Patterning of Hydrophilic and Hydrophobic Gold and Magnetite Nanoparticles by Dip Pen Nanolithography.

Nanoparticles offer unique physical and chemical properties. Dip pen nanolithography of nanoparticles enables versatile patterning and nanofabrication with potential application in electronics and sensing, but is not well studied yet. Herein, the patterned deposition of various nanoparticles onto unmodified silicon substrates is presented. It is shown that aqueous solutions of hydrophilic citrate and cyclodextrin functionalized gold nanoparticles as well as poly(acrylic) acid decorated magnetite nanoparticles are feasible for writing nanostructures. Both smaller and larger nanoparticles can be patterned. Hydrophobic oleylamine or n-dodecylamine capped gold nanoparticles and oleic acid decorated magnetite nanoparticles are deposited from toluene. Tip loading is carried out by dip-coating, and writing succeeds fast within 0.1 s. Also, coating with longer tip dwell times, at different relative humidity and varying frequency are studied for deposition of nanoparticle clusters. The resulting feature size is between 300 and 1780 nm as determined by scanning electron microscopy. Atomic force microscopy confirms that the heights of the deposited structures correspond to a single or double layer of nanoparticles. Higher writing speeds lead to smaller line thicknesses, offering possibilities to more complex structures. Dip pen nanolithography can hence be used to pattern nanoparticles on silicon substrates independent of the surface chemistry.

Surface Modification of ITO with N-Heterocyclic Carbene Precursors Results in Electron Selective Contacts in Organic Photovoltaic Devices.

Surface modification of indium tin oxide (ITO) electrodes with organic molecules is known to tune their work function which results in higher charge carrier selectivity in corresponding organic electronic devices and hence influences the performance of organic solar cells. In recent years, N-heterocyclic carbenes (NHCs) have also been proven to be capable to modify the work function of metals and semimetals compared to the unfunctionalized surface via the formation of strong covalent bonds. In this report, we have designed and performed the modification of the ITO surface with NHC by using the zwitterionic bench stable IPr-CO2 as the NHC precursor, applied via spin coating. Upon modification, the work function of ITO electrodes was reduced significantly which resulted in electron selective contacts in corresponding organic photovoltaic devices. In addition, various characterization techniques and analytical methods are used to elucidate the nature of the bound species and the corresponding binding mechanism of the material to the ITO surface.

Label-free sub-micrometer 3D imaging of ciprofloxacin in native-state biofilms with cryo-time-of-flight secondary ion mass spectrometry.

High spatial resolution mass spectrometry imaging has been identified as a key technology needed to improve understanding of the chemical components that influence antibiotic resistance within biofilms, which are communities of micro-organisms that grow attached to a surface. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) offers the unique ability for label-free 3D imaging of organic molecules with sub-micrometer spatial resolution and high sensitivity. Several studies of biofilms have been done with the help of ToF-SIMS, but none of those studies have shown 3D imaging of antibiotics in native-state hydrated biofilms with cell-level resolution. Because ToF-SIMS measurements must be performed in a high-vacuum environment, cryogenic preparation and analysis are necessary to preserve the native biofilm structure and antibiotic spatial distribution during ToF-SIMS measurements. In this study, we have investigated the penetration of the antibiotic ciprofloxacin into Bacillus subtilis biofilms using sub-micrometer resolution 3D imaging cryo-ToF-SIMS. B. subtilis biofilms were exposed to physiologically relevant levels of ciprofloxacin. The treated biofilms were then plunge-frozen in liquid propane and analyzed with ToF-SIMS under cryogenic conditions. Multivariate analysis techniques, including multivariate curve resolution (MCR) and inverse maximum signal factor (iMSF) denoising, were used to aid analysis of the data and facilitate high spatial resolution 3D imaging of the biofilm, providing individually resolved cells and spatially resolved ciprofloxacin intensity at "real world" concentrations.

Denoising of Mass Spectrometry Images via Inverse Maximum Signal Factors Analysis.

