Abstract: Microplasmas can be used for a wide range of technological applications and to improve the understanding of fundamental physics. Scanning electron microscopy, on the other hand, provides insights into the sample morphology and chemistry of materials from the mm‐ down to the nm‐scale. Combining both would provide direct insight into plasma‐sample interactions in real‐time and at high spatial resolution. Up till now, very few attempts in this direction have been made, and significant challenges remain. This work presents a stable direct current glow discharge microplasma setup built inside a scanning electron microscope. The experimental setup is capable of real‐time in situ imaging of the sample evolution during plasma operation and it demonstrates localized sputtering and sample oxidation. Further, the experimental parameters such as varying gas mixtures, electrode polarity, and field strength are explored and experimental<italic>V</italic>–<italic>I</italic>curves under various conditions are provided. These results demonstrate the capabilities of this setup in potential investigations of plasma physics, plasma‐surface interactions, and materials science and its practical applications. The presented setup shows the potential to have several technological applications, for example, to locally modify the sample surface (e.g., local oxidation and ion implantation for nanotechnology applications) on the µm‐scale.

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: In this study, the multi-layer self-assembled molecular network formation of an alkylated tetrathiafulvalene compound is studied at the liquid-solid interface between 1-phenyloctane and graphite. A combined theoretical/experimental approach associating force-field and quantum-chemical calculations with scanning tunnelling microscopy is used to determine the two-dimensional self-assembly beyond the monolayer, but also to further the understanding of the molecular adsorption conformation and its impact on the molecular packing within the assemblies at the monolayer and bilayer level.

Abstract: In this work, we have fabricatedan aryl amino-substitutedgraphiticcarbon nitride (g-C3N4) catalyst with atomicallydispersed Mn capable of generating hydrogen peroxide (H2O2) directly from seawater. This new catalyst exhibitedexcellent reactivity, obtaining up to 2230 & mu;M H2O2 in 7 h from alkaline water and up to 1800 & mu;Mfrom seawater under identical conditions. More importantly, the catalystwas quickly recovered for subsequent reuse without appreciable lossin performance. Interestingly, unlike the usual two-electron oxygenreduction reaction pathway, the generation of H2O2 was through a less common two-electron water oxidation reaction(WOR) process in which both the direct and indirect WOR processesoccurred; namely, photoinduced h(+) directly oxidized H2O to H2O2 via a one-step 2e(-) WOR, and photoinduced h(+) first oxidized a hydroxide (OH-) ion to generate a hydroxy radical ((OH)-O-& BULL;), and H2O2 was formed indirectly by thecombination of two (OH)-O-& BULL;. We have characterized thematerial, at the catalytic sites, at the atomic level using electronparamagnetic resonance, X-ray absorption near edge structure, extendedX-ray absorption fine structure, high-resolution transmission electronmicroscopy, X-ray photoelectron spectroscopy, magic-angle spinningsolid-state NMR spectroscopy, and multiscale molecular modeling, combiningclassical reactive molecular dynamics simulations and quantum chemistrycalculations.

Abstract: High-resolution transmission electron microscopy (TEM) of organic crystals, such as Lead Phthalocyanine (PbPc), is very challenging since these materials are prone to electron beam damage leading to the breakdown of the crystal structure during investigation. Quantification of the damage is imperative to enable high-resolution imaging of PbPc crystals with minimum structural changes. In this work, we performed a detailed electron diffraction study to quantitatively measure degradation of PbPc crystals upon electron beam irradiation. Our study is based on the quantification of the fading intensity of the spots in the electron diffraction patterns. At various incident dose rates (e/Å2/s) and acceleration voltages, we experimentally extracted the decay rate (1/s), which directly correlates with the rate of beam damage. In this manner, a value for the critical dose (e/Å2) could be determined, which can be used as a measure to quantify beam damage. Using the same methodology, we explored the influence of cryogenic temperatures, graphene TEM substrates, and graphene encapsulation in prolonging the lifetime of the PbPc crystal structure during TEM investigation. The knowledge obtained by diffraction experiments is then translated to real space high-resolution TEM imaging of PbPc.

