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The analysis of nanomaterials is current an important task - especially in case of risk assessment, as the properties of these material class are not well understood currently. The rather high surface area of these objects renders their interactions significantly different to their corresponding bulk. Thus, the surfaces chemical composition has to be investigated to get a better understanding and prediction of the nanomaterials' behavior. ToF-SIMS has proven as a powerful tool to determine said chemical composition. Its superior surface sensitivity allows us to study mainly the utmost atomic layer and therefore gives us an idea of the interactions involved. Here, we show first result from the validation of the method for the analysis of polystyrene and gold nanoparticles. ToF-SIMS will be compared to other methods like XPS, T-SEM or REM. Furthermore, principle component analysis (PCA) will be used to detect the influence of different sample preparation performed by an innovative microfluidic device. ToF-SIMS imaging is desired to be implemented for single particle detection as well.
The analysis of nanomaterials is currently an important task - especially in case of risk assessment – as the properties of these material class are not well understood. The rather high surface area of these objects renders their interactions significantly different to their corresponding bulk. Thus, the surface’s chemical composition must be investigated to get a better understanding and prediction of the nanomaterials’ behavior. ToF-SIMS and XPS have proven to be powerful tools to determine the general chemical composition. The superior surface sensitivity of ToF-SIMS furthermore allows us to study mainly the utmost atomic layer and thus gives us an idea of the interactions involved. Here, we present initial data on the analysis of Hyflon®-polystyrene core-shell nanoparticles which can be used as a model system due to the known preparation and a rather good chemical as well as physical separation of core and shell. Furthermore, principle component analysis (PCA) will be used to detect the influence of sample preparation and for a better separation of different samples. ToF-SIMS imaging is desired to be implemented for single particle detection as well.
During the energy transformation from fossil fuels to renewable energy sources, the use of hydrogen as fuel and energy storage can play a key role. This presents new challenges to industry and the scientific community alike. The storage and transport of hydrogen, which is nowadays mainly realized by austenitic stainless steels, remains problematic, which is due to the degradation of mechanical properties and the possibility of phase transformation by hydrogen diffusion and accumulation. The development of materials and technologies requires a fundamental understanding of these degradation processes. Therefore, studying the behavior of hydrogen in austenitic steel contributes to an understanding of the damage processes, which is crucial for both life assessment and safe use of components in industry and transportation. As one of the few tools that is capable of depicting the distribution of hydrogen in steels, time-of-flight secondary ion mass spectrometry was conducted after electrochemical charging. To obtain further information about the structural composition and cracking behavior, electron-backscattered diffraction and scanning electron microscopy were performed. Gathered data of chemical composition and topography were treated employing data fusion, thus creating a comprehensive portrait of hydrogen-induced effects in the austenite grade AISI 304L. Specimens were electrochemically charged with deuterium instead of hydrogen. This arises from the difficulties to distinguish between artificially charged hydrogen and traces existing in the material or the rest gas in the analysis chamber. Similar diffusion and permeation behavior, as well as solubility, allow nonetheless to draw conclusions from the experiments.
The analysis of nanomaterials is currently an important task - especially in case of risk assessment – as the properties of these material class are not well understood. The rather high surface area of these objects renders their interactions significantly different to their corresponding bulk. Thus, the surface’s chemical composition must be investigated to get a better understanding and prediction of the nanomaterials’ behavior. ToF-SIMS and XPS have proven to be powerful tools to determine the general chemical composition. The superior surface sensitivity of ToF-SIMS furthermore allows us to study mainly the utmost atomic layers and thus gives us an idea of the interactions involved.
Here, we present initial data on the analysis of Hyflon®-polystyrene core-shell nanoparticles which can be used as a model system due to the known preparation and a rather good chemical as well as physical separation of core and shell. Furthermore, results on Au nanoparticles with and without an antibody shell are presented. Principle component analysis (PCA) will be used to detect the influence of sample preparation and for a better separation of different samples. ToF-SIMS imaging is desired to be implemented for single particle detection as well.
