6.5 Synthese und Streuverfahren nanostrukturierter Materialien
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Small-angle scattering is an increasingly common method for characterizing particle ensembles in a wide variety of sample types and for diverse areas of application. SASfit has been one of the most comprehensive and flexible curve-fitting programs for decades, with many specialized tools for various fields. Here, a selection of enhancements and additions to the SASfit program are presented that may be of great benefit to interested and advanced users alike: (a) further development of the technical basis of the program, such as new numerical algorithms currently in use, a continuous integration practice for automated building and packaging of the software, and upgrades on the plug-in system for easier adoption by third-party developers; (b) a selection of new form factors for anisotropic scattering patterns and updates to existing form factors to account for multiple scattering effects; (c) a new type of a very flexible distribution called metalog [Keelin (2016). Decis. Anal. 13, 243–277], and regularization techniques such as the expectation-maximization method [Dempster et al. (1977). J. R. Stat. Soc. Ser. B (Methodological), 39, 1–22; Richardson (1972) J. Opt. Soc. Am. 62, 55; Lucy (1974). Astron. J. 79, 745; Lucy (1994). Astron. Astrophys. 289, 983–994], which is compared with fits of analytical size distributions via the non-linear least-squares method; and (d) new structure factors, especially for ordered nano- and meso-scaled material systems, as well as the Ornstein–Zernike solver for numerical determination of particle interactions and the resulting structure factor when no analytical solution is available, with the aim of incorporating its effects into the small-angle scattering intensity model used for fitting with SASfit.
A tool for merging and/or rebinning single or multiple datasets to achieve a lower point density with best possible statistics. highly scriptable, CLI, no GUI
Version 0.1: works but could do with a cleanup. Weighting by uncertainty currently always on, but should be optional for use as an azimuthal or radial averager
Measuring an X-ray scattering pattern is relatively easy, but measuring a steady stream of high-quality, useful patterns requires significant effort and good laboratory organization.
Such laboratory organization can help address the reproducibility crisis in science, and easily multiply the scientific output of a laboratory, while greatly elevating the quality of the measurements. We have demonstrated this for small- and wide-angle X-ray scattering in the MOUSE project (Methodology Optimization for Ultrafine Structure Exploration).
With the MOUSE, we have combined a comprehensive and highly automated laboratory workflow with a heavily modified X-ray scattering instrument. This combination allows us to collect fully traceable scattering data, within a well-documented, FAIR-compliant data flow (akin to what is found at the more automated synchrotron beamlines). With two full-time researchers, our lab collects and interprets thousands of datasets, on hundreds of samples, for dozens of projects per year, supporting many users along the entire process from sample selection and preparation, to the analysis of the resulting data.
This talk will briefly introduce the foundations of X-ray scattering, present the MOUSE project, and will highlight the proven utility of the methodology for materials science. Upgrades to the methodology will also be discussed, as well as possible avenues for transferring this holistic methodology to other instruments
A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a quasi-randomly distributed point cloud in the desired particle shape and then applies the open-source software DEBYER for efficient evaluation of Debye’s scattering formula to calculate the SAXS pattern (https://github.com/j-from-b/CDEF). If self-correlation of the scattering signal is not omitted, the quasi-random distribution provides faster convergence compared with a true-random distribution of the scatterers, especially at higher momentum transfer. The usage of the software is demonstrated for the evaluation of scattering data of Au nanocubes with rounded edges, which were measured at the four-crystal monochromator beamline of PTB at the synchrotron radiation facility BESSY II in Berlin. The implementation is fast enough to run on a single desktop computer and perform model fits within minutes. The accuracy of the method was analyzed by comparison with analytically known form factors and verified with another implementation, the SPONGE, based on a similar principle with fewer approximations. Additionally, the SPONGE coupled to McSAS3 allows one to retrieve information on the uncertainty of the size distribution using a Monte Carlo uncertainty estimation algorithm.
Post-assembly modifications are efficient tools to adjust colloidal features of block copolymer (BCP) particles. However, existing methods often address particle shape, morphology, and chemical functionality individually. For simultaneous control, we transferred the concept of seeded polymerization to phase separated BCP particles. Key to our approach is the regioselective polymerization of (functional) monomers inside specific BCP domains. This was demonstrated in striped PS-b-P2VP ellipsoids. Here, polymerization of styrene preferably occurs in PS domains and increases PS lamellar thickness up to 5-fold. The resulting asymmetric lamellar morphology also changes the particle shape, i.e., increases the aspect ratio. Using 4-vinylbenzyl azide as co-monomer, azides as chemical functionalities can be added selectively to the PS domains. Overall, our simple and versatile method gives access to various multifunctional BCP colloids from a single batch of pre-formed particles.
Designing the shape and size of catalyst particles, and their interfacial charge, at the nanometer scale can radically change their performance. We demonstrate this with ceria nanoparticles. In aqueous media, nanoceria is a functional mimic of haloperoxidases, a group of enzymes that oxidize organic substrates, or of peroxidases that can degrade reactive oxygen species (ROS) such as H2O2 by oxidizing an organic substrate. We show that the chemical activity of CeO2−x nanoparticles in haloperoxidase- and peroxidaselike reactions scales with their active surface area, their surface charge, given by the ζ-potential, and their surface defects (via the Ce3+/Ce4+ ratio). Haloperoxidase-like reactions are controlled through the ζ-potential as they involve the adsorption of charged halide anions to the CeO2 surface, whereas peroxidase-like reactions without charged substrates are controlled through the specific surface area SBET. Mesoporous CeO2−x particles, with large surface areas, were prepared via template-free hydrothermal reactions and characterized by small-angle X-ray scattering. Surface area, ζ-potential and the Ce3+/Ce4+ ratio are controlled in a simple and predictable manner by the synthesis time of the hydrothermal reaction as demonstrated by X-ray photoelectron spectroscopy, sorption and ζ-potential measurements. The surface area increased with synthesis time, whilst the Ce3+/Ce4+ ratio scales inversely with decreasing ζ-potential. In this way the catalytic activity of mesoporous CeO2−x particles could be tailored selectively for haloperoxidase- and peroxidase-like reactions. The ease of tuning the surface properties of mesoporous CeO2x particles by varying the synthesis time makes the synthesis a powerful general tool for the preparation of nanocatalysts according to individual needs.
