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: 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: 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.

Abstract: Electron tomography is essential for investigating the three-dimensional (3D) structure of nanomaterials. However, many of these materials, such as metal-organic frameworks (MOFs), are extremely sensitive to electron radiation, making it difficult to acquire a series of projection images for electron tomography without inducing electron-beam damage. Another significant challenge is the high contrast in high-angle annular dark field scanning transmission electron microscopy that can be expected for nanocomposites composed of a metal nanoparticle and an MOF. This strong contrast leads to so-called metal artifacts in the 3D reconstruction. To overcome these limitations, we here present low-dose electron tomography based on four-dimensional scanning transmission electron microscopy (4D-STEM) data sets, collected using an ultrafast and highly sensitive direct electron detector. As a proof of concept, we demonstrate the applicability of the method for an Au nanostar embedded in a ZIF-8 MOF, which is of great interest for applications in various fields, including drug delivery.

Abstract: Determining the three-dimensional (3D) atomic structure of nanoparticles (NPs) is critical to understand their structure-dependent properties. It is hereby important to perform such analyses under conditions relevant for the envisioned application. Here, we investigate the 3D structure of supported Au NPs at high temperature, which is of importance to understand their behavior during catalytic reactions. To overcome limitations related to conventional high-resolution electron tomography at high temperature, 3D characterization of NPs with atomic resolution has been performed by applying atom-counting using atomic resolution annular darkfield scanning transmission electron microscopy (ADF STEM) images followed by structural relaxation. However, at high temperatures, thermal displacements, which affect the ADF STEM intensities, should be taken into account. Moreover, it is very likely that the structure of a NP investigated at elevated temperature deviates from a ground state configuration, which is difficult to determine using purely computational energy minimization approaches. In this paper, we therefore propose an optimized approach using an iterative local minima search algorithm followed by molecular dynamics (MD) structural relaxation of candidate structures associated with each local minimum. In this manner, it becomes possible to investigate the 3D atomic structure of supported NPs, which may deviate from their ground state configuration.

Abstract: Self-assembly of inorganic nanoparticles has been used to prepare hundreds of different colloidal crystals, but almost invariably with the restriction that the particles must be densely packed. Here,we show that non–close-packed nanoparticle arrays can be fabricated through the selective removal of one of two components comprising binary nanoparticle superlattices. First, a variety of binary nanoparticle superlattices were prepared at the liquid-air interface, including several arrangements that were previously unknown. Molecular dynamics simulations revealed the particular role of the liquid in templating the formation of superlattices not achievable through self-assembly in bulk solution. Second, upon stabilization, all of these binary superlattices could be transformed into distinct “nanoallotropes”—nanoporous materials having the same chemical composition but differing in their nanoscale architectures.

Abstract: A robust and easy to handle 3D porous platinum structure was created via replicating the 3D channel system
of an ordered mesoporous silica material using atomic layer deposition (ALD) over micrometer distances.
After ALD of Pt in the silica material, the host template was digested using hydrogen fluoride (HF). A fully
connected ordered Pt nanostructure was obtained with morphology and sizes corresponding to that of
the pores of the host matrix, as revealed with high-resolution scanning transmission electron
microscopy and electron tomography. The Pt nanostructure consisted of hexagonal Pt rods originating
from the straight mesopores (11 nm) of the host structure and linking features resulting from Pt
replication of the interconnecting mesopore segments (2–4 nm) present in the silica host structure.
Electron tomography of partial replicas, made by incomplete infilling of Zeotile-4 material with Pt,
provided insight in the connectivity and formation mechanism of the Pt nanostructure by ALD. The Pt
replica was evaluated for its potential use as electrocatalyst for the hydrogen evolution reaction, one of
the half-reactions of water electrolysis, and as microelectrode for biomedical sensing. The Pt replica
showed high activity for the hydrogen evolution reaction and electrochemical characterization revealed
a large impedance improvement in comparison with reference Pt electrodes.