The analysis of nanomaterials is currently an important task - especially in case of risk assessment – as the properties of these material class are not well understood and their growing use in everyday life. The rather high surface area of these objects renders their interactions significantly different to their corresponding bulk. Thus, the surface’s chemical composition must be investigated to get a better understanding and prediction of the nanomaterials’ behaviour. ToF-SIMS and XPS have proven to be powerful tools to determine the general chemical composition. The superior surface sensitivity of ToF-SIMS furthermore allows us to study mainly the utmost atomic layers and thus gives us an idea of possible interactions involved. Supported by multivariate data analysis such as principal component analysis (PCA), the method can also be used for sub-classification of different materials using slight differences in surface chemistry.
Here, we present data of the analysis of Hyflon®-polystyrene core-shell nanoparticles which can be used as a model system due to the known preparation and a rather good chemical as well as physical separation of core and shell. Principle component analysis (PCA) will be used to detect the influence of sample preparation and for a better separation of different samples. This is achieved by measurement of a statistically relevant set of samples for every particle sample. We acquired surface spectra under static SIMS conditions with Bi32+ and analysed the resulting spectra by PCA. The carefully selected and refined peaks allow a reasonable categorization and further a reliable allocation of blank feeds. In detail, the fluorine containing, organic fragments are an indication for a heterogeneous shell that has errors. Furthermore, results on Au nanoparticles with and without an antibody shell are presented. ToF-SIMS imaging is desired to be implemented for single particle detection as well.
Due to the growing number of engineered nanomaterials (NM) the need for a reliable risk assessment for these materials is today bigger than ever before. Especially the nanomaterial’s surface or shell directly interacts with its environment and therefore is a crucial factor for NM’ toxicity or functionality.
Especially, titania is one of the NM with the greatest technological importance. It is used for a large number of applications and can be found in food, cosmetics, glasses, mirrors, paints to mention only a few. In 2012, experts estimate[d] the annual European nano-titania production or utilization at an amount of more than 10,000 t.
Great progress has been achieved in the area of NM investigation and characterization during the past decade. A variety of publications provide information about technological innovation as well as hazard potential, which means the potential risk on human health and ecosystems. However, enhanced data harmonization and well-defined standards for nanomaterial analysis, could significantly improve the reliability of such studies which often suffers from varying methods, parameters and sample preparations. To develop a suitable approach for the NM’s risk assessment, the ACEnano project aims at establishing a toolbox of verified methods. The size of this well-structured European project allows to handle even those big challenges like data harmonization and standardization.
Due to its powerful combination of superior surface sensitivity and lateral resolution down to the Nano regime, ToF-SIMS could become one of these toolbox methods. Supported by multivariate data analysis such as principal component analysis (PCA), the method can be used for sub-classification of nanomaterial families using slight differences in surface chemistry.
Here, we show a PCA supported classification of titania nanoparticles from various sources (NIST, JRC, BAM) with ToF-SIMS. Parameters like size, shell, pre-preparation and crystal system cause variance in the data and allow us to distinguish the species from each other. Moreover, this variance in the data also occurs and can be used for investigation when we compare our measurements of particle ensembles with those of grown titania films. The carefully selected and refined peaks allow a reasonable particle categorization and further a reliable allocation of blank feeds, which introduces a promising approach for NM characterization in the context of NM risk assessment.
A method is described for high-resolution label-free molecular imaging of human bone tissue. To preserve the lipid content and the heterogeneous structure of osseous tissue, 4 μm thick human bone sections were prepared via cryoembedding and tape-assisted cryosectioning, circumventing the application of organic solvents and a decalcification step. A protocol for comparative mass spectrometry imaging (MSI) on the same section was established for initial analysis with time-of-flight secondary ion mass spectrometry (TOF-SIMS) at a lateral resolution of 10 μm to <500 nm, followed by atmospheric pressure scanning microprobe matrix-assisted laser desorption/ionization (AP-SMALDI) Orbitrap MSI at a lateral resolution of 10 μm. This procedure ultimately enabled MSI of lipids, providing the lateral localization of major lipid classes such as glycero-, glycerophospho-, and sphingolipids. Additionally, the applicability of the recently emerged Orbitrap-TOF-SIMS hybrid system was exemplarily examined and compared to the before-mentioned MSI methods.