Improving signal-to-noise and, thereby, image contrast is one of the key challenges needed to expand the useful applications of mass spectrometry imaging (MSI). Both instrumental and data analysis approaches are of importance. Univariate denoising techniques have been used to improve contrast in MSI images with varying levels of success. Additionally, various multivariate analysis (MVA) methods have proven to be effective for improving image contrast. However, the distribution of important but low intensity ions can be obscured in the MVA analysis, leading to a loss of chemically specific information. In this work we propose inverse maximum signal factors (MSF) denoising as an alternative approach to both denoising and multivariate analysis for MSI imaging. This approach differs from the standard MVA techniques in that the output is denoised images for each original mass peak rather than the frequently difficult to interpret scores and loadings. Five tests have been developed to optimize and validate the resulting denoised images. The algorithm has been tested on a range of simulated data with different levels of noise, correlated noise, varying numbers of underlying components, and nonlinear effects. In the simulations, an excellent correlation between the true images and the denoised images was observed for peaks with an original signal-to-noise ratio as low as 0.1, as long as there was sufficient intensity in the sum of the selected peaks. The power of the approach was then demonstrated on two time-of-flight secondary ion mass spectrometry (ToF-SIMS) images that contained largely uncorrelated noise and a laser post-ionization matrix-assisted laser desorption/ionization mass spectrometry (MALDI-2-MS) image that contained strongly correlated noise. The improvements in signal-to-noise increased with decreasing intensity of the original peaks. A signal-to-noise improvement of as much as two orders of magnitude was achieved for very low intensity peaks. MSF denoising is a powerful addition to the suite of image processing techniques available for studying mass spectrometry images.

Versatile Surface Patterning with Low Molecular Weight Photoswitches.

Surface patterning of functional materials is a key technology in various fields such as microelectronics, optics, and photonics. In micro- and nanofabrication, polymers are frequently employed either as photoreactive or thermoresponsive resists that enable further fabrication steps, or as functional adlayers in electronic and optical devices. In this article, a method is presented for imprint lithography using low molecular weight arylazoisoxazoles photoswitches instead of polymer resists. These photoswitches exhibit a rapid and reversible solid-to-liquid phase transition upon photo-isomerization at room temperature, making them highly suitable for reversible surface functionalization at ambient conditions. Beyond photo-induced imprint lithography with multiple write-and-erase cycles, prospective applications as patterned matrix for nanoparticles and etch resist on gold surfaces are demonstrated.

The Often-Overlooked Power of Summary Statistics in Exploratory Data Analysis: Comparison of Pattern Recognition Entropy (PRE) to Other Summary Statistics and Introduction of Divided Spectrum-PRE (DS-PRE).

Unsupervised exploratory data analysis (EDA) is often the first step in understanding complex data sets. While summary statistics are among the most efficient and convenient tools for exploring and describing sets of data, they are often overlooked in EDA. In this paper, we show multiple case studies that compare the performance, including clustering, of a series of summary statistics in EDA. The summary statistics considered here are pattern recognition entropy (PRE), the mean, standard deviation (STD), 1-norm, range, sum of squares (SSQ), and X4, which are compared with principal component analysis (PCA), multivariate curve resolution (MCR), and/or cluster analysis. PRE and the other summary statistics are direct methods for analyzing data-they are not factor-based approaches. To quantify the performance of summary statistics, we use the concept of the "critical pair," which is employed in chromatography. The data analyzed here come from different analytical methods. Hyperspectral images, including one of a biological material, are also analyzed. In general, PRE outperforms the other summary statistics, especially in image analysis, although a suite of summary statistics is useful in exploring complex data sets. While PRE results were generally comparable to those from PCA and MCR, PRE is easier to apply. For example, there is no need to determine the number of factors that describe a data set. Finally, we introduce the concept of divided spectrum-PRE (DS-PRE) as a new EDA method. DS-PRE increases the discrimination power of PRE. We also show that DS-PRE can be used to provide the inputs for the k-nearest neighbor (kNN) algorithm. We recommend PRE and DS-PRE as rapid new tools for unsupervised EDA.

Correlative Hyperspectral Imaging Using a Dimensionality-Reduction-Based Image Fusion Method.

