Abstract: Graphene, having all atoms on its surface, is favorable to extend the functions by introducing the spin–orbit coupling and magnetism through proximity effect. Here, we report the tunable interfacial exchange field produced by proximity coupling in graphene/BiFeO3 heterostructures. The exchange field has a notable dependence with external magnetic field, and it is much larger under negative magnetic field than that under positive magnetic field. For negative external magnetic field, interfacial exchange coupling gives rise to evident spin splitting for N ≠ 0 Landau levels and a quantum Hall metal state for N = 0 Landau level. Our findings suggest graphene/BiFeO3 heterostructures are promising for spintronics.

Abstract: The major mechanism responsible for plasmonic enhancement of titanium dioxide photocatalysis using gold nanoparticles is still under contention. This work introduces an experimental strategy to disentangle the significance of the charge transfer and near-field mechanisms in plasmonic photocatalysis. By controlling the thickness and conductive nature of a nanoparticle shell that acts as a spacer layer separating the plasmonic metal core from the TiO2 surface, field enhancement or charge transfer effects can be selectively repressed or evoked. Layer-by-layer and in situ polymerization methods are used to synthesize gold core–polymer shell nanoparticles with shell thickness control up to the sub-nanometer level. Detailed optical and electrical characterization supported by near-field simulation models corroborate the trends in photocatalytic activity of the different systems. This approach mainly points at an important contribution of the enhanced near field.

Abstract: Tubular ZnO – Co3O4 nanofibers were co-electrospun from polymer solution containing zinc and cobalt acetates. Phase composition, cobalt electronic state and element distribution in the fibers were investigated by XRD, SEM, HRTEM, HAADF-STEM with EDX mapping, and XPS. Bare ZnO has high selective sensitivity to NO and NO2, while ZnO-Co3O4 composites demonstrate selective sensitivity to H2S in dry and humid air. This effect is discussed in terms of transformation of cobalt oxides into cobalt sulfides and change in the acidity of ZnO oxide surface upon cobalt doping. Reduction in response and recovery time is attributed to the formation of a tubular structure facilitating gas transport through the sensitive layer.

Abstract: The chemical composition, nanostructure and electronic structure of nanosized oxide scales naturally formed on the surface of AISI 316L stainless steel microfibres used for strengthening of composite materials have been characterised using a combination of scanning and transmission electron microscopy with energy-dispersive X-ray, electron energy loss and Auger spectroscopy. The analysis reveals the presence of three sublayers within the total surface oxide scale of 5.0-6.7 nm thick: an outer oxide layer rich in a mixture of FeO.Fe2 O3 , an intermediate layer rich in Cr2 O3 with a mixture of FeO.Fe2 O3 and an inner oxide layer rich in nickel.

Abstract: We describe the simple, scalable, single-step, and polar-solvent-free synthesis of high-quality colloidal CsPbX3 (X=Cl, Br, and I) perovskite nanocrystals (NCs) with tunable halide ion composition and thickness by direct ultrasonication of the corresponding precursor solutions in the presence of organic capping molecules. High angle annular dark field scanning transmission electron microscopy (HAADF-STEM) revealed the cubic crystal structure and surface termination of the NCs with atomic resolution. The NCs exhibit high photoluminescence quantum yields, narrow emission line widths, and considerable air stability. Furthermore, we investigated the quantum size effects in CsPbBr3 and CsPbI3 nanoplatelets by tuning their thickness down to only three to six monolayers. The high quality of the prepared NCs (CsPbBr3) was confirmed by amplified spontaneous emission with low thresholds. The versatility of this synthesis approach was demonstrated by synthesizing different perovskite NCs.

Abstract: Recent progress in materials synthesis enabled fabrication of superconducting atomically flat single-crystalline metallic nanofilms with thicknesses down to a few monolayers. Interest in such nano-thin systems is attracted by the dimensional 3D-2D crossover in their coherent properties which occurs with decreasing the film thickness. The first fundamental aspect of this crossover is dictated by the Mermin-Wagner-Hohenberg theorem and concerns frustration of the long-range order due to superconductive fluctuations and the possibility to track its impact with an unprecedented level of control. The second important aspect is related to the Fabri-Perot modes of the electronic motion strongly bound in the direction perpendicular to the nanofilm. The formation of such modes results in a pronounced multiband structure that changes with the nanofilm thickness and affects both the mean-field behavior and superconductive fluctuations. Though the subject is very rich in physics, it is scarcely investigated to date. The main obstacle is that there are no manageable models to study a complex magnetic response in this case. Full microscopic consideration is rather time consuming, if practicable at all, while the standard Ginzburg-Landau theory is not applicable. In the present work we review the main achievements in the subject to date, and construct and justify an efficient multiband mean-field formalism which allows for numerical and even analytical treatment of nano-thin superconductors in applied magnetic fields.

