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BAM and Division 6.1
(2018)
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.
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.
Due to its large strength-to-weight ratio and excellent biocompatibility, titanium materials are of paramount importance for medical applications, e.g. as implant material for protheses. In this work, the evolution of various types of laser-induced micro- and nanostructures emerging on titanium or titanium alloys upon irradiation by near-infrared ultrashort laser pulses (925 fs, 1030 nm) in air environment is studied for various laser fluence levels, effective number of pulses and at different pulse repetition rates (1 – 400 kHz). The morphologies of the processed surfaces were systematically characterized by optical and scanning electron microscopy (OM, SEM). Complementary white-light interference microscopy (WLIM) revealed the corresponding surface topographies. Chemical and structural changes were analysed through depth-profiling time-of-flight secondary ion mass spectrometry (TOF-SIMS) and X-ray diffraction (XRD) analyses. The results point towards a remarkable influence of the laser processing parameters on the surface topography, while simultaneously altering the near-surface chemistry via laser-induced oxidation effects. Consequences for medical applications are outlined.
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.
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.
This talk was given within the scope of the SIMS-22 conference in October 2019 in Kyoto (Japan). It deals with the surface analytical investigation of nanoparticles by PCS-assisted ToF-SIMS. This technique is applicable to core-shell nanoparticles, in order to distinguish a complete encapsulation from an incomplete encapsulation of the core by the shell material. Furthermore, the depletion process of organic nanoparticle coatings caused by UV-weathering is investigated. Finally, the significance of grouping studies for nanomaterials research and risk assessment is demonstrated.
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.