Chemical imaging techniques are increasingly being used in combination to achieve a greater understanding of a sample. This is especially true in the case of mass spectrometry imaging (MSI), where the use of different ionization sources allows detection of different classes of molecules across a range of spatial resolutions. There has been significant recent effort in the development of data fusion algorithms that attempt to combine the benefits of multiple techniques, such that the output provides additional information that would have not been present or obvious from the individual techniques alone. However, the majority of the data fusion methods currently in use rely on image registration to generate the fused data and therefore can suffer from artifacts caused by interpolation. Here, we present a method for data fusion that does not incorporate interpolation-based artifacts into the final fused data, applied to data acquired from multiple chemical imaging modalities. The method is evaluated using simulated data and a model polymer blend sample, before being applied to biological samples of mouse brain and lung.

An Arylazopyrazole-Based N-Heterocyclic Carbene as a Photoswitch on Gold Surfaces: Light-Switchable Wettability, Work Function, and Conductance.

A novel photoresponsive and fully conjugated N-heterocyclic carbene (NHC) has been synthesized that combines the excellent photophysical properties of arylazopyrazoles (AAPs) with an NHC that acts as a robust surface anchor (AAP-BIMe). The formation of self-assembled monolayers (SAMs) on gold was proven by ToF-SIMS and XPS, and the organic film displayed a very high stability at elevated temperatures. This stability was also reflected in a high desorption energy, which was determined by temperature-programmed SIMS measurements. E-/Z-AAP-BIMe@Au photoisomerization resulted in reversible alterations of the surface energy (i.e. wettability), the surface potential (i.e. work function), and the conductance (i.e. resistance). The effects could be explained by the difference in the dipole moment of the isomers. Furthermore, sequential application of a dummy ligand by microcontact printing and subsequent backfilling with AAP-BIMe allowed its patterning on gold. To the best of our knowledge, this is the first example of a photoswitchable NHC on a gold surface. These properties of AAP-BIMe@Au illustrate its suitability as a molecular switch for electronic devices.

A methodological inter-comparison study on the detection of surface contaminant sodium dodecyl sulfate applying ambient- and vacuum-based techniques.

Biomedical devices are complex products requiring numerous assembly steps along the industrial process chain, which can carry the potential of surface contamination. Cleanliness has to be analytically assessed with respect to ensuring safety and efficacy. Although several analytical techniques are routinely employed for such evaluation, a reliable analysis chain that guarantees metrological traceability and quantification capability is desirable. This calls for analytical tools that are cascaded in a sensible way to immediately identify and localize possible contamination, both qualitatively and quantitatively. In this systematic inter-comparative approach, we produced and characterized sodium dodecyl sulfate (SDS) films mimicking contamination on inorganic and organic substrates, with potential use as reference materials for ambient techniques, i.e., ambient mass spectrometry (AMS), infrared and Raman spectroscopy, to reliably determine amounts of contamination. Non-invasive and complementary vibrational spectroscopy techniques offer a priori chemical identification with integrated chemical imaging tools to follow the contaminant distribution, even on devices with complex geometry. AMS also provides fingerprint outputs for a fast qualitative identification of surface contaminations to be used at the end of the traceability chain due to its ablative effect on the sample. To absolutely determine the mass of SDS, the vacuum-based reference-free technique X-ray fluorescence was employed for calibration. Convex hip liners were deliberately contaminated with SDS to emulate real biomedical devices with an industrially relevant substance. Implementation of the aforementioned analytical techniques is discussed with respect to combining multimodal technical setups to decrease uncertainties that may arise if a single technique approach is adopted. Graphical abstract ᅟ.

3D Molecular ToF-SIMS Imaging of Artificial Lipid Membranes Using a Discriminant Analysis-Based Algorithm.

