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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
Calcium sulfate minerals are abundant in natural and engineered environments and they exist in the form of three hydrates: gypsum (CaSO4·2H2O), bassanite (CaSO4·0.5H2O), and anhydrite (CaSO4). Due to their relevance in natural and industrial processes, the formation pathways of these calcium sulfate phases from aqueous solution have been the subject of intensive research1.
The state-of-the-art of the calcium sulfate formation mechanisms builds upon and goes beyond what we have come to appreciate in the astounding intricacy of other mineral formation processes from ions in aqueous solutions. The original, and rather naive, 'textbook' image of these phenomena, stemming from the adaptation of classical nucleation and growth theories, has increased in complexity due to the discovery of a variety of precursor and intermediate species2. These include solute clusters (e.g. prenucleation clusters, PNCs), liquid(-like) phases, as well as amorphous and nanocrystalline solids etc.. In this context, a number of studies have already revealed that nucleation in the CaSO4-H2O system is non-classical, where the formation of the different crystalline phases involves several steps including a common amorphous precursor1, 3, 4.
In this contribution we show that the formation of the amorphous phase involves the aggregation of small primary particles into larger disordered aggregates exhibiting a "brick-in-the-wall" structure5, 6. The actual crystallization occurs by the restructuring and coalescence of the particles ("bricks") into a given calcium sulfate phase depending on the physicochemical conditions of the solution. Importantly, the rearrangement process does not continue until a (nearly-)perfect homogeneous single crystal is obtained. Instead it comes to a stop, or at least significantly slows down. Such a process thus yields a final imperfect mesocrystal, composed of smaller domains rather than a continuous crystal structure, within which the domains are separated by an amorphous (i.e. less ordered) calcium sulfate phase.
Hence, the non-classical crystallization process of CaSO4 yields a final imperfect mesocrystal with an overall morphology resembling that of a single crystal, yet composed of smaller nano-domains. Importantly, these observations reveal that organic-free calcium sulfate mesocrystals grown by a particle mediated-pathway preserve in the final crystal structure a “memory” or “imprint” of their non-classical nucleation process, something that has been overlooked until now. Furthermore, the nano-scale misalignment of the structural sub-units within these crystals can propagate through the length-scales, and be expressed macroscopically as misaligned zones/domains in large single crystals. Indeed, by considering large anhydrite crystals from the famous Naica Mine (“Cueva de los cristales”) we observed a suite of correlated self-similar void defects spanning multiple length-scales7. These flaws, in the macroscopic crystal, stem from “seeds of imperfection” originating from a particle-mediated nucleation pathway. Hence, building a crystal could be viewed as Nature stacking blocks in a game of Tetris, whilst slowly forgetting the games core concept and failing to fill rows completely.
Models for TOPAS/Geant4 to estimate the microscopic dose received by biomolecules during bioSAXS experiments.
The C++ classes in this repository extend the functionality of the TOPAS (http://www.topasmc.org/) Monte-Carlo program, which is itself a wrapper of the Geant4 MCS Toolkit (http://geant4.org).
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.
One aim of the EMPIR nPSize project 17NRM04 was to develop and validate three classes of candidate reference (test) materials (RTMs), with i) well-defined non-spherical shape, ii) relatively high polydispersity index, and iii) accurate particle concentrations.
To fulfil the requirements of the project, 11 different types of materials were prepared. Following the initial assessment of the materials suitability, nPSize5_PT_UNITO, nPSize6_AC_UNITO and nPSize7_GN_CEA materials were found unsuitable for the project, due to various reasons. PT material was deemed unsuitable due to its predominantly agglomerated nature. AC material contained relatively high amount of impurities (other particle forms). GN material was found too heterogeneous in both the length and width for the purpose of the project. The remaining 8 candidate RTMs were assessed for their homogeneity and stability and used for successful delivery of the associated activities within the nPSize project.
BAM is currently building up a platform of novel nanoRMs relying on iron oxide nanoparticles of different shape, size and surface chemistry. Iron oxide was chosen as a core material because of its relevance to the material and life sciences.
As a first candidate of this series, we present cubic iron oxide nanoparticles with a nominal edge length of 8 nm. These particles were synthesized by thermal decomposition of iron oleate in high boiling organic solvents adapting well-known literature procedures. After dilution to a concentration suitable for electron microscopy (TEM and SEM) as well as for small-angle X-ray scattering (SAXS) measurements, the candidate nanoRM was bottled and assessed for homogeneity and stability by both methods following the guidelines of ISO 17034 and ISO Guide 35.
The particle sizes obtained by both STEM-in-SEM and TEM are in excellent agreement with a minimum Feret of 8.3 nm ± 0.7 nm. The aspect ratio (AR) of the iron oxide cubes were extracted from the images as the ratio of minimum Feret to Feret resulting in an AR of 1.18 for TEM to 1.25 for SEM. Alternatively, a rectangular bounding box was fitted originating from the minimum Feret and the longest distance through the particle in perpendicular direction. This led to AR values of 1.05 for TEM and 1.12 for SEM, respectively. The results confirm the almost ideal cubic shape.