e.g. molecular ions, functional groups and alkyl chains. By comparison with the reference spectra, it was possible to track some of these lipids in a pre‐characterised organic extract and in cryosections of microbial mats. The results highlight the potential of ToF‐SIMS for the laterally resolved analysis of organic biomarkers in environmental materials. The identification of the target compounds, however, may be hampered by matrix effects (e.g. adduct formation) and often require careful consideration of all spectral features and taking advantage of the molecular imaging capability of ToF‐SIMS. Copyright © 2009 John Wiley & Sons, Ltd.     

ToF‐SIMS analysis of a polymer microarray composed of poly(meth)acrylates with C6 derivative pendant groups

Surface analysis plays a key role in understanding the function of materials, particularly in biological environments. Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) provides highly surface sensitive chemical information that can readily be acquired over large areas and has, thus, become an important surface analysis tool. However, the information‐rich nature of ToF‐SIMS complicates the interpretation and comparison of spectra, particularly in cases where multicomponent samples are being assessed. In this study, a method is presented to assess the chemical variance across 16 poly(meth)acrylates. Materials are selected to contain C₆ pendant groups, and ten replicates of each are printed as a polymer microarray. SIMS spectra are acquired for each material with the most intense and unique ions assessed for each material to identify the predominant and distinctive fragmentation pathways within the materials studied. Differentiating acrylate/methacrylate pairs is readily achieved using secondary ions derived from both the polymer backbone and pendant groups. Principal component analysis (PCA) is performed on the SIMS spectra of the 16 polymers, whereby the resulting principal components are able to distinguish phenyl from benzyl groups, mono‐functional from multi‐functional monomers and acrylates from methacrylates. The principal components are applied to copolymer series to assess the predictive capabilities of the PCA. Beyond being able to predict the copolymer ratio, in some cases, the SIMS analysis is able to provide insight into the molecular sequence of a copolymer. The insight gained in this study will be beneficial for developing structure–function relationships based upon ToF‐SIMS data of polymer libraries. © 2016 The Authors Surface and Interface Analysis Published by John Wiley & Sons Ltd.     

ToF‐SIMS for the characterization of hyperbranched aliphatic polyesters: probing their molecular weight on surfaces based on principal component analysis (PCA)

A series of 2,2‐bis(hydroxymethyl)propionic acid (Bis‐MPA) hyperbranched aliphatic polyesters with different molecular weights (generations) is analysed for the first time by time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). The main negative and positive low‐mass fragments are identified in the fingerprint part of the spectra (m/z < 400) and are principally assigned to fragmentation of the Bis‐MPA repeating units. In addition, it is shown that the fragmentation pattern is highly affected by the functional end‐groups. This is illustrated for a phthalic acid end‐capped hyperbranched polymer and for an acetonide‐terminated dendrimer analog. Also, typical fragments assigned to the ethoxylated pentaerythritol core molecule are detected. These ions show decreasing intensities with increasing molecular weight. This intensity dependency on the generation is used to calibrate the molecular weight of hyperbranched polyesters on the surface. To obtain quantitative information, a principal component analysis (PCA) multivariate statistical method is applied to the ToF‐SIMS data. The influence of different normalization procedures prior to PCA calculation is tested, e.g. normalization to the total intensity, to the intensities of ions assigned to the Bis‐MPA repeating unit or to intensities of fragments due to the core molecule. It is shown that only one principal component (PC1) is needed to describe most of the variance between the samples. In addition, PC1 takes into account the generation effect. However, different relationships between the PC1 scores and the hyperbranched mass average molecular weights are observed depending on the normalization procedure used. Normalization of data set ion intensities by ion intensities from the core molecule allows linearization of the SIMS intensities versus the molecular weight and allows the hyperbranched polymers to be discriminated up to the highest generations. In addition, PCA applied to ToF‐SIMS data provides an extended interpretation of the spectra leading to further identification of the correlated mass peaks, such as those of the Bis‐MPA repeating unit (terminal, dendritic and linear) and those of the core molecule. Finally, the work presented demonstrates the extreme potential of the static ToF‐SIMS and PCA techniques in the analysis of dendritic molecules on solid surfaces. Copyright © 2003 John Wiley & Sons, Ltd.     