Artificial lipid membranes play a growing role in technical applications such as biosensors in pharmacological research and as model systems in the investigation of biological lipid films. In the standard procedure for displaying the distribution of membrane components, fluorescence microscopy, the fluorophores used can influence the distribution of the components and usually not all substances can be displayed at the same time. The discriminant analysis-based algorithm used in combination with scanning time-of-flight secondary ion mass spectrometry (ToF-SIMS) enables marker-free, quantitative, simultaneous recording of all membrane components. These data are used for reconstruction of distribution patterns. In the model system used for this survey, a tear fluid lipid layer, the distribution patterns of all lipids correlate well in calculated ToF-SIMS images and epi-fluorescence microscopic images. All epi-fluorescence microscopically viewable structures are visible when using both positive and negative secondary ions and can be reproduced with high lateral resolution in the submicrometer range despite the very low signal intensity and a very low signal-to-noise ratio. In addition, three-dimensional images can be obtained with a subnanometer depth resolution. Furthermore, structures and the distribution of substances that cannot be made visible by epi-fluorescence microscopy can be displayed. This enables new insights that cannot be gained by epi-fluorescence microscopy alone.

Influence of Matrix pKa on Molecular Ion Formation in Matrix-Enhanced Secondary-Ion Mass Spectrometry.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is one of the most important techniques for chemical imaging of nanomaterials and biological samples with high lateral resolution. However, low ionization efficiency limits the detection of many molecules at low concentrations or in very small volumes. One promising approach to increasing the sensitivity of the technique is by the addition of a matrix that promotes ionization and desorption of important analyte molecules. This approach is known as matrix-enhanced secondary-ion mass spectrometry (ME-SIMS). We have investigated the effect of matrix acidity on molecular ion formation in three different biomolecules. A series of cinnamic acid based matrixes that vary in acidity was employed to systematically investigate the influence of matrix acidity on analyte ion formation. The positive ion signal for all three biomolecules showed a strong increase for more acidic matrixes. The most acidic matrix was then vapor-deposited onto mouse brain sections. This led to significant enhancement of lipid signals from the brain. This work indicates that proton donation plays an important role in the formation of molecular ions in ME-SIMS.

Matrix-Enhanced SIMS: The Influence of Primary Ion Species and Cluster Size on Ion Yield and Ion Yield Enhancement of Lipids.

Time-of-flight secondary ion mass spectrometry is one of the most promising techniques for label-free analysis of biomolecules with nanoscale spatial resolution. However, high-resolution imaging of larger biomolecules such as phospholipids and peptides is often hampered by low yields of molecular ions. Matrix-enhanced SIMS (ME-SIMS), in which an organic matrix is added to the sample, is one promising approach to enhancing the ion yield for biomolecules. Optimizing this approach has, however, been challenging because the processes involved in increasing the ion yield in ME-SIMS are not yet fully understood. In this work, the matrix α-cyano-4-hydroxycinnamic acid (HCCA) has been combined with cluster primary ion analysis to better understand the roles of proton donation and reduced fragmentation on lipid molecule ion yield. A model system consisting of 1:100 mol ratio dipalmitoylphosphatidylcholine (DPPC) in HCCA as well as an HCCA-coated mouse brain cryosection have been studied using a range of Bi and Ar cluster ions. Although the molecular ion yield increased with an increase in cluster ion size, the enhancement of the signals from intact lipid molecules decreased with an increase in cluster ion size for both the model system and the mouse brain. Additionally, in both systems, protonated molecular ions were significantly more enhanced than sodium and potassium cationized molecules for all of the primary ions utilized. For the model system, the DPPC molecular ion yield was increased by more than an order of magnitude for all of the primary ions studied, and fragmentation of DPPC was dramatically reduced. However, on the brain sample, even though the HCCA matrix reduced DPPC fragmentation for all of the primary ions studied, the matrix coating suppressed the ion yield for some lipids when the larger cluster primary ions were employed. This indicated insufficient migration of the lipids into the matrix coating, so that dilution by the matrix overpowered the enhancement effect. This study provides strong evidence that the HCCA matrix both enhances protonation and reduces fragmentation. For imaging applications, the ability of the analytes to migrate to the surface of the matrix coating is also a critical factor for useful signal enhancement. This work demonstrates that the HCCA matrix provides a softer desorption environment when using Bi cluster ions than that obtained using the large gas cluster ions studied alone, indicating the potential for improved high spatial resolution imaging with ME-SIMS.