Biomedical applications, including functional biomaterials, carbohydrate-arrays, and glycan-based biosensors.
The chemistry of glycan immobilization plays an essential role in the bioavailability and function of surface bound carbohydrate moieties. For biomedical applications the stability over time (shelf life) of glycan arrays is a crucial factor. Herein we report on approaches for surface and interface characterization relevant to the needs of production of glycan microarrays which were tested using model carbohydrate surfaces. For detailed characterization of glycan model surfaces we used a combination of X-ray photoelectron spectroscopy (XPS), near edge X-ray absorption fine structure spectroscopy (NEXAFS) and ToF SIMS which are complementary techniques of surface chemical analysis. Links to fluorescence spectroscopy often used for characterization in the microarray community were established as well. In detail, amine-reactive silicon oxide and glass surfaces were used for anchoring oligosaccharides with an amino linker. The amount of surface bound carbohydrates was estimated by X-ray photoelectron spectroscopy (XPS). Glycan immobilization was investigated using lectins, which are glycan-binding molecules. A shelf life study of model glycan microarrays on epoxy-coated glass surfaces was done over a period of 160 days under different storage conditions utilizing fluorescence, ToF-SIMS and XPS analysis. It was shown that glycan activity of the models used can be maintained at least for half a year of storage at 4 °C.
In the presented research, the high potential and abilities of secondary ion mass spectrometry (ToF-SIMS) to detect and locally map the hydrogen distribution in two types of duplex stainless steels are shown. The research validates certain proposed mechanisms by combining ToF-SIMS with high-resolution scanning electron microscopy and electron-backscattered diffraction. The combination of data from several techniques on the same region was conducted in this field for the first time by applying data treatment of the ToF-SIMS raw data and data fusion approach. This powerful combination of methods allows reviewing of the occurring processes related to hydrogen assisted cracking. The step beyond the state of the art in this field was gained here by developing permeation and mechanical loading experiments within the ToF-SIMS during chemometric imaging of the hydrogen distribution in the microstructure. The research presents the necessary correlation between the hydrogen distribution and the resulted structural changes, the diffusion behavior in a duplex microstructure and stress induced diffusion of hydrogen by applying external load at the microscale.
Due to its low mass and high diffusivity in presence of compositional, thermal and mechanical gradients, hydrogen within a metallic microstructure can result in severe loss in ductility even at low concentrations and might lead eventually to a catastrophic and unpredictable failure of structural components during service. In this context, hydrogen mapping at the microscale is still considered among the most important challenges on the pathway towards a better understanding of the hydrogen transport and assisted cracking phenomena in metals, specifically in structural components, e.g. steels.
Among the very few available techniques to localize hydrogen at the microscale, Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was proven to be a reliable tool. Based on the assumption that deuterium influence the microstructure similarly to hydrogen, in the following contribution ToF-SIMS was applied as the main technique to detect and locally map the deuterium distribution in several alloys: lean 2101 and standard 2205 duplex stainless steel (DSS), AISI 304L austenitic stainless steel and titanium 6Al-4V alloy. These alloys were selected as case studies in this work due to the wide use of them in many applications and environments which frequently provide critical conditions for hydrogen absorption and assisted degradation.
The innovative design of in-situ and ex-situ experiments enabled us to elucidate the permeation, transport and trapping of deuterium in the microstructure in sub-micron resolution for the first time. In addition to the novel experimental setups, further progress was gained by applying computational multivariate data analysis (MVA) on the raw data and data fusion with high resolution structural characterization methods (scanning electron microscopy and electron back-scattered diffraction – SEM/EBSD). This combination allowed us to correlate the deuterium distribution and the influence on the microstructure.