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: 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: 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: The reduction of carbon dioxide (CO2) using porphyrin-containing 2D covalent organic frameworks (2D-COFs) catalysts is widely explored nowadays. While these framework materials are normally fabricated as powders followed by their uncontrolled surface heterogenization or directly grown as thin films (thickness >200 nm), very little is known about the performance of substrate-supported single-layered (approximate to 0.5 nm thickness) 2D-COFs films (s2D-COFs) due to its highly challenging synthesis and characterization protocols. In this work, a fast and straightforward fabrication method of porphyrin-containing s2D-COFs is demonstrated, which allows their extensive high-resolution visualization via scanning tunneling microscopy (STM) in liquid conditions with the support of STM simulations. The as-prepared single-layered film is then employed as a cathode for the electrochemical reduction of CO2. Fe porphyrin-containing s2D-COF@graphite used as a single-layered heterogeneous catalyst provided moderate-to-high carbon monoxide selectivity (82%) and partial CO current density (5.1 mA cm(-2)). This work establishes the value of using single-layered films as heterogene ous catalysts and demonstrates the possibility of achieving high performance in CO2 reduction even with extremely low catalyst loadings.

Abstract: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic‐resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state‐of‐the‐art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark‐field scanning transmission electron microscopy enables the acquisition of ten high‐resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allows resolving the real‐time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions.

Abstract: The idea of this Review is to introduce newly developed possibilities of advanced electron microscopy to the materials science community. Over the last decade, electron microscopy has evolved into a full analytical tool, able to provide atomic scale information on the position, nature, and even the valency atoms. This information is classically obtained in two dimensions (2D), but can now also be obtained in 3D. We show examples of applications in the field of nanoparticles and interfaces.

Abstract: Investigating domain boundaries and their effects on the behaviour of materials automatically implies the need for detailed knowledge on the structural aspects of the atomic configurations at these interfaces. Not only in view of nearest neighbour interactions but also at a larger scale, often surpassing the unit cell, the boundaries can contain structural elements that do not exist in the bulk. In the present contribution, a number of special boundaries resulting from phase transformations or crystal growth and those recently investigated by advanced transmission electron microscopy techniques in different systems will be reviewed. These include macrotwins between microtwinned martensite plates in NiAl, austenite-single variant martensite habit planes in low hysteresis NiTiPd, nanotwins in non-textured nanostructured Pd and ferroelastic domain boundaries in CaTiO3. In all discussed cases these boundaries play an essential role in the properties of the respective materials.

Abstract: We report a method to reliably count the number of atoms from high-angle annular dark field scanning transmission electron microscopy images. A model-based analysis of the experimental images is used to measure scattering cross sections at the atomic level. The high sensitivity of these measurements in combination with a thorough statistical analysis enables us to count atoms with single-atom sensitivity. The validity of the results is confirmed by means of detailed image simulations. We will show that the method can be applied to nanocrystals of arbitrary shape, size, and atom type without the need for a priori knowledge about the atomic structure.

Abstract: Functional interfaces are at the core of research in the emerging field of domain boundary engineering where polar, conducting, chiral, and other interfaces and twin boundaries have been discovered. Ferroelectricity was found in twin walls of paraelectric CaTiO3. We show that the effect of functional interfaces can be optimized if the number of twin boundaries is increased in densely twinned materials. Such materials can be produced by shear in the ferroelastic phase rather than by rapid quench from the paraelastic phase.

Abstract: The synthesis of materials with well-controlled composition and structure improves our understanding of their intrinsic electrical transport properties. Recent developments in atomically controlled growth have been shown to be crucial in enabling the study of new physical phenomena in epitaxial oxide heterostructures. Nevertheless, these phenomena can be influenced by the presence of defects that act as extrinsic sources of both doping and impurity scattering. Control over the nature and density of such defects is therefore necessary to fully understand the intrinsic materials properties and exploit them in future device technologies. Here, it is shown that incorporation of a strontium copper oxide nano-layer strongly reduces the impurity scattering at conducting interfaces in oxide LaAlO3SrTiO3(001) heterostructures, opening the door to high carrier mobility materials. It is proposed that this remote cuprate layer facilitates enhanced suppression of oxygen defects by reducing the kinetic barrier for oxygen exchange in the hetero-interfacial film system. This design concept of controlled defect engineering can be of significant importance in applications in which enhanced oxygen surface exchange plays a crucial role.

Abstract: In the present paper, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. In order to count the number of atoms, it is assumed that the total scattered intensity scales with the number of atoms per atom column. These intensities are quantitatively determined using model-based statistical parameter estimation theory. The distribution describing the probability that intensity values are generated by atomic columns containing a specific number of atoms is inferred on the basis of the experimental scattered intensities. Finally, the number of atoms per atom column is quantified using this estimated probability distribution. The number of atom columns available in the observed STEM image, the number of components in the estimated probability distribution, the width of the components of the probability distribution, and the typical shape of a criterion to assess the number of components in the probability distribution directly affect the accuracy and precision with which the number of atoms in a particular atom column can be estimated. It is shown that single atom sensitivity is feasible taking the latter aspects into consideration.

Abstract: A thorough understanding of the three-dimensional (3D) atomic structure and composition of coreshell nanostructures is indispensable to obtain a deeper insight on their physical behavior. Such 3D information can be reconstructed from two-dimensional (2D) projection images using electron tomography. Recently, different electron tomography techniques have enabled the 3D characterization of a variety of nanostructures down to the atomic level. However, these methods have all focused on the investigation of nanomaterials containing only one type of chemical element. Here, we combine statistical parameter estimation theory with compressive sensing based tomography to determine the positions and atom type of each atom in heteronanostructures. The approach is applied here to investigate the interface in coreshell Au@Ag nanorods but it is of great interest in the investigation of a broad range of nanostructures.

Abstract: A (LaVO3)6/(SrVO3)(3) superlattice is studied with a combination of sub-A resolved scanning transmission electron microscopy and monochromated electron energy-loss spectroscopy. The V oxidation state is mapped with atomic spatial resolution enabling us to investigate electronic reconstruction at the LaVO3/SrVO3 interfaces. Surprisingly, asymmetric charge distribution is found at adjacent chemically symmetric interfaces. The local structure is proposed and simulated with a double channeling calculation which agrees qualitatively with our experiment. We demonstrate that local strain asymmetry is the likely cause of the electronic asymmetry of the interfaces. The electronic reconstruction at the interfaces extends much further than the chemical composition, varying from 0.5 to 1.2 nm. This distance corresponds to the length of charge transfer previously found in the (LaVO3)./(SrVO3). metal/insulating and the (LaAlO3)./(SrTiO3). insulating/insulating interfaces.

Abstract: Modern TEM enables the investigation of nanostructures at the atomic scale. However, TEM images are only two-dimensional (2D) projections of a three-dimensional (3D) object. Electron tomography can overcome this limitation. The technique is increasingly focused towards quantitative measurements and reaching atomic resolution in 3D has been the ultimate goal for many years. Therefore, one needs to optimize the acquisition of the data, the 3D reconstruction techniques as well as the quantification methods. Here, we will review a broad range of methodologies and examples. Finally, we will provide an outlook and will describe future challenges in the field of electron tomography.