Selective Removal of Gold: N-Heterocyclic Carbenes as Positive Etch Resists on Planar Gold Surfaces.

N-Heterocyclic carbene (NHC)-modified planar gold surfaces (NHC@Au) were found to be more susceptible toward wet chemical etching than undecorated surface areas. Site-selective decoration of NHCs on Au was achieved by microcontact printing (µCP) of the NHC precursors 1,3-bis(diisopropylphenyl)imidazol-3-ium hydrogen carbonate (IPr(H)[HCO3]) or 1,3-dimethylbenzimidazol-3-ium hydrogen carbonate (BIMe(H)[HCO3]). Strikingly, BIMe@Au showed concentration-dependent etching behavior, tunable from a positive resist to a negative resist. Surface patterning was verified by time-of-flight secondary-ion mass spectrometry and Kelvin probe force microscopy. Moreover, orthogonal µCP enabled the patterned functionalization of planar Au with both IPr and 1-eicosanethiol and the subsequent formation of three-dimensional structures with a single etching step. The selective removal of Au by functionalization with a surface ligand is unprecedented and enables novel applications of NHCs in materials chemistry and nanofabrication.

Investigation of the utility of laser-secondary neutral mass spectrometry for the detection of polyaromatic hydrocarbons in individual atmospheric aerosol particles.

The distribution of polyaromatic hydrocarbons (PAHs) in ambient aerosol particles is of importance to both human health and climate forcing. Although time-of-flight secondary ion mass spectrometry (ToF-SIMS) has proven useful for studying the distribution of organic compounds in individual aerosol particles, it is difficult to detect PAHs at relevant concentrations in individual aerosol particles because of their low ion yield. In this study, we explore the potential of using laser secondary neutral mass spectrometry (Laser-SNMS) to study three PAHs: pyrene, anthracene, and naphthalene. Because of the high volatility of PAHs, a cryostage was required for the analysis to prevent sublimation of the molecules into the vacuum chamber. We studied two laser systems, a 157 nm excimer laser, which is capable of single-photon ionization of the PAHs, and a 193 nm laser, which requires multiphoton ionization. Under optimized conditions for laser power density and primary ion pulse length, 193 nm postionization resulted in a 2-50-fold increase in ion yield over ToF-SIMS. Using the 157 nm laser, the yield was increased by more than 3 orders of magnitude for all 3 PAHs studied. The single-photon postionization process proved superior in terms of both yield enhancement and reduced fragmentation. By using the optimized 157 nm laser system and a cryostage, we were able to detect PAHs on the surface of 2 µm diameter ambient aerosol particles.

Candida albicans viability after exposure to amphotericin B: assessment using metabolic assays and colony forming units.

Metabolic assays are a preferred method for evaluation of Candida albicans viability after exposure to antimicrobial agents in cases in which the culture is a complex mixture of yeast and filamentous forms. There is a lack of published data indicating the strength of the correlation between metabolic assays and viable cell numbers determined by a standard assay such as colony forming units (CFU). We developed a kinetic metabolic assay (KMA) for quantifying viable cells which was tested on yeast cells in both exponential and stationary phase using alamarBlue and XTT as metabolic indicators. The KMA enabled quantification of the viable population over a range of 10(1) to 10(7) cells that linearly correlated (R(2)>0.98) with estimates made by enumeration of CFU regardless of the indicator or growth phase of the cells. Linear relationships were used to calibrate the KMA in terms of equivalent CFU. Viable cell populations were then determined after exposure to AmB. These results were compared with those obtained by direct enumeration of CFU. There were significant correlations between KMA-derived equivalent CFU and direct CFU estimates of viable cell populations for exponential-phase cells. However, the proportions of viable cells based on the KMA were consistently lower than those obtained directly by CFU. This trend was substantially more pronounced for stationary phase cells. These results show that even in the relatively simple case in which only the yeast form is present, the relationship between assessment by metabolic assays and CFU is perturbed by exposure to an antimicrobial and that, furthermore, growth phase alters the nature of the perturbation.