Abstract: We present a time-dependent parametric model for reactive HiPIMS deposition of films. Specific features of HiPIMS discharges and a possible increase in the density of the reactive gas in front of the reactive gas inlets placed between the target and the substrate are considered in the model. The model makes it possible to calculate the compound fractions in two target layers and in one substrate layer, and the deposition rate of films at fixed partial pressures of the reactive and inert gas. A simplified relation for the deposition rate of films prepared using a reactive HiPIMS is presented. We used the model to simulate controlled reactive HiPIMS depositions of stoichiometric ZrO2 films, which were recently carried out in our laboratories with two different configurations of the O2 inlets in front of the sputtered target. The repetition frequency was 500 Hz at the deposition-averaged target power densities of 5 Wcm−2 and 50 Wcm−2 with a pulse-averaged target power density up to 2 kWcm−2. The pulse durations were 50 μs and 200 μs. Our model calculations show that the to-substrate O2 inlet provides systematically lower compound fractions in the target surface layer and higher compound fractions in the substrate surface layer, compared with the to-target O2 inlet. The low compound fractions in the target surface layer (being approximately 10% at the depositionaveraged target power density of 50 Wcm−2 and the pulse duration of 200 μs) result in high deposition rates of the films produced, which are in agreement with experimental values.

Abstract: Korund-artiges ε-Mn2O3 und Perowskit-artiges ζ-Mn2O3, zwei neue Phasen von Mn2O3, wurden unter hohen Drücken bei hohen Temperaturen synthetisiert. Die Manganatome können vollständig die A- und B-Positionen der Perowskitstruktur besetzen. ζ-Mn2O3 (siehe Bild, A-Positionsordnung) enthält Mn in den drei Oxidationsstufen +II, +III und +IV.

Abstract: Antiferromagnetic(AFM)|ferrimagnetic(FiM) core|shell (CS) nanoparticles (NPs) of formula Co0.3Fe0.7O|Co0.6Fe2.4O4 with mean diameter from 6 to 18 nm have been synthesized through a one-pot thermal decomposition process. The CS structure has been generated by topotaxial oxidation of the core region, leading to the formation of a highly monodisperse single inverted AFM|FiM CS system with variable AFM-core diameter and constant FiM-shell thickness (~2 nm). The sharp interface, the high structural matching between both phases and the good crystallinity of the AFM material have been structurally demonstrated and are corroborated by the robust exchange-coupling between AFM and FiM phases, which gives rise to one among the largest exchange bias (HE) values ever reported for CS NPs (8.6 kOe) and to a strongly enhanced coercive field (HC). In addition, the investigation of the magnetic properties as a function of the AFM-core size (dAFM), revealed a non-monotonous trend of both HC and HE, which display a maximum value for dAFM = 5 nm (19.3 and 8.6 kOe, respectively). These properties induce a huge improvement of the capability of storing energy of the material, a result which suggests that the combination of highly anisotropic AFM|FiM materials can be an efficient strategy towards the realization of novel Rare Earth-free permanent magnets.

Abstract: In this work we study energy transport in a gliding arc discharge with two diverging flat
electrodes in argon gas at atmospheric pressure. The discharge is ignited at the shortest electrode
gap and it is pushed downstream by a forced gas flow. The current values considered are
relatively low and therefore a non-equilibrium plasma is produced. We consider two cases, i.e.
with high and low discharge current (28 mA and 2.8mA), and a constant gas flow of 10 lmin −1 ,
with a significant turbulent component to the velocity. The study presents an analysis of the
various energy transport mechanisms responsible for the redistribution of Joule heating to the
plasma species and the moving background gas. The objective of this work is to provide a
general understanding of the role of the different energy transport mechanisms in arc formation
and sustainment, which can be used to improve existing or new discharge designs. The work is
based on a three-dimensional numerical model, combining a fluid plasma model, the shear stress
transport Reynolds averaged Navier–Stokes turbulent gas flow model, and a model for gas
thermal balance. The obtained results show that at higher current the discharge is constricted
within a thin plasma column several hundred kelvin above room temperature, while in the low-
current discharge the combination of intense convective cooling and low Joule heating prevents
discharge contraction and the plasma column evolves to a static non-moving diffusive plasma,
continuously cooled by the flowing gas. As a result, the energy transport in the two cases is
determined by different mechanisms. At higher current and a constricted plasma column, the
plasma column is cooled mainly by turbulent transport, while at low current and an unconstricted
plasma, the major cooling mechanism is energy transport due to non-turbulent gas convection. In
general, the study also demonstrates the importance of turbulent energy transport in
redistributing the Joule heating in the arc and its significant role in arc cooling and the formation
of the gas temperature profile. In general, the turbulent energy transport lowers the average gas
temperature in the arc, thus allowing additional control of thermal non-equilibrium in the
discharge.