Abstract: Simple methods for producing noble metal catalysts with well-defined active sites and improved performance are highly desired in the chemical industry. However, the development of such methods still presents a formidable synthetic challenge. Here, we demonstrate a one-pot synthesis route for the controlled production of bimetallic Pt–In catalysts based on the single-step formation of Mg,Al,Pt,In-containing layered double hydroxides (LDHs). Besides their simple synthesis, these Pt–In catalysts exhibit superior propane dehydrogenation activity compared to their multi-step synthesized analogs. The presented material serves as a showcase for the one-pot synthesis of a broader class of LDH-derived mono- and multimetallic Pt catalysts. The compositional flexibility provided by LDH materials can pave the way towards highperforming Pt-based catalysts with tunable physicochemical properties.

Abstract: We present an investigation of the microstructure changes in V2O3 as it goes through its inherent structural phase transition. Using V2O3 films with a well-defined crystal structure deposited by reactive magnetron sputtering on r-plane Al2O3 substrates, we study the phase coexistence region and its impact on the surface roughness of the films and the magnetic properties of overlying Ni magnetic layers in V2O3/Ni hybrid magnetic heterostructures. The simultaneous presence of two phases in V2O3 during its structural phase transition was identified with high resolution x-ray diffraction and led to an increase in surface roughness observed using x-ray reflectivity. The roughness reaches its maximum at the midpoint of the transition. In V2O3/Ni hybrid heterostructures, we find a concomitant increase in the coercivity of the magnetic layer correlated with the increased roughness of the V2O3 surface. The chemical homogeneity of the V2O3 is confirmed through transmission electron microscopy analysis. High-angle annular dark field imaging and electron energy loss spectroscopy reveal an atomically flat interface between Al2O3 and V2O3, as well as a sharp interface between V2O3 and Ni.

Abstract: Superconducting YBa2Cu3O7-delta (YBCO) films with artificial BaZrO3 (BZO) nanodots were prepared using a chemical solution deposition method involving hybrid solutions composed of trifluoroacetate-based YBCO precursors and reverse micelle stabilized BZO nanoparticle dispersions. Microemulsion-mediated synthesis was used to obtain nano-sized (similar to 12 nm) and mono-dispersed BZO nanoparticles that preserve their features once introduced into the YBCO solution, as revealed by dynamic light scattering. Phase pure, epitaxial YBCO films with randomly oriented BZO nanodots distributed over their whole microstructure were grown from the hybrid solutions on (100) LaAlO3 substrates. The morphology of the YBCO-BZO nanocomposite films was strongly influenced by the amount of nanoparticles incorporated into the system, with contents ranging from 5 to 40 mol%. Scanning electron microscopy showed a high density of isolated second-phase defects consisting of BZO nanodots in the nanocomposite film with 10 mol% of BZO. Furthermore, a direct observation and quantitative analysis of lattice defects in the form of interfacial edge dislocations directly induced by the BZO nanodots was evidenced by transmission electron microscopy. The superconducting properties (77 K) of the YBCO films improved considerably by the presence of such nanodots, which seem to enhance the morphology of the sample and therefore the intergranular critical properties. The incorporation of preformed second-phase defects (here, BZO) during the growth of the superconducting phase is the main innovation of this novel approach for the all-solution based low-cost fabrication of long-length coated conductors.

Abstract: Ni thin films sputter-deposited at room temperature with varying Ar pressures were investigated with automated crystal orientation mapping in a transmission electron microscope to uncover the mechanisms controlling the internal stress build-up recorded in-situ during deposition. Large grains were found to induce behaviour similar to a stress-free nucleation layer. The measurements of grain size in most of the Ni thin films are in agreement with the island coalescence model. Low internal stress was observed at low Ar pressure and was explained by the presence of large grains. Relaxation of high internal stress was also noticed at the highest Ar pressure, which was attributed to a decrease of Σ3 twin boundary density due to a low deposition rate. The results provide insightful information to better understand the relationship between structural boundaries and the evolution of internal stress upon deposition of thin films.