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A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
SASfit 0.94.12
(2023)
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.
In contrast to the crisp, clear images you can get from electron microscopy, small-angle X-ray scattering (SAXS) patterns are rather featureless. These patterns, however, contain averaged structural information of all of the finest material structures that were illuminated by the X-ray beam. With careful and precise investigation, and supplementary information from complementary techniques, this bulk material structure can be quantified to reveal structural information spanning four or even five decades in size. Additionally, while the data correction and analysis is complex, sample preparation is very straightforward, also allowing for in-situ and operando measurements to be performed without breaking a sweat. In the right hands, then, this technique can be the most powerful tool in your analytical arsenal.
Small-angle scattering (SAS) offers a reliable route to characterize the nanostructure of large amounts of material with a minimum of tedium, for example, easily extracting size distributions and volume fractions. There are a variety of analysis programs available while the evaluation of SAS measurements has been dominated by the classical curve fitting approach. SASfit represents such a classical curve fitting toolbox: it is one of the mature programs for SAS data analysis and has been available and used for many years. The latest developments will be presented and a scattering function of a mass fractal model of branched polymers in solution is provided as an example for implementing a plug-in.
Alternatively to classical curve fitting, part two presents the latest developments of the user-friendly open-source Monte Carlo regression package McSAS. The form-free Monte Carlo nature of McSAS means, it is not necessary to provide further restrictions on the mathematical form of the parameter distribution: without prior knowledge, McSAS is able to extract complex multimodal or odd- shaped parameter distributions from SAS data. The headless mode is presented by an example of operation within interactive programming environments such as a Jupyter notebook.
Metal carbides have shown great promise in a wide range of applications due to their unique catalytic, electrocatalytic and magnetic properties. However, the scalable production of dispersible metal carbide nanoparticles remains a challenge. Here, we report a simple and scalable route to dispersible iron carbide (Fe3C) nanoparticles. This uses MgO nanoparticles as a removable ‘cast’ to synthesize Fe3C nanoparticles from Prussian blue (KFeIII[FeII(CN)6]). Electron tomography demonstrates how nanoparticles of the MgO cast encase the Fe3C nanoparticles to prevent sintering and agglomeration during the high-temperature synthesis. The MgO cast is readily removed with ethylenediaminetetraacetic acid (EDTA) to generate Fe3C nanoparticles that can be used to produce a colloidal ferrofluid or dispersed on a support material.
Structural modularity of polymer frameworks is a key advantage of covalent organic polymers, however, only C, N, O, Si and S have found their way into their building blocks so far. Here, we expand the toolbox available to polymer and materials chemists by one additional nonmetal, phosphorus. Starting with a building block that contains a λ⁵‐phosphinine (C₅P) moiety, we evaluate a number of polymerisation protocols, finally obtaining a π‐conjugated, covalent phosphinine‐based framework (CPF‐1) via Suzuki‐Miyaura coupling. CPF‐1 is a weakly porous polymer glass (72.4 m2 g‐1 N2 BET at 77 K) with green fluorescence (λmax 546 nm) and extremely high thermal stability. The polymer catalyzes hydrogen evolution from water under UV and visible light irradiation without the need for additional co‐catalyst at a rate of 33.3 μmol h‐¹ g‐¹. Our results demonstrate for the first time the incorporation of the phosphinine motif into a complex polymer framework. Phosphinine‐based frameworks show promising electronic and optical properties that might spark future interest in their applications in light‐emitting devices and heterogeneous catalysis.
Ever since increasing a reaction’s yield while shortening the reaction time is the main objective in synthesis optimization. Microwave reactors meet these demands. In literature however their usage is under discussion due to claims of the existence of non-thermal effects resulting from the microwave radiation. Especially for nano-material syntheses it is of crucial importance to be aware of influences on the reaction pathway. Therefore, we compare ultra-small silver nanoparticles with mean radii of 3 nm, synthesized via conventional and microwave heating. We employed a versatile one-pot polyol synthesis of poly(acrylic acid) (PAA) stabilized silver nanoparticles, which display superior catalytic properties. No microwave specific effects in terms of particle size distribution characteristics, as derived by small-angle X-ray scattering (SAXS) and dynamic light scattering (DLS), are revealed. Due to the microwave reactor’s characteristics of a closed system, syntheses can be carried out at temperatures beyond the solvent’s boiling point. Particle formation was accelerated by a factor of 30 by increasing the reaction temperature from 200 °C to 250 °C. The particle growth process follows a cluster coalescence mechanism. A post-synthetic incubation step at 250 °C induces a further growth of the particles while the size distribution broadens. Thus, utilization of microwave reactors enables an enormous decrease of the reaction time as well as the opportunity of tuning the particles’ size. Possibly, decomposition of the stabilizing ligand at elevated temperatures results in reduced yields. A temperature of 250 °C and a corresponding reaction time of 30 s represent a compromise between short reaction times and high yields.