Denoising and multivariate analysis of time‐of‐flight SIMS images

Time‐of‐flight SIMS (ToF‐SIMS) imaging offers a modality for simultaneously visualizing the spatial distribution of different surface species. However, the utility of ToF‐SIMS datasets may be limited by their large size, degraded mass resolution and low ion counts per pixel. Through denoising and multivariate image analysis, regions of similar chemistries may be differentiated more readily in ToF‐SIMS image data. Three established denoising algorithms—down‐binning, boxcar and wavelet filtering—were applied to ToF‐SIMS images of different surface geometries and chemistries. The effect of these filters on the performance of principal component analysis (PCA) was evaluated in terms of the capture of important chemical image features in the principal component score images, the quality of the principal component score images and the ability of the principal components to explain the chemistries responsible for the image contrast. All filtering methods were found to improve the performance of PCA for all image datasets studied by improving capture of image features and producing principal component score images of higher quality than the unfiltered ion images. The loadings for filtered and unfiltered PCA models described the regions of chemical contrast by identifying peaks defining the regions of different surface chemistry. Down‐binning the images to increase pixel size and signal was the most effective technique to improve PCA performance. Copyright © 2003 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.     

Effects of Ar‐ and Ar/O2‐plasma‐treated amorphous and crystalline polymer surfaces revealed by ToF‐SIMS and principal component analysis

The effects of argon (Ar) and a mixture of Ar and oxgyen(Ar/O₂) plasmas on amorphous and semi‐crystalline poly(bisphenol A hexane ether) thin films were investigated by time‐of‐flight secondary ion mass spectroscopy (ToF‐SIMS) and principal component analysis (PCA). PCA results of the ToF‐SIMS spectra indicate that an Ar/O₂ plasma produced less physical sputtering and had a higher chemical reactivity than did an Ar plasma, regardless of whether an amorphous or a crystalline surface was involved. However, the chemical differences between the Ar‐ and Ar/O₂‐plasma‐treated semi‐crystalline films were much smaller. The observed results can be explained by the higher resistance of the polymer crystalline regions to physical sputtering and chemical etching. Copyright © 2013 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.     

ToF‐SIMS study of 1‐dodecanethiol adsorption on Au,Ag, Cu and Pt surfaces

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) has been used to perform a chemical analysis of long‐chain thiol (CH₃(CH₂)₁₁SH)‐treated gold, silver, copper and platinum surfaces. All the mass peaks from positive and negative ion spectra within the range m/z = 0–2000 u are studied. ToF‐SIMS data revealed that on gold, silver and copper substrates 1‐dodecanethiol form dense standing‐up phases, but on platinum being a catalytically active substrate, we were able to identify also surface‐aligned parallel lying molecules in addition to a standing thiolate layer. Our study shows that when ToF‐SIMS spectra are analyzed, not only the existence of oligomers but also metal + hydrocarbon fragments give information about the order of SAM. Copyright © 2008 John Wiley & Sons, Ltd.     

Analysis of the surface chemistry of oxidized polyethylene: comparison of XPS and ToF‐SIMS

A series of low‐density polyethylene (LDPE) surfaces, chemically modified using a number of oxidative techniques employed for adhesion enhancement (pretreatments), have been studied by time‐of‐flight (ToF) SIMS and XPS. The methods consisted of corona discharge, flame, electrochemical, chromic acid, acid dichromate and acid permanganate treatment. All except flame treatment were performed under mild and fairly severe conditions to yield a range of surface chemistries. The XPS analysis, using high energy resolution and a refined approach to C 1s curve‐fitting, provided some new insights into the quantitative assessment of the type and concentration of functional groups. Both positive and negative ion ToF‐SIMS spectra were obtained at high mass resolution. The oxygen‐containing fragments were identified by accurate mass analysis and subjected to a detailed comparison with the XPS results. No convincing relative intensity correlations could be identified that would allow particular secondary ion fragments to be associated strongly with particular functional groups (in this multi‐functional surface situation). Inorganic residues resulting from wet chemical treatments were also investigated and here the two techniques were found to be more complementary. Copyright © 2003 John Wiley & Sons, Ltd.