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Iron nitride (Fe3N) and iron carbide (Fe3C) nanoparticles can be prepared via sol−gel synthesis. While sol−gel methods are simple, it can be difficult to control the crystalline composition, i.e., to achieve a Rietveld-pure product. In a previous in situ synchrotron study of the sol−gel synthesis of Fe3N/Fe3C, we showed that the reaction proceeds as follows:
Fe3O4 → FeOx → Fe3N → Fe3C. There was considerable overlap between the different phases, but we were unable to ascertain whether this was due to the experimental setup (side-on heating of a quartz capillary which could lead to thermal gradients) or whether individual particle reactions proceed at different rates. In this paper, we use in situ wide- and small-angle X-ray scattering (wide-angle X-ray scattering (WAXS) and small-angle X-ray scattering (SAXS)) to demonstrate that the overlapping phases are indeed due to variable reaction rates. While the initial oxide nanoparticles have a small range of diameters, the size range expands considerably and very rapidly during the oxide−nitride transition. This has implications for the isolation of Rietveld-pure Fe3N, and in an extensive laboratory study, we were indeed unable to isolate phasepure Fe3N. However, we made the surprising discovery that Rietveld-pure Fe3C nanoparticles can be produced at 500 °C with a sufficient furnace dwell time. This is considerably lower than the previous reports of the sol−gel synthesis of Fe3C nanoparticles.
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.
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.
Aqueous Dispersions of Polypropylene: Toward Reference Materials for Characterizing Nanoplastics
(2023)
Microplastics and nanoplastics pollute the natural environment all over the world, but the full extent of the hazards posed by this waste is unclear. While research on microplastics is well advanced, little work has been done on nanoplastics. This discrepancy is mainly due to the lacking ability to detect nanoplastics in biologically and environmentally relevant matrices. Nanoplastics reference materials can help the development of suitable methods for identifying and quantifying nanoplastics in nature. The aim is to synthesize nanoplastics made from one of the most commonly used plastics, namely polypropylene. An easy way to produce long-term stable aqueous dispersions of polypropylene nanoparticles (nano polypropylene) is reported. The nanoplastic particles, prepared by mechanical breakdown, show a mean hydrodynamic diameter of D h = 180.5 ± 5.8 nm and a polydispersity index of PDI = 0.084 ± 0.02. No surfactant is needed to obtain dispersion which is stable for more than 6 months. The colloidal stability of the surfactant-free nano polypropylene dispersions is explained by their low zeta potential of 𝜻 = −43 ± 2 mV.
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.
This paper reports a systematic study into the effect of nitrogen on iron-catalyzed graphitization of biomass. Chitin, chitosan, N-acetylglucosamine, gelatin and glycine were selected to represent nitrogen-rich saccharides and amino-acid/polypeptide biomass precursors. The materials were pyrolyzed with an iron catalyst to produce carbons with a wide range of chemical and structural features such as mesoporosity and nitrogen-doping. Many authors have reported the synthesis of nitrogen-doped carbons by pyrolysis and these have diverse applications. However, this is the first systematic study of how nitrogen affects pyrolysis of biomass and importantly the catalytic graphitization step. Our data demonstrates that nitrogen inhibits graphitization but that some nitrogen survives the catalytic graphitization process to become incorporated into various chemical environments in the carbon product.
The production of plastics is rising since they have been invented. Micro, submicro- and nanoplastics are produced intentionally or generated by environmental processes, and constitute ubiquitous contaminants which are ingested orally by consumers. Reported health concerns include intestinal translocation, inflammatory response, oxidative stress and cytotoxicity. Every digestive milieu in the gastrointestinal tract does have an influence on the properties of particles and can cause changes in their effect on biological systems. In this study, we subjected plastic particles of different materials (polylactic acid, polymethylmethacrylate, melamine formaldehyde) and sizes (micro- to nano-range) to a complex artificial digestion model consisting of three intestinal fluid simulants (saliva, gastric and intestinal juice). We monitored the impact of the digestion process on the particles by performing Dynamic Light Scattering, Scanning Electron Microscopy and Asymmetric Flow Field-Flow Fractionation. An in vitro model of the intestinal epithelial barrier was used to monitor cellular effects and translocation behavior of (un)digested particles. In conclusion, artificial digestion decreased cellular interaction and slightly increased transport of all particles across the intestinal barrier. The interaction with organic matter resulted in clear differences in the agglomeration behavior. Moreover, we provide evidence for polymer-, size- and surface-dependent cellular effects of the test particles.
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 %, respectively. Due to the added complexity of the structure factor, much 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.
Zinc oxide nanostructures possess optical properties that are dependent on particle shape and size. Here, we report on the synthesis of elongated zinc oxide tubes via the in-situ aggregation of spherical particles. Using a custom-built, lab-based instrument, x-ray scattering can be investigated over more than three decades in scattering vector q, allowing for a complete investigation from atomic distances up to larger-than-nano structures.
For this study, the hydrolytic synthesis of stearate stabilized zinc oxide nanostructures in tetrahydrofuran was performed and the reaction mixture was continuously fed through the SAXS/WAXS apparatus by means of a peristaltic pump. For comparison to nanospheres, oleate-functionalized zinc oxide particles were synthesized in a microwave-assisted fashion, and depending on reaction temperature, sphere radii could be adjusted between 2.6 and 3.8 nm, changing the optical and crystal lattice properties.
The evaluation of the in-situ measurements showed that at the beginning of the synthesis of the stearate-stabilized zinc oxide, similar, spherical particles are formed as in the oleate-based synthesis. In contrast, as the reaction progresses, the stearate-capped particles aggregate into elongated rods with radii of a few nanometres, which eventually form the nanotubes. These have radii of 30-50 nm and lengths of several hundred nanometres. Nevertheless, these structures still possess optical properties like the ultra-small zinc oxide spheres, i.e. a bright, yellow fluorescence. Therefore, we assume that the originally formed, ultra-small spheres, are still present within the tube structure, but separated by stearate, and thus determine their fluorescence properties.
We report on ultrasmall zinc oxide single-crystalline nanoparticles of narrow size distribution and long-term colloidal stability. These oleate-stabilized nanoparticles were synthesized using microwave-assisted synthesis for 5 min, corresponding to a 99% decrease in synthesis time, when compared to the conventional synthesis method. It was observed that the average particle radius increases from 2.6 ± 0.1 to 3.8 ± 0.1 nm upon increasing synthesis temperature from 125 to 200 °C. This change also corresponded to observed changes in the optical band gap and the fluorescence energy of the particles, from 3.44 ± 0.01 to 3.36 ± 0.01 eV and from 2.20 ± 0.01 to 2.04 ± 0.01 eV, respectively. Small-angle X-ray scattering, dynamic light scattering, and UV–vis and fluorescence spectroscopy were employed for particle characterization. Debye–Scherrer analysis of the X-ray diffraction (XRD) pattern reveals a linear increase of the crystallite size with synthesis temperature. The consideration of the convolution of a Lorentz function with a Gaussian function for data correction of the instrumental peak broadening has a considerable influence on the values for the crystallite size. Williamson–Hall XRD analyses in the form of the uniform deformation model, uniform stress deformation model, and uniform deformation energy density model revealed a substantial increase of strain, stress, and deformation energy density of the crystallites with decreasing size. Exponential and power law models were utilized for quantification of strain, stress, and deformation energy density.