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These are four datasets that were made available to the participants of the Small-angle Scattering data analysis round robin. The intent was to find out how comparable results from different researchers are, who analyse exactly the same processed, corrected dataset.
In this repository, there are:
1) a PDF document with more details for the study,
2) the datasets for people to try and fit,
3) an Excel spreadsheet to document the results.
Datasets 1 and 2 were modified from: Deumer, Jerome, & Gollwitzer, Christian. (2022). npSize_SAXS_data_PTB (Version 5) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5886834
Datasets 3 and 4 were collected in-house on the MOUSE instrument.
This dataset is a complete set of raw, processed and analyzed data, associated with the manuscript mentioned in the title.
All associated metadata and processing history has been added. Particle size distribution analyses using McSAS are included as well.
The samples consisted of a 4.2 mass% dispersion of yttria-stabilized zirconia nanoparticles in a cross-linked matrix. The measurements show a good dispersion with minimal agglomeration. The wide-angle region shows diffraction information consistent with zirconia.
Wide-range X-ray scattering datasets and analyses for all samples described in the 2020 publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup". These datasets are composed by combining multiple small-angle x-ray scattering and wide-angle x-ray scattering curves into a single dataset. They have been analyzed using McSAS to extract polydispersities and volume fractions. They have been collected using the MOUSE project (instrument and methodology).
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.
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.
Though the reinforcing properties of inorganic particles in thermosetting nanocomposites, has been exploited, the integration of nanoparticles continues to be challenging in terms of their homogeneous distribution and their manipulation which can contribute to occupational hazards. Due to a second encapsulations of nanoparticles, electrospun nanocomposite fibers containing nanoparticles might be an alternative for overcoming these issues, as the fiber nonwovens contains the nanoparticles allowing for safer manipulation. Here, the morphology, and the thermal properties of electrospun polycarbonate fibers containing taurine modified boehmite nanoparticles (BNP) are investigated by means of small and wide-angle X-ray scattering as well as fast scanning and temperature modulated fast scanning calorimetry for the first time. The latter techniques allow the investigation of the thermal properties of single fibers at heating rates up to 10^4 K s^-1 keeping its structure intact. A quantitative analysis of the scattering data reveals a porous structure of the fibers. The porous structure is quantified regarding the pore volume and the pore size. A constant amount of aggregation is found even for the highly BNP loaded fibers. Thermal analysis on the fibers reveals a rigid amorphous fraction (RAF) where it is known that RAF determinates the properties of a nanocomposite to a large extent. For the fibers RAF amounts up to 40 wt%, which is essential higher compared to equally formulated PC/BNP composite cast films. The RAF in the case of the fibers, is not only due to the presence of particles in the polymer but also due to orientation effects induced by the electrospinning process.
In recent years, we have come to appreciate the astounding intricacies associated with the formation of minerals from ions in aqueous solutions. In this context, a number of studies have revealed that the nucleation of calcium sulfate systems occurs nonclassically, involving the aggregation and reorganization of nanosized prenucleation species. In recent work, we have shown that this particle-mediated nucleation pathway is actually imprinted in the resultant micrometer-sized CaSO4 crystals. This property of CaSO4 minerals provides us with the unique opportunity to search for evidence of nonclassical nucleation pathways in geological environments.
In particular, we focused on large anhydrite Crystals extracted from the Naica Mine in Mexico. We were able to shed light on this mineral's growth history by mapping defects at different length scales. Based on this, we argue that the nanoscale misalignment of the structural subunits, observed in the initial calcium sulfate crystal seeds, propagates through different length scales both in morphological, as well as in strictly crystallographic aspects, eventually causing the formation of large mesostructured single crystals of anhydrite. Hence, the nonclassical nucleation mechanism introduces a “seed of imperfection,” which leads to a macroscopic “single” crystal whose fragments do not fit together at different length scales in a self-similar manner. Consequently, anisotropic voids of various sizes are formed with very welldefined walls/edges. However, at the same time, the material retains in part its single crystal nature.
Herein, we provide a "systems architecture"-like overview and detailed discussions of the methodological and instrumental components that, together, comprise the "MOUSE" project (Methodology Optimization for UltrafineStructure Exploration). The MOUSE project provides scattering information on a wide variety of samples, with traceable dimensions for both the scattering vector (q) and the absolute scattering cross-section (I). The measurable scattering vector-range of 0.012≤ q (nm-1) ≤ 92, allows information across a hierarchy of structures with dimensions ranging from ca. 0.1 to 400 nm. In addition to details that comprise the MOUSE project, such as the organisation and traceable aspects, several representative examples are provided to demonstrate its flexibility. These include measurements on alumina membranes, the tobacco mosaic virus, and dual-source information that overcomes fluorescence limitations on ZIF-8 and iron-oxide-containing carbon catalyst materials.
Epoxy nanocomposites are promising materials for industrial applications (i.e., aerospace, marine and automotive industry) due to their extraordinary mechanical and thermal properties. Here, the effect of hollow halloysite nanotubes (HNT) on an epoxy matrix (Ep) was the focus of the study. The structure and molecular mobility of the nanocomposites were investigated using a combination of X-ray scattering, calorimetry (differential (DSC) and fast scanning calorimetry (FSC)) and dielectric spectroscopy. Additionally, the effect of surface modification of HNT (polydopamine (PDA) and Fe(OH)3 nanodots) was considered. For Ep/HNT, the glass transition temperature (Tg) is was de-creased due to a nanoparticle-related decrease of the crosslinking density. For the modified system, Ep/m-HNT, the surface modification resulted in enhanced filler–matrix interactions leading to higher Tg values than the pure epoxy in some cases. For Ep/m-HNT, the amount of interface formed between the nanoparticles and the matrix ranged from 5% to 15%. Through BDS measurements, localized fluctuations were detected as a β- and γ-relaxation, related to rotational fluctuations of phenyl rings and local reorientations of unreacted components. A combination of calorimetry and BDS dielectric spectroscopy revealed a dynamic and structural heterogeneity of the matrix, as confirmed by two glassy dynamics in both systems, related to regions with different crosslinking densities.