6.5 Synthese und Streuverfahren nanostrukturierter Materialien
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Eingeladener Vortrag
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An artificial digestion of silver nitrate is reported. It is shown that AgSCN nanoparticles emerge from ionic silver in saliva and remain present during the entire digestion process. The particles were characterized by infrared spectroscopy and small- and wide-angle X-ray scattering (SAXS/WAXS) regarding their composition and size distribution.
Uptake and molecular impact of aluminum-containing nanomaterials on human intestinal caco-2 cells
(2018)
Aluminum (Al) is one of the most common elements in the earth crust and increasingly used in food, consumer products and packaging. Its hazard potential for humans is still not completely understood. Besides the metallic form, Al also exists as mineral, including the insoluble oxide, and in soluble ionic forms. Representatives of these three species, namely a metallic and an oxidic species of Al-containing nanoparticles and soluble aluminum chloride, were applied to human intestinal cell lines as models for the intestinal barrier. We characterized physicochemical particle parameters, protein corona composition, ion release and cellular uptake. Different in vitro assays were performed to determine potential effects and molecular modes of Action related to the individual chemical species. For a deeper insight into signaling processes, microarray transcriptome analyses followed by bioinformatic data analysis were employed. The particulate Al species showed different solubility in biological media. Metallic Al nanoparticles released more ions than Al2O3 nanoparticles, while AlCl3 showed a mixture of dissolved and agglomerated particulate entities in biological media. The protein corona composition differed between both nanoparticle species. Cellular uptake, investigated in transwell experiments, occurred predominantly in particulate form, whereas ionic Al was not taken up by intestinal cell lines. Transcellular transport was not observed. None of the Al species showed cytotoxic effects up to 200 mg Al/mL. The transcriptome analysis indicated mainly effects on oxidative stress pathways, xenobiotic metabolism and metal homeostasis. We have shown for the first time that intestinal cellular uptake of Al occurs preferably in the particle form, while toxicological effects appear to be ion-related.
Negatively charged flat gold nanotriangles, formed in a vesicular template phase and separated by an AOT-micelle-based depletion flocculation, were reloaded by adding a cationic polyelectrolyte, that is, a hyperbranched polyethylenimine (PEI). Heating the system to 100 °C in the presence of a gold chloride solution, the reduction process leads to the formation of gold nanoparticles inside the polymer shell surrounding the nanoplatelets. The gold nanoparticle formation is investigated by UV−vis spectroscopy, small-angle X-ray scattering, and dynamic light scattering measurements in combination with transmission electron microscopy. Spontaneously formed gold clusters in the hyperbranched PEI shell with an absorption maximum at 350 nm grow on the surface of the nanotriangles as hemispherical particles with diameters of ∼6 nm. High-resolution micrographs show that the hemispherical gold particles are crystallized onto the {111} facets on the bottom and top of the platelet as well as on the edges without a grain boundary. Undulated gold nanoplatelet superstructures with special properties become available, which show a significantly modified performance in SERS-detected photocatalysis regarding both reactivity and enhancement factor.
tNegatively charged ultrathin gold nanotriangles (AuNTs) were synthesized in a vesicular dioctyl sodiumsulfosuccinate (AOT)/phospholipid-based template phase. These “naked” AuNTs with localized surfaceplasmon resonances in the NIR region at about 1300 nm and special photothermal properties are ofparticular interest for imaging and hyperthermia of cancerous tissues. For these kinds of applicationsthe toxicity and the cellular uptake of the AuNTs is of outstanding importance. Therefore, this studyfocuses on the toxicity of “naked” AOT-stabilized AuNTs compared to polymer-coated AuNTs. Poly-meric coating consisted of non-modified hyperbranched poly(ethyleneimine) (PEI), maltose-modifiedpoly(ethyleneimine) (PEI-Mal) and heparin. The toxicological experiments were carried out with twodifferent cell lines (embryonic kidney carcinoma cell line HEK293T and NK-cell leukemia cell line YTS).This study revealed that the heparin-coating of AuNTs improved biocompatibility by a factor of 50 whencompared to naked AuNTs. Of note, the highest nontoxic concentration of the AuNTs coated with PEI andPEI-Mal is drastically decreased. Overall, this is mainly triggered by the different surface charges of poly-meric coatings. Therefore, AuNTs coated with heparin were selected to carry out uptake studies. Theirpromising high biocompatibility and cellular uptake may open future studies in the field of biomedicalapplications.
Contrast-variation small-angle neutron scattering (CV-SANS), small-angle X-ray scattering (SAXS), nuclear magnetic resonance (NMR) measurements of diffusion and isothermal titration calorimetry (ITC) are used to gain insight into the aggregation of an alkyl–C60 derivative, molecule 1, in n-hexane, n-decane and toluene as a function of concentration and temperature. Results point to an associative mechanism of aggregation similar to other commonly associating molecules, including non-ionic surfactants or asphaltenes in non-aqueous solvents. Little aggregation is detected in toluene, but small micelle-like structures form in n-alkane solvents, which have a C60-rich core and alkyl-rich shell. The greatest aggregation extent is found in n-hexane, and at 0.1 M the micelles of 1 comprise around 6 molecules at 25 °C. These micelles become smaller when the concentration is lowered, or if the solvent is changed to n-decane. The solution structure is also affected by temperature, with a slightly larger aggregation extent at 10 °C than at 25 °C. At higher concentrations, for example in solutions of 1 above 0.3 M in n-decane, a bicontinuous network becomes apparent. Overall, these findings aid our understanding of the factors driving the assembly of alkyl–π-conjugated hydrophobic amphiphiles such as 1 in solution and thereby represent a step towards the ultimate goal of exploiting this phenomenon to form materials with well-defined order.
