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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.
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.
Due to their unique physico-chemical properties, nanoparticles are well established in research and industrial applications. A reliable characterization of their size, shape, and size distribution is not only mandatory to fully understand and exploit their potential and develop reproducible syntheses, but also to manage environmental and health risks related to their exposure and for regulatory requirements. To validate and standardize methods for the accurate and reliable particle size determination nanoscale reference materials (nanoRMs) are necessary. However, there is only a very small number of nanoRMs for particle size offered by key distributors such as the National Institute of Standards and Technology (NIST) and the Joint Research Centre (JRC) and, moreover, few provide certified values. In addition, these materials are currently restricted to polymers, silica, titanium dioxide, gold and silver, which have a spherical shape except for titania nanorods. To expand this list with other relevant nanomaterials of different shapes and elemental composition, that can be used for more than one sizing technique, we are 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 for the material and life sciences.
Nanoparticles (NPs) have become important materials for a variety of chemical technologies, including catalysis. One of the main challenges is the reduction of green house gases, such as CO2. One opportunity besides the capturing is the conversion to synthesis gas via the reverse water-gas shift reaction.
A facile and efficient method is described for the solvothermal synthesis of size-tunable, stable, and uniform NiCu core-shell NPs. The diameter of the NPs can be tuned in a range from 6 nm to 30 nm and the Ni:Cu ratio from 30:1 to 1:1. The NPs are structurally characterized with combination of transmission electron microscopy, anomalous small-angle X-ray scattering, X-ray photoelectron spectroscopy, and X-ray absorption fine structure. Using these analytical methods, a core-shell-shell structure their chemical composition is elucidated. A depletion from the core to the shell is observed, with the core consisting of NiCu alloy, surrounded by an inner Ni-rich shell and an outer NiO shell. The SiO2-supported NiCu core-shell NPs show pronounced selectivity of >99% for CO in the catalytic reduction of CO2 to CO using hydrogen as reactant (reverse water–gas shift reaction).
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.
Core–shell nanoparticles have attracted much attention in recent years due to their unique properties and their increasing importance in many technological and consumer products. However, the chemistry of nanoparticles is still rarely investigated in comparison to their size and morphology. In this review, the possibilities, limits, and challenges of X-ray photoelectron spectroscopy (XPS) for obtaining more insights into the composition, thickness, and homogeneity of nanoparticle coatings are discussed with four examples: CdSe/CdS quantum dots with a thick coating and a small core; NaYF4-based upconverting nanoparticles with a large Yb-doped core and a thin Er-doped coating; and two types of polymer nanoparticles with a poly(tetrafluoroethylene) core with either a poly(methyl methacrylate) or polystyrene coating. Different approaches for calculating the thickness of the coating are presented, like a simple numerical modelling or a more complex simulation of the photoelectron peaks. Additionally, modelling of the XPS background for the investigation of coating is discussed. Furthermore, the new possibilities to measure with varying excitation energies or with hard-energy X-ray sources (hard-energy X-ray photoelectron spectroscopy) are described. A discussion about the sources of uncertainty for the determination of the thickness of the coating completes this review.
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 facile and efficient methodology is described for the solvothermal synthesis of size-tunable, stable, and uniform NiCu core–shell nanoparticles (NPs) for application in catalysis. The diameter of the NPs is tuned in a range from 6 nm to 30 nm and to adjust the Ni:Cu ratio from 30:1 to 1:1. Furthermore, the influence of different reaction parameters on the final NPs is studied. The NPs are structurally characterized by a method combination of transmission electron microscopy, anomalous small-angle X-ray scattering, X-ray absorption fine structure, and X-ray photoelectron spectroscopy. Using these analytical methods, it is possible to elucidate a core–shell–shell structure of all particles and their chemical composition. In all cases, a depletion from the core to the shell is observed, with the core consisting of NiCu alloy, surrounded by an inner Ni-rich shell and an outer NiO shell. The SiO2-supported NiCu core–shell NPs show pronounced selectivity of >99% for CO in the catalytic reduction of CO2 to CO using hydrogen as reactant (reverse water–gas shift reaction) independent of size and Ni:Cu ratio.
The roughness as a property of core–shell (CS) microparticles plays a key role in their functionality. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task with approaches using electron microscopy images being scarce and showing pronounced differences in terms of methodology and results. This work presents a generalized method for the reliable roughness determination of nonplanar specimens such as CS particles from electron microscopic images, the method being robust and reproducible with a high accuracy. It involves a self-written software package (Python) that analyzes the recorded images, extracts corresponding data, and calculates the roughness based on the deviation of the identified contour. Images of single particles are taken by a dual mode scanning electron microscopy (SEM) setup which permits imaging of the same field-of-view of the sample with high resolution and surface sensitive in SE InLens mode as well as in transmission mode (TSEM). Herein, a new type of polystyrene core–iron oxide shell–silica shell particles is developed to serve as a set of lower micrometer-sized study objects with different surface roughness; the analysis of their images by the semiautomatic workflow is demonstrating that the particles’ profile roughness can be quantitatively obtained.
Reliable characterization of materials at the nanoscale regarding their physio-chemical properties is a challenging task, which is important when utilizing and designing nanoscale materials. Nanoscale materials pose a potential toxicological hazard to the environment and the human body. For this reason, the European Commission amended the REACH Regulation in 2018 to govern the classification of nanomaterials, relying on number-based distribution of the particle size.
Suitable methods exist for the granulometric characterization of monodisperse and ideally shaped nanoparticles. However, the evaluation of commercially available nanoscale powders is problematic. These powders tend to agglomerate, show a wide particle size distribution and are of irregular particle shape.
Zinc oxide, aluminum oxide and cerium oxide with particle sizes less than 100 nm were selected for the studies and different preparation methods were used comparatively.
First, the nanoparticles were dispersed in different dispersants and prepared on TEM-supported copper grids. Furthermore, individual powders were deposited on carbon-based self-adhesive pads. In addition, the samples were embedded by hot mounting and then ground and polished.
The prepared samples were investigated by scanning electron microscopy (including the transmission mode STEM-in-SEM) and Dynamic Light scattering. The software package ImageJ was used to segment the SEM images and obtain the particle sizes and shapes and finally the number-based particles size distribution with size expressed as various descriptors.