Development of a Knudsen-type matrix coater for sample preparation for mass spectrometry imaging.

The use of time-of-flight secondary ion mass spectrometry (SIMS) is of increasing interest for biological and medical applications due to its ability to provide chemical information on a submicrometer scale. However, the detection of larger biomolecules such as phospholipids and peptides is often inhibited by high fragmentation rates and low ionization efficiencies. One way to increase the secondary ion molecular yield is to chemically modify the surface using the matrix-enhanced SIMS approach, where an organic matrix is placed upon the surface. In this study, a Knudsen cell type matrix coater was developed in order to produce well-defined thicknesses of a matrix on a sample in order to study the effect of these matrix layers on the secondary ions. Using this technique, an order of magnitude enhancement of the useful ion yield for lipids was observed and clear enhancement of image contrast for lipids in brain tissue was demonstrated. The study shows that the layer thickness has a great influence on the emission of secondary ions, and therefore, its precise control is important for optimal yield enhancement.

Laser postionization of neutral molecules sputtered using bismuth and argon cluster primary ions.

In this study, the influence of two different cluster primary ions in laser secondary neutral mass spectrometry (Laser-SNMS) has been investigated. Despite the many advantages of Laser-SNMS, fragmentation of neutral organic molecules during both sputtering and photoionization has limited its efficiency for the study of large organic and biological molecules. Cluster ion sputtering, and in particular large argon gas cluster sputtering, has been proposed as a means of reducing this fragmentation. Molecules of 9-fluorenylmethoxycarbonyl-pentafluoro-l-phenylalanine were sputtered using Bi3+ and Ar2000+ cluster primary ions, and the desorbed neutral species ("secondary neutrals") were postionized using a 7.87 eV vacuum ultraviolet laser light fluorine excimer laser. By varying timing parameters and laser power density, time-of-flight and laser power density distributions were obtained to investigate the fragmentation and energy distributions of the sputtered neutral species. Changing from 30 keV Bi3+ sputtering to 10 keV Ar2000+ resulted in a significant reduction in fragmentation of the molecule as well as a suppression of the high background that results from metastable decay of highly excited ions, yielding significantly improved detection of the intact molecule and characteristic fragments. Analysis of the influence of laser power density and laser pulse delay time indicates a reduction of fragmentation in both the sputtering phase and the photoionization phase. This study demonstrates the importance of soft desorption for efficient laser postionization of large organic molecules and shows the potential for improving the efficiency of laser postionization by using large gas cluster ion sputtering.

Multivariate analysis strategies for processing ToF-SIMS images of biomaterials.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a hyperspectral imaging technique. Each pixel in a two-dimensional ToF-SIMS image (or each voxel in a three-dimensional (3-D) ToF-SIMS image) contains a full mass spectrum. Thus, multivariate analysis methods are being increasingly used to process biomaterial ToF-SIMS images so the maximum amount of information can be extracted from the images. This study examines the use of principal component analysis (PCA) and maximum autocorrelation factors (MAF) on four different ToF-SIMS images. These images were selected because they represent significant challenges for biomedical ToF-SIMS image processing (topographical features, low count rates, surface contaminants, etc.). With PCA four different types of scaling methods (auto, root mean, filter, and shift variance scaling) were used. The effect of two preprocessing methods (normalization and mean centering) was also examined for both PCA and MAF. The more computational intense MAF provided the best results for all the images investigated in this study, doing the best job of reducing the number of variables required to describe the image, enhancing image contrast and recovering key spectral features. MAF was particularly good at identifying subtle features that were often lost in PCA and impossible to visualize in single peak images. However, the combination of PCA with either root mean or shift variance scaling provided similar results to MAF. Thus, these combinations offer promising alternatives to MAF for working with large data sets encountered in 3-D imaging. Also, the new method of filter scaling is promising for processing low count rate images with salt and pepper noise. Normalization proved an important tool for deconvoluting chemical effects from topographic and/or matrix effects. Mean centering aided in reducing the dimensionality of the data, but in one case resulted in a loss of information.