Abstract: Pt nanoparticles play an essential role in a wide variety of catalytic reactions. The activity of the particles strongly depends on their three-dimensional (3D) structure and exposed facets, as well as on the reactive environment. High-resolution electron microscopy has often been used to characterize nanoparticle catalysts but unfortunately most observations so far have been either performed in vacuum and/or using conventional (2D) in situ microscopy. The latter however does not provide direct 3D morphological information. We have implemented a quantitative methodology to measure variations of the 3D atomic structure of nanoparticles under the flow of a selected gas. We were thereby able to quantify refaceting of Pt nanoparticles with atomic resolution during various oxidation−reduction cycles. In a H2 environment, a more faceted surface morphology of the particles was observed with {100} and {111} planes being dominant. On the other hand, in O2 the percentage of {100} and {111} facets decreased and a significant increase of higher order facets was found, resulting in a more rounded morphology. This methodology opens up new opportunities toward in situ characterization of catalytic nanoparticles because for the first time it enables one to directly measure 3D morphology variations at the atomic scale in a specific gaseous reaction environment.

Abstract: This paper investigates the possible benefits for counting atoms of different chemical nature when analysing multiple 2D scanning transmission electron microscopy (STEM) images resulting from independent annular dark field (ADF) detector regimes. To reach this goal, the principles of statistical detection theory are used to quantify the probability of error when determining the number of atoms in atomic columns consisting of multiple types of elements. In order to apply this theory, atom-counting is formulated as a statistical hypothesis test, where each hypothesis corresponds to a specific number of atoms of each atom type in an atomic column. The probability of error, which is limited by the unavoidable presence of electron counting noise, can then be computed from scattering-cross sections extracted from multiple ADF STEM images. Minimisation of the probability of error as a function of the inner and outer angles of a specified number of independent ADF collection regimes results in optimal experimental designs. Based on simulations of spherical Au@Ag and Au@Pt core–shell nanoparticles, we investigate how the combination of two non-overlapping detector regimes helps to improve the probability of error when unscrambling two types of atoms. In particular, the combination of a narrow low angle ADF detector with a detector formed by the remaining annular collection regime is found to be optimal. The benefit is more significant if the atomic number Z difference becomes larger. In
addition, we show the benefit of subdividing the detector regime into three collection areas for heterogeneous nanostructures based on a structure consisting of three types of elements, e.g., a mixture of Au, Ag and Al atoms. Finally, these results are compared with the probability of error resulting when one would ultimately use a pixelated 4D STEM detector and how this could help to further reduce the incident electron dose.

Abstract: Quantification of annular dark field (ADF) scanning transmission electron microscopy (STEM) images in terms
of composition or thickness often relies on probe-position integrated scattering cross sections (PPISCS). In
order to compare experimental PPISCS with theoretically predicted ones, expensive simulations are needed for
a given specimen, zone axis orientation, and a variety of microscope settings. The computation time of such
simulations can be in the order of hours using a single GPU card. ADF STEM simulations can be efficiently
parallelized using multiple GPUs, as the calculation of each pixel is independent of other pixels. However, most
research groups do not have the necessary hardware, and, in the best-case scenario, the simulation time will
only be reduced proportionally to the number of GPUs used. In this manuscript, we use a learning approach and
present a densely connected neural network that is able to perform real-time ADF STEM PPISCS predictions as
a function of atomic column thickness for most common face-centered cubic (fcc) crystals (i.e., Al, Cu, Pd, Ag,
Pt, Au and Pb) along [100] and [111] zone axis orientations, root-mean-square displacements, and microscope
parameters. The proposed architecture is parameter efficient and yields accurate predictions for the PPISCS
values for a wide range of input parameters that are commonly used for aberration-corrected transmission
electron microscopes.

Abstract: Quantitative structure determination is needed in order to study and understand nanomaterials at the atomic scale. Materials characterisation resulting in precise structural information is a crucial point to understand the structure–property relation of materials. Counting the number of atoms and retrieving the 3D atomic structure of nanoparticles plays an important role here. In this paper, an overview will be given of the atom-counting methodology and its applications over the past decade. The procedure to count the number of atoms will be discussed in detail and it will be shown how the performance of the method can be further improved. Furthermore, advances toward mixed element nanostructures, 3D atomic modelling based on the atom-counting results, and quantifying the nanoparticle dynamics will be highlighted.

Abstract: Advanced electron microscopy techniques, including scanning electron microscopes (SEM), scanning transmission electron microscopes (STEM), and transmission electron microscopes (TEM), have revolutionized imaging capabilities. However, achieving high-quality experimental images remains a challenge due to various distortions stemming from the instrumentation and external factors. These distortions, introduced at different stages of imaging, hinder the extraction of reliable quantitative insights. In this paper, we will discuss the main sources of distortion in TEM and S(T)EM images, develop models to describe them, and propose a method to correct these distortions using a convolutional neural network. We validate the effectiveness of our method on a range of simulated and experimental images, demonstrating its ability to significantly enhance the signal-to-noise ratio. This improvement leads to a more reliable extraction of quantitative structural information from the images. In summary, our findings offer a robust framework to enhance the quality of electron microscopy images, which in turn supports progress in structural analysis and quantification in materials science and biology.