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- 2022 (5) (entfernen)
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he main objective of the nPSize project is to improve the measurement capabilities for nanoparticle size based on both measurement methods traceable to SI units and new reference materials. Two basic approaches have been used in order to develop measurement procedures resulting in traceable results of the nanoparticle size distribution: physical modelling for the methods used in the project (TSEM, SEM, AFM and SAXS) and machine learning.
Physical modelling: In this part, the physical models associated with different shape measurements for the techniques TSEM, SEM, AFM and SAXS have been collected and further developed with the aim to simulate the resulting signal as measured by the individual methods. Uncertainties and traceability associated with each model were investigated and evaluated. In the following, the progress on these physical models is reported for each individual method.
Machine Learning modelling: The aim of this part is to use machine learning to enable automatic measurement of nanoparticle shape from expert a-priori information only. No physical model will be used as a-priori information in this task.
The accuracy and traceability of the size results obtained by each technique will be analyzed and compared with the physical modelling. A machine learning database will then be used to create automatic detection algorithms.
Metal nanoparticles have a substantial impact across diferent felds of science, such as photochemistry, energy conversion, and medicine. Among the commonly used nanoparticles, silver nanoparticles are of special interest due to their antibacterial properties and applications in sensing and catalysis. However, many of the methods used to synthesize silver nanoparticles often do not result in well-defned products, the main obstacles being high polydispersity or a lack of particle size tunability. We describe an automated approach to on-demand synthesis of adjustable particles with mean radii of 3 and 5 nm using the polyol route. The polyol process is a promising route for silver nanoparticles e.g., to be used as reference materials. We characterised the as-synthesized nanoparticles using small-angle X-ray scattering, dynamic light scattering and further methods, showing that automated synthesis can yield colloids with reproducible and tuneable properties.
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.
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.
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.