Mechanically stable structures with interconnected hierarchical porosity combine the benefits of both small
and large pores, such as high surface area, pore volume, and good mass transport capabilities. Hence, lightweight micro-/meso-/macroporous monoliths are prepared from ordered mesoporous silica COK-12 by means of spark plasma sintering (SPS, S-sintering) and compared to conventionally (C-) sintered monoliths. A multi-scale model is developed to fit the small angle X-ray scattering data and obtain information on the hexagonal lattice parameters, pore sizes from the macro to the micro range, as well as the dimensions of the silica population. For both sintering techniques, the overall mesoporosity, hexagonal pore ordering, and amorphous character are preserved. The monoliths' porosity (77–49%), mesopore size (6.2–5.2 nm), pore volume (0.50–0.22 g cm-3
), and specific surface area (451–180 m2 g-1) decrease with increasing processing temperature and pressure. While the difference in porosity is enhanced, the
structural parameters between the C-and S-sintered monoliths are largely converging at 900 C, except for the mesopore size and lattice parameter, whose dimensions are more extensively preserved in the
S-sintered monoliths, however, coming along with larger deviations from the theoretical lattice. Their higher mechanical properties (biaxial strength up to 49 MPa, 724 MPa HV 9.807 N) at comparable porosities and ability to withstand ultrasonic treatment and dead-end filtration up to 7 bar allow S-sintered monoliths to reach a high permeance (2634 L m-2 h-1 bar-1), permeability (1.25 x 10^-14 m2), and ability to reduce the chemical oxygen demand by 90% during filtration of a surfactant-stabilized oil in water emulsion, while indicating reasonable resistance towards fouling.
Li-rich nanoparticles of Li1+xMn2–xO4 doped with Al, Co, or Ni are successfully synthesized using a facile, fast, and efficient microwave-assisted hydrothermal route. Synchrotron X-ray diffraction confirms the formation of the crystalline cubic spinel phase type. X-ray absorption spectroscopy analysis at the Co and Ni K- and L-edges verifies that the dopants are within the Li1+xMn2–xO4 spinel structure and are inactive during cycling in the bulk and at the surface. Moreover, we demonstrate that nanocrystallinity and cationic doping play an important role in improving the electrochemical performance with respect to LiMn2O4 microparticles. They significantly reduce the charge-transfer resistance, lower the first cycle irreversible capacity loss to 6%, and achieve a capacity retention between 85 and 90% after 380 cycles, with excellent Coulombic efficiency close to 99% without compromising the specific charge at a 5C cycling rate. Furthermore, the Mn K- and L-edges attest that after long cycling, the Mn oxidation state in the bulk differs from that at the surface caused by the Mn disproportion reaction; however, the cationic doping helps mitigate the Mn dissolution with respect to the undoped Li1+xMn2–xO4 nanoparticles, as indicated by inductively coupled plasma atomic emission spectrometry.
Advanced peptide-based nanomaterials composed of self-assembling peptides (SAPs) are of emerging interest in pharmaceutical and biomedical applications. The introduction of fluorine into peptides, in fact, offers unique opportunities to tune their biophysical properties and intermolecular interactions. In particular, the degree of fluorination plays a crucial role in peptide engineering as it can be used to control the characteristics of fluorine-specific interactions and, thus, peptide conformation and self-assembly. Here, we designed and explored a series of amphipathic peptides by incorporating the fluorinated amino acids (2S)-4-monofluoroethylglycine (MfeGly), (2S)-4,4-difluoroethylglycine (DfeGly) and (2S)-4,4,4-trifluoroethylglycine (TfeGly) as hydrophobic components. This approach enabled studying the impact of fluorination on secondary structure formation and peptide self-assembly on a systematic basis. We show that the interplay between polarity and hydrophobicity, both induced differentially by varying degrees of side chain fluorination, does affect peptide folding significantly. A greater degree of fluorination promotes peptide fibrillation and subsequent formation of physical hydrogels in physiological conditions. Molecular simulations revealed the key role played by electrostatically driven intra-chain and inter-chain contact pairs that are modulated by side chain fluorination and give insights into the different self-organization behaviour of selected peptides. Our study provides a systematic report about the distinct features of fluorinated oligomeric peptides with potential applications as peptide-based biomaterials.
Herein, a simple one-pot procedure is reported to obtain aqueous zinc oxide (ZnO) nanoparticle dispersions from ZnO nanoparticles dispersed in cyclohexane. In the process, polyoxyethylene (20) sorbitan monooleate (polysorbate 80, Tween 80) functions as a phase transfer agent and colloidal stabilizer. The particles grow in a defined manner during the transfer, presumably via coalescence. The final particle radii are tuneable in the range from 2.3 ± 0.1 nm to 5.7 ± 0.1 nm depending on the incubation time of the dispersion at 90 °C. Small-angle X-ray scattering is employed to determine the particle radius distributions before and after phase transfer. The larger ZnO particle radii are associated with a redshift of the optical bandgap and luminescence emission, as expected for semiconductor nanoparticles. The particles presented here exhibit a relative size distribution width of 20%, rendering them attractive for applications in, e.g., biology or catalysis. The latter application is demonstrated at the photocatalytic degradation of methylene blue dye.