6.1 Oberflächen- und Dünnschichtanalyse
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Understanding the interaction between boehmite and epoxy and the formation of their interphases with different mechanical and chemical structures is crucial to predict and optimize the properties of epoxy-boehmite nanocomposites. Probing the interfacial properties with atomic force microscopy (AFM)-based methods, especially particle-matrix long-range interactions, is challenging. This is due to size limitations of various analytical methods in resolving nanoparticles and their interphases, the overlap of interphases, and the effect of buried particles that prevent the accurate interphase property measurement. Here, we develop a layered model system in which the epoxy is cured in contact with a thin layer of hydrothermally synthesized boehmite. Different microscopy methods are employed to evaluate the interfacial properties. With intermodulation atomic force microscopy (ImAFM) and amplitude dependence force spectroscopy (ADFS), which contain information about stiffness, electrostatic, and van der Waals forces, a soft interphase was detected between the epoxy and boehmite. Surface potential maps obtained by scanning Kelvin probe microscopy (SKPM) revealed another interphase about one order of magnitude larger than the mechanical interphase. The AFM-infrared spectroscopy (AFM-IR) technique reveals that the soft interphase consists of unreacted curing agent. The long-range electrical interphase is attributed to the chemical alteration of the bulk epoxy and the formation of new absorption bands.
We show that complex physical and chemical interactions between boehmite nanoparticles and epoxy drastically affect matrix properties, which in the future will provide tuning of material properties for further optimization in applications from automotive to aerospace. We utilize intermodulation atomic force microscopy (ImAFM) for probing local stiffness of both particles and polymer matrix. Stiff particles are expected to increase total stiffness of nanocomposites and the stiffness of polymer should remain unchanged. However, ImAFM revealed that stiffness of matrix in epoxy/boehmite nanocomposite is significantly higher than unfilled epoxy. The stiffening effect of the boehmite on epoxy also depends on the particle concentration. To understand the mechanism behind property alteration induced by boehmite nanoparticles, network architecture is investigated using dynamic mechanical thermal analysis (DMTA). It was revealed that although with 15 wt% boehmite nanoparticles the modulus at glassy state increases, crosslinking density of epoxy for this composition is drastically low.
This chapter first gives an introduction to the concepts of SSA and volume-specific surface area (VSSA) and an outline of the BET method. It continues with a discussion of the relationship between particle size, shape, and the VSSA, followed by an overview of instrumentation, experimental methods, and standards. Finally, sections on the use of the VSSA as a tool to identify nanomaterials and non-nanomaterials and its role in a regulatory context provide some insight on the importance of VSSA in the current Regulation of nanomaterials.
Welcome to the poster Towards Determination of Surface Roughness from a SEM Image, a contribution from BAM in Berlin, Germany. This work is part of the MamaLoCA project, which aims to develop a biosensor for the detection of mycotoxins in cereals. Biosensors come in a great variety, one of which makes use of microscopic beads produced by homogenous coating of polystyrene microspheres. The beads are functionalized by decorating them with bioreceptors – in our case antibodies – which then specifically react with the analyte – in our case mycotoxins – and emit an electrical or optical signal. The functionalization of the beads depends on the surface roughness because this determines the amount and orientation of binders. In other words, the surface roughness affects the accessibility to the binding sites and influences device sensitivity, hence its quantitative determination is an important step in evaluating the quality of the biosensor in general.
The presented solution to the problem of the estimation of surface roughness relies in the repetitive characteristics on the surface of the beads. A SEM image of the bead shows a raspberry like microparticle with a variation of grayscale values, which arise from the secondary electron yield. The principle of the measurement measures the variation of grayscale values along a circumference of a circle centred in the centre of the particle and with an arbitrary radius. The grayscale value variation along the given circumference gives the so-called z-modulation or the lateral profile. By performing Fast Fourier Transform on this profile we obtain the power spectrum as a function of the spatial frequencies through which the grayscales vary. The maximal value for spatial frequency then reveals the most common feature along one given circumference. Surface roughness then is the feature frequency in the spatial domain. This calculation is repeated for several concentric circles with different radii over the particle.
The results for the same particle but recorded at two different accelerating voltages show that the applied method has a potential to reveal the roughness. Interpretation of results from an SE InLens SEM image obtained using 3 kV shows that surface roughness is about 21 nm, which is in a good agreement with an alternative method given in a different presentation. The results from the 10 kV are underestimated due to the loss of surface sensitivity on the SE InLens detection at high voltages.
In conclusion, this method shows promise in determining quantitatively the surface roughness from a single SEM image and its validation is being sought using 3D SEM images and AFM methods.
