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.

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: 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: 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: 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: The signal-to-noise ratio (SNR) in energy-loss magnetic chiral dichroism (EMCD)the equivalent of X-ray magnetic circular dichroism (XMCD) in the electron microscopeis optimized with respect to the detector shape, size and position. We show that an important increase in SNR over previous experiments can be obtained when taking much larger detector sizes. We determine the ideal shape of the detector but also show that round apertures are a good compromise if placed in their optimal position. We develop the theory for a simple analytical description of the EMCD experiment and then apply it to dynamical multibeam Bloch wave calculations and to an experimental data set. In all cases it is shown that a significant and welcome improvement of the SNR is possible.

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: 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: In typical seed-mediated syntheses of metal nanocrystals, the shape of the nanocrystal is determined largely by the seed nucleation environment and subsequent growth environment (where “environment” refers to the chemical environment, including the surfactant and additives). In this approach, crystallinity is typically determined by the seeds, and surfaces are controlled by the environment(s). However, surface energies, and crystallinity, are both influenced by the choice of environment(s). This limits the permutations of crystallinity and surface facets that can be mixed and matched to generate new nanocrystal morphologies. Here, we control post-seed growth to deliberately incorporate twin planes during the growth stage to deliver new final morphologies, including twinned cubes and bipyramids from single-crystal seeds. The nature and number of twin planes, together with surfactant control of facet growth, define the final nanoparticle morphology. Moreover, by breaking symmetry, the twin planes introduce new facet orientations. This additional mechanism opens new routes for the synthesis of different morphologies and facet orientations.

Abstract: A systematic study has been carried out to compare the surface morphology, shell thickness, mechanical properties, and binding behavior of melamine–formaldehyde microcapsules of 5–30 μm diameter size with various amounts of core content by using scanning and transmission electron microscopy including electron tomography, in situ nanomechanical tensile testing, and electron energy-loss spectroscopy. It is found that porosities are present on the outside surface of the capsule shell, but not on the inner surface of the shell. Nanomechanical tensile tests on the capsule shells reveal that Young’s modulus of the shell material is higher than that of bulk melamine–formaldehyde and that the shells exhibit a larger fracture strain compared with the bulk. Core-loss elemental analysis of microcapsules embedded in epoxy indicates that during the curing process, the microcapsule-matrix interface remains uniform and the epoxy matrix penetrates into the surface micro-porosities of the capsule shells.

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: 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: CsPbI3 is a promising perovskite material for photovoltaic applications in its photoactive perovskite or black phase. However, the material degrades to a photovoltaically inactive or yellow phase at room temperature. Various mitigation strategies are currently being developed to increase the lifetime of the black phase, many of which rely on inducing strains in the material that hinder the black-to-yellow phase transition. Physical insight into how these strategies exactly induce strain as well as knowledge of the spatial extent over which these strains impact the material is crucial to optimize these approaches but is still lacking. Herein, we combine machine learning potential-based molecular dynamics simulations with our in silico strain engineering approach to accurately quantify strained large-scale atomic structures on a nanosecond time scale. To this end, we first model the strain fields introduced by atomic substitutions as they form the most elementary strain sources. We demonstrate that the magnitude of the induced strain fields decays exponentially with the distance from the strain source, following a decay rate that is largely independent of the specific substitution. Second, we show that the total strain field induced by multiple strain sources can be predicted to an excellent approximation by summing the strain fields of each individual source. Finally, through a case study, we illustrate how this additive character allows us to explain how complex strain fields, induced by spatially extended strain sources, can be predicted by adequately combining the strain fields caused by local strain sources. Hence, the strain additivity proposed here can be adopted to further our insight into the complex strain behavior in perovskites and to design strain from the atomic level onward to enhance their sought-after phase stability.

Abstract: Source size broadening is an important resolution limiting effect in modern STEM experiments. Here, we propose an alternative method to measure the source size broadening making use of a holographic biprism to create interference patterns in an empty Ronchigram. This allows us to measure the exact shape of the source size broadening with a much better sampling than previously possible. We find that the shape of the demagnified source deviates considerably from a Gaussian profile that is often assumed. We fit the profile with a linear combination of a Gaussian and a bivariate Cauchy distribution showing that even though the full width at half maximum is similar to previously reported measurements, the tails of the profile are considerable wider. This is of fundamental importance for quantitative comparison of STEM simulations with experiments as these tails make the image contrast dependent on the interatomic distance, an effect that cannot be reproduced by a single Gaussian profile of fixed width alone.

Abstract: Pure and 6 mol% BaHfO3 (BHO) doped YBa2Cu3O7-δ (YBCO) films were prepared on CeO2-buffered ABAD-YSZ templates by pulsed laser deposition. The self-field Jc at 77 K reaches 1.1 MA/cm² in the doped sample compared to 2.5 MA/cm² in pure YBCO, at a film thickness of around 1 μm. Above a magnetic field of 2.2 T along B||c, Jc of the BHO-doped sample exceeds the Jc of the undoped film. The maximum pinning force density (FP,max) reaches a value of around 3 GN/cm² for both samples, but B(FP,max) increases from 1.4 T (pure) to a value of 2.9 T (BHO:YBCO). The Jc anisotropy curves of the doped sample show a large and broad peak at B||c and a strongly reduced anisotropy at all temperatures and fields compared to the pure sample. A complex defect structure with YBa2Cu4O8 intergrowths, Y2O3 precipitates and BHO nanocolumns with a fanshaped structure is observed by TEM investigations, which can explain the measured Jc(B,θ) behavior.