Abstract: In this study, we explore the possibility to use deep learning for the reconstruction of phase images from 4D scanning transmission electron microscopy (4D-STEM) data. The process can be divided into two main steps. First, the complex electron wave function is recovered for a convergent beam electron diffraction pattern (CBED) using a convolutional neural network (CNN). Subsequently, a corresponding patch of the phase object is recovered using the phase object approximation. Repeating this for each scan position in a 4D-STEM dataset and combining the patches by complex summation yields the full-phase object. Each patch is recovered from a kernel of 3x3 adjacent CBEDs only, which eliminates common, large memory requirements and enables live processing during an experiment. The machine learning pipeline, data generation, and the reconstruction algorithm are presented. We demonstrate that the CNN can retrieve phase information beyond the aperture angle, enabling super-resolution imaging. The image contrast formation is evaluated showing a dependence on the thickness and atomic column type. Columns containing light and heavy elements can be imaged simultaneously and are distinguishable. The combination of super-resolution, good noise robustness, and intuitive image contrast characteristics makes the approach unique among live imaging methods in 4D-STEM.

Abstract: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1].   The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions.   We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration.   Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3]   Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference.   Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script.  Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.

Abstract: We introduce a Bayesian genetic algorithm for reconstructing atomic models of monotype crystalline nanoparticles from a single projection using Z-contrast imaging. The number of atoms in a projected atomic column obtained from annular dark field scanning transmission electron microscopy images serves as an input for the initial three-dimensional model. The algorithm minimizes the energy of the structure while utilizing a priori information about the finite precision of the atom-counting results and neighbor-mass relations. The results show promising prospects for obtaining reliable reconstructions of beam-sensitive nanoparticles during dynamical processes from images acquired with sufficiently low incident electron doses.

Abstract: A decade ago, a statistics-based method was introduced to count the number of atoms from annular dark-field scanning transmission electron microscopy (ADF STEM) images. In the past years, this method was successfully applied to nanocrystals of arbitrary shape, size, and composition (and its high accuracy and precision has been demonstrated). However, the counting results obtained from this statistical framework are so far presented without a visualization of the actual uncertainty about this estimate. In this paper, we present three approaches that can be used to represent counting results together with their statistical error, and discuss which approach is most suited for further use based on simulations and an experimental ADF STEM image.

Abstract: A real-time image reconstruction method for scanning transmission electron microscopy (STEM) is proposed. With an algorithm requiring only the center of mass of the diffraction pattern at one probe position at a time, it is able to update the resulting image each time a new probe position is visited without storing any intermediate diffraction patterns. The results show clear features at high spatial frequency, such as atomic column positions. It is also demonstrated that some common post-processing methods, such as band-pass filtering, can be directly integrated in the real-time processing flow. Compared with other reconstruction methods, the proposed method produces high-quality reconstructions with good noise robustness at extremely low memory and computational requirements. An efficient, interactive open source implementation of the concept is further presented, which is compatible with frame-based, as well as event-based camera/file types. This method provides the attractive feature of immediate feedback that microscope operators have become used to, for example, conventional high-angle annular dark field STEM imaging, allowing for rapid decision-making and fine-tuning to obtain the best possible images for beam-sensitive samples at the lowest possible dose.

Abstract: We report a study of scattering dynamics in crystals employing momentum-resolved scanning transmission
electron microscopy under varying illumination conditions. As we perform successive changes of the probe
focus, multiple real-space signals are obtained in dependence of the shape of the incident electron wave.
With support from extensive simulations, each signal is shown to be characterised by an optimum focus for
which the contrast is maximum and which differs among different signals. For instance, a systematic focus
mismatch is found between images formed by high-angle scattering, being sensitive to thickness and chemical
composition, and the first moment in diffraction space, being sensitive to electric fields. It follows that a single
recording at one specific probe focus is usually insufficient to characterise materials comprehensively. Most
importantly, we demonstrate in experiment and simulation that the second moment (

Abstract: Structural analysis of metal clusters confined in nanoporous materials is typically performed by X-ray-driven techniques. Although X-ray analysis has proved its strength in the characterization of metal clusters, it provides averaged structural information. Therefore, we here present an alternative workflow for bringing the characterization of confined metal clusters towards the local scale. This workflow is based on the combination of aberration-corrected transmission electron microscopy (TEM), TEM image simulations, and powder X-ray diffraction (XRD) with advanced statistical techniques. In this manner, we were able to characterize the clustering of Pb atoms in Linde Type A (LTA) zeolites with Pb loadings as low as 5 wt%. Moreover, individual Pb clusters could be directly detected. The proposed methodology thus enables a local-scale characterization of confined metal clusters in zeolites. This is important for further elucidation of the connection between the structure and the physicochemical properties of such systems.

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.