Development and characterization of a stable adhesive bond between a poly(dimethylsiloxane) catheter material and a bacterial biofilm resistant acrylate polymer coating.

Catheter associated urinary tract infections are the most common health related infections worldwide, contributing significantly to patient morbidity and mortality and increased health care costs. To reduce the incidence of these infections, new materials that resist bacterial biofilm formation are needed. A composite catheter material, consisting of bulk poly(dimethylsiloxane) (PDMS) coated with a novel bacterial biofilm resistant polyacrylate [ethylene glycol dicyclopentenyl ether acrylate (EGDPEA)-co-di(ethyleneglycol) methyl ether methacrylate (DEGMA)], has been proposed. The coated material shows excellent bacterial resistance when compared to commercial catheter materials, but delamination of the EGDPEA-co-DEGMA coatings under mechanical stress presents a challenge. In this work, the use of oxygen plasma treatment to improve the wettability and reactivity of the PDMS catheter material and improve adhesion with the EGDPEA-co-DEGMA coating has been investigated. Argon cluster three dimensional-imaging time-of-flight secondary ion mass spectrometry (ToF-SIMS) has been used to probe the buried adhesive interface between the EGDPEA-co-DEGMA coating and the treated PDMS. ToF-SIMS analysis was performed in both dry and frozen-hydrated states, and the results were compared to mechanical tests. From the ToF-SIMS data, the authors have been able to observe the presence of PDMS, silicates, salt particles, cracks, and water at the adhesive interface. In the dry catheters, low molecular weight PDMS oligomers at the interface were associated with poor adhesion. When hydrated, the hydrophilic silicates attracted water to the interface and led to easy delamination of the coating. The best adhesion results, under hydrated conditions, were obtained using a combination of 5 min O2 plasma treatment and silane primers. Cryo-ToF-SIMS analysis of the hydrated catheter material showed that the bond between the primed PDMS catheter and the EGDPEA-co-DEGMA coating was stable in the presence of water. The resulting catheter material resisted Escherichia coli and Proteus mirabilis biofilm colonization by up to 95% compared with uncoated PDMS after 10 days of continuous bacterial exposure and had the mechanical properties necessary for use as a urinary catheter.

Changes in the molecular ion yield and fragmentation of peptides under various primary ions in ToF-SIMS and matrix-enhanced ToF-SIMS.

Time of flight secondary ion mass spectrometry (ToF-SIMS) is a powerful technique for the nanoanalysis of biological samples, but improvements in sensitivity are needed in order to detect large biomolecules, such as peptides, on the individual cell level at physiological concentrations. Two promising options to improve the sensitivity of SIMS to large peptides are the use of cluster primary ions to increase desorption of intact molecules or the use of matrix-assisted laser desorption/ionization (MALDI) matrices to increase the ionization probability. In this paper, the authors have combined these two approaches in order to improve understanding of the interaction between ionization and fragmentation processes. The peptides bradykinin and melittin were prepared as neat monolayers on silicon, in a Dextran-40 matrix and in two common MALDI matrices, 2,5-dihydroxybenzoic acid (DHB) and α-cyano-4-hydroxy cinnamic acid (HCCA). ToF-SIMS spectra of these samples were collected using a range of small Bi cluster primary ions and large Ar cluster primary ions. The trends observed in the molecular ion yield and the [M+H](+)/C4H8N(+) ratio with primary ion cluster size were sample system dependent. The molecular ion yield of the bradykinin was maximized by using 30 keV Bi3 (+) primary ions in a DHB matrix but in the HCCA matrix, the maximum molecular ion yield was obtained by using 30 keV Bi7 (+) primary ions. In contrast, the molecular ion yield for melittin in both matrices was greatest using 20 keV Ar2000 (+) primary ions. Improvements in the molecular ion yield were only loosely correlated with a decrease in small fragment ions. The data indicate a complex interplay between desorption processes and ion formation processes which mean that the optimal analytical conditions depend on both the target analyte and the matrix.