Small-angle scattering data from particle dispersions with narrow size distributions are usually analysed by fitting a model function to the data, which is composed of a monodisperse form factor with a size distribution and, optionally, a structure factor. For common particle shapes like solid spheres, core-shell particles, ellipsoids or rods, the form factor can be computed analytically, and several software packages are readily available which provide a compilation of form factors.1,2 Recently, highly monodisperse nanoparticles with a variety of shapes have been synthesized, e.g. cubes and bipyramids3,4 with lightly capped edges, for which analytic form factors are harder to derive.
We compute an approximation to the scattering curve of arbitrary shapes by filling the shape with a quasi-random distribution of point scatterers and using Debye’s formula to get the overall scattering curve. The highly optimized debyer code is used to perform an efficient evaluation of Debye’s formula,5 which can perform the evaluation of 500,000 point scatterers in two minutes on commodity hardware. Moderate polydispersity is handled by interpolating the computed scattering curve over q from a master curve. In this way, the code is fast enough to perform data fitting of particle ensembles with moderate polydispersity for arbitrary shapes to experimental data.
This work was partly funded by the 17NRM04 nPSize project of the EMPIR programme co-financed by the EMPIR participating states and by the European Union’s Horizon 2020 research and innovation programme.
Abstract. In power electronics, compound semiconductors with large bandgaps, like silicon carbide (SiC), are increasingly being used as material instead of silicon. They have a lot of advantages over silicon but are also intolerant of nanoscale material defects, so that a defect inspection with high accuracy is needed. The different defect types on SiC samples are measured with various measurement methods, including optical and tactile methods. The defect types investigated include carrots, particles, polytype inclusions and threading dislocations, and they are analysed with imaging ellipsometry, coherent Fourier scatterometry (CFS), white light interference microscopy (WLIM) and atomic force microscopy (AFM). These different measurement methods are used to investigate which method is most sensitive for which type of defect to be able to use the measurement methods more effectively. It is important to be able to identify the defects to classify them as critical or non-critical for the functionality of the end product. Once these investigations have been completed, the measurement systems can be optimally distributed to the relevant defects in further work to realize a hybrid analysis of the defects. In addition to the identification and classification of defects, such a future hybrid analysis could also include characterizations, e.g. further evaluation of ellipsometric data by using numerical simulations.
The different defect types on SiC samples are measured with various measurement methods including optical and tactile methods. The defect types investigated include particles, carrots and triangles and they are analyzed with imaging ellipsometry, coherent Fourier scatterometry and atomic force microscopy. Each of these methods measures different properties of the defects and they all together contribute to a complete analysis.
A new method for top‐down, one‐pot, gram‐scale production of high quality nanographene by incubating graphite in a dilute sodium hypochlorite solution at only 40 °C is reported here. The produced sheets have only 4 at% oxygen content, comparable with nanographene grown by chemical vapor deposition. The nanographene sheets are covalently functionalized using a nondestructive nitrene [2+1] cycloaddition reaction that preserves their π‐conjugated system. Statistical analyses of Raman spectroscopy and X‐ray photoelectron spectroscopy indicate a low number of sp3 carbon atoms on the order of 2% before and 4% after covalent functionalization. The nanographene sheets are significantly more conductive than conventionally prepared nanographene oxide, and conductivity further increases after covalent functionalization. The observed doping effects and theoretical studies suggest sp2 hybridization for the carbon atoms involved in the [2+1] cycloaddition reaction leading to preservation of the π‐conjugated system and enhancing conductivity via n‐type doping through the bridging N‐atom. These methods are easily scalable, which opens the door to a mild and efficient process to produce high quality nanographenes and covalently functionalize them while retaining or improving their physicochemical properties.
Design and construction of a rainfall simulator to test metal runoff at atmospheric conditions
(2023)
A rainfall simulator was presented as an environmental assessment tool to quantify wash-off concentrations from metallic materials. It is part of the RUNOFF-project, which studies and re-assesses the durability of roofing and facade materials under current atmospheric conditions in Germany.
Studying building materials is important as they have a significant impact on achieving a variety of goals and targets within the sustainable developments goals (SDGs). The durability of materials is essential to reach sustainability. However, the durability of metallic materials is strongly depended on climate conditions, which have changed as a result of technical measures in industry, climate change and increasing urbanisation. In Germany at least, the data base is not up-to-date leading to prediction models regarding corrosion resistance and durability of metallic materials which can no longer be trusted and therefore need to be re-assessed and updated. Also, not only the demand for sustainable but also environmentally friendly building materials has increased dramatically. A number of construction materials produce chemical hazards, and therefore have negative impacts on water quality, soils health and ecosystems. To limit these impacts, environmental assessment methods and tools are needed to measure and quantify the inputs and outputs of building materials throughout their lifetime.