This poster deals with improvements and characteriztion of small-angle scattering limitations, by looking at the trifecta of Data collection and uncertainty propagation, data analysis methodologies, and real-world tests. It is found that - with appropriate care and instrumentation - accuracies of 1% on mean nanomaterial sizes, and 10% on the size distribution width as well as the volume fraction can be achieved.
Healable materials could play an important role in reducing the environmental footprint of our modern technological society through extending the life cycles of consumer products and constructions. Future technologies require smart materials with advanced properties including responsiveness to external stimuli and particularly the ability to autonomously repair inflicted damage. The introduction of reversible connections in the polymer architecture, either in a non-covalent fashion, such as in supramolecular polymers, or by using dynamic covalent chemistry. One facile approach involves the implementation of reversible polymer networks as they offer high mechanical strength and thermal properties that are readily modified by the nature of the connecting dynamic bonds and the crosslinking density. In this context, small-angle scattering allows a detailed insight into the network structure of self-healing polymers either in bulk materials or in form of hydrogels. Here we report on how small-angle scattering can contribute to reveal the network structure. A first example is the conditional repair by locally switching the thermal healing capability of dynamic covalent polymers with light.
Typical experimental SAXS curves of a photo- and thermal switchable polymer are shown. The scattering pattern show three characteristics. Region 1 is dominated by a forward scattering interpreted as resultant from large scale inhomogeneities of the bulk polymers (characterized by a first correlation length). The second scattering contribution can be interpreted as resultant from the network and is characterized by its entanglement distance. The mesh size of this network can be described by a second correlation length. Region 3 of the scattering pattern is dominated by a broad peak. Taking all effects into account, we approximate the total scattering as a sum of the three scattering contributions. In particular, the Debye-Büche function is used for I1 the Ornstein-Zernike function for the crosslinking contribution I2 and a Lorentzian peak function.
We discussed this simple and more sophisticated approaches for revealing network structures. Examples of studies from hydrogel networks are provided as important materials with polymeric networks in life science applications. Finally, the determination of mesh size distributions as a function of temperature, time and healing efficiency is discussed in detail.
Zinc oxide (ZnO) as a wide-bandgap II-VI semiconductor finds application in areas like optoelectronics, photocatalysis as well as in detection systems. While band-gap engineering in macroscopic ZnO can be performed by alloying, the band-gap of ZnO nanoparticles is also dependent on their size. Since small-angle X-ray scattering (SAXS) provides a much higher resolution in terms of ultra-small nanoparticle size analysis compared to other techniques, it allows for a careful examination of the correlation between particle size and band-gap.
We report on the microwave-assisted synthesis of oleate-capped, photoluminescent zinc oxide nanoparticles with adjustable size as dispersions in organic solvents. The spherical particles were obtained by hydrolysis of the metal precursor in presence of a strong base at temperatures above the solvent’s boiling point. Hence, the reaction is dramatically accelerated and within seconds – instead of hours at lower temperatures –, narrowly dispersed particle systems are yielded. The particles’ sizes as derived from SAXS strongly depend on the reaction temperature and time. Choosing the right reaction conditions, the particle size and thus their band gap can be finely tuned. A size increase can be achieved both by increasing the reaction temperature and the reaction time.
See Figure 1 for an exemplary comparison of five-minute syntheses at different temperatures. Here, the yielded particles display diameters between 5.0 and 7.6 nm and corresponding band-gaps of 3.32 up to 3.41 eV. The size increase is accompanied by a red-shift of the UV/Vis absorption edges and fluorescence emission.
Furthermore, these particles can be transferred into water by coating with polysorbates.
Data analysis of SAS measurements has been dominated by the classical curve fitting approach. This method finds optimal parameters of a scattering model composed of analytical expressions. SASfit represents such a classical curve fitting toolbox: it is one of the mature programs for small-angle scattering data analysis and has been available and used for many years. The latest developments [1] will be extended by improving the interoperability of the extensive data base of models with third-party analysis software. An updated format of model definitions is also presented, which allows model function plug-ins to be used with the Python language.
To complement the classical curve fitting method, the user-friendly opensource Monte Carlo regression package McSAS was developed. Most importantly, the form-free Monte Carlo approach of McSAS means that it is not necessary to provide any further mathematical restrictions to the Parameter distribution. Future developments include separating the core optimization from the GUI (allowing 'headless' integration), as well as parallel computing which reduces the computing time proportional to the number of available computing cores. The headless mode is presented by an example of Operation within interactive programming environments such as a Jupyter notebook.
The promising results of Monte Carlo based data analysis for determining form-free Parameter distributions motivated the evaluation of the method with dynamic light scattering (DLS) data. For this purpose, the method was adapted for analyzing correlation curves such as those from multi-angle dynamic light scattering (DLS) data. The development of McDLS intends to overcome limitations of existing methods at reliably determining the modality of size distributions. An example of Monte Carlo based data analysis of multimodal DLS measurements will be presented.