Abstract: A computational method is presented for angle-resolved photoemission spectra (ARPES) and photoelectron diffraction (PED) in the ultraviolet regime. The one-step model is employed and both initial valence and final continuum states are calculated using the finite-cluster, real-space multiple scattering method. Thereby the approach is versatile and provides a natural link to core-level PED. The method is applied to the Cu(111) valence band and good agreement with experiment is found for both ARPES spectra and PED patterns. When the PED patterns are integrated over a filled band of a single-orbital symmetry, such as Cu-3d, we show, both numerically and analytically, that the exact theory with delocalized initial states can be replaced by the much simpler, core-level-type theory where the initial states are taken as localized.

Abstract: We present a new approach to study the three-dimensional compositional and structural evolution of metal alloys during heat treatments such as commonly used for improving overall material properties. It relies on in situ heating in a high-resolution scanning transmission electron microscope (STEM). The approach is demonstrated using a commercial Al alloy AA2024 at 100-240 degrees C, showing in unparalleled detail where and how precipitates nucleate, grow,or dissolve. The observed size evolution of individual precipitates enables a separation between nucleation and growth phenomena, necessary for the development of refined growth models. We conclude that the in situ heating STEM approach opens a route to a much faster determination of the interplay between local compositions, heat treatments, microstructure, and mechanical properties of new alloys.

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: A detailed 3D investigation of nanoparticles at a local scale is of great importance to connect their structure and composition to their properties. Electron tomography has therefore become an important tool for the 3D characterization of nanomaterials. 3D investigations typically comprise multiple steps, including acquisition, reconstruction, and analysis/quantification. Usually, the latter two steps are performed offline, at a dedicated workstation. This sequential workflow prevents on-the-fly control of experimental parameters to improve the quality of the 3D reconstruction, to select a relevant nanoparticle for further characterization or to steer an in-situ tomography experiment. Here, we present an efficient approach to overcome these limitations, based on the real-time reconstruction of arbitrary 2D reconstructed slices through a 3D object. Implementation of this method may lead to generalized implementation of electron tomography for routine nanoparticle characterization in 3D.

Abstract: Over the last decade, scanning transmission electron microscopy has become one of the most powerful tools to characterise nanomaterials at the atomic scale. Often, the ultimate goal is to retrieve the three-dimensional structure, which is very challenging since small species are typically sensitive to electron irradiation. Nevertheless, measuring individual atomic positions is crucial to understand the relation between the structure and physicochemical properties of these (nano)materials. In this review, we highlight the latest approaches that are available to reveal the 3D atomic structure of small species. Finally, we will provide an outlook and will describe future challenges where the limits of electron microscopy will be pushed even further.

Abstract: Several TEM techniques are used to characterise the local structure of low dimensional forms of carbon. HREM is particularly useful to describe the defect structure of thin films of diamond or fullerenes and C-60-C-70 nanoclusters. A columnar form of graphite is analysed, mainly by electron diffraction which allowed us to propose a growth mechanism. Diffraction contrast dark field microscopy, in combination with electron diffraction, allows a detailed characterisation of carbon nanotubes; e.g. the chirality distribution of tubes in ropes of single wall tubes is studied by selected area electron diffraction. (C) 1998 Elsevier Science Ltd. All rights reserved.

Abstract: The highly energetic electrons in a transmission electron microscope (TEM) can alter or even completely destroy the structure of samples before sufficient information can be obtained. This is especially problematic in the case of zeolites, organic and biological materials. As this effect depends on both the electron beam and the sample and can involve multiple damage pathways, its study remained difficult and is plagued with irreproducibility issues, circumstantial evidence, rumors, and a general lack of solid data. Here we take on the experimental challenge to investigate the role of the STEM scan pattern on the damage behavior of a commercially available zeolite sample with the clear aim to make our observations as reproducible as possible. We make use of a freely programmable scan engine that gives full control over the tempospatial distribution of the electron probe on the sample and we use its flexibility to obtain multiple repeated experiments under identical conditions comparing the difference in beam damage between a conventional raster scan pattern and a newly proposed interleaved scan pattern that provides exactly the same dose and dose rate and visits exactly the same scan points. We observe a significant difference in beam damage for both patterns with up to 11 % reduction in damage (measured from mass loss). These observations demonstrate without doubt that electron dose, dose rate and acceleration voltage are not the only parameters affecting beam damage in (S)TEM experiments and invite the community to rethink beam damage as an unavoidable consequence of applied electron dose.

Abstract: The irradiation effects of thinning a sample of a Cu-Zn-Al shape memory alloy to electron transparency by a Ga+ focused ion beam were investigated. This thinning method was compared with conventional electropolishing and Ar+ ion milling. No implanted Ga was detected but surface FCC precipitation was found as a result of the focused ion beam sample preparation. Decreasing the irradiation dose by lowering the energy and current of the Ga+ ions did not lead to a complete disappearance of the FCC structure. The latter could only be removed after gentle Ar+ ion milling of the sample. It was further concluded that the precipitation of the FCC is independent of the crystallographic orientation of the surface.

Abstract: We present a new method to measure structure factors from electron spot diffraction patterns recorded under almost parallel illumination in transmission electron microscopes. Bloch wave refinement routines have been developed to refine the crystal thickness, its orientation and structure factors by comparison of experimentally recorded and calculated intensities. Our method requires a modicum of computational effort, making it suitable for contemporary personal computers. Frozen lattice and Bloch wave simulations of GaAs diffraction patterns are used to derive optimised experimental conditions. Systematic errors are estimated from the application of the method to simulated diffraction patterns and rules for the recognition of physically reasonable initial refinement conditions are derived. The method is applied to the measurement of the 200 structure factor for GaAs. We found that the influence of inelastically scattered electrons is negligible. Additionally, we measured the 200 structure factor from zero loss filtered two-dimensional convergent beam electron diffraction patterns. The precision of both methods is found to be comparable and the results agree well with each other. A deviation of more than 20% from isolated atom scattering data is observed, whereas close agreement is found with structure factors obtained from density functional theory [A. Rosenauer, M. Schowalter, F. Glas, D. Lamoen, Phys. Rev. B 72 (2005), 085326-1], which account for the redistribution of electrons due to chemical bonding via modified atomic scattering amplitudes.

Abstract: Electrons, X-rays and neutrons that pass through a thin crystalline sample will be diffracted. Diffraction patterns of crystalline materials contain Bragg reflections (sharp discrete intensity maxima) and diffuse scattering (a weak continuous background). The Bragg reflections contain information about the average crystal structure (the type of atoms and the average atomic positions), whereas the diffuse scattering contains information about the short-range order (deviations from the average crystal structure that are ordered on a local scale). Because the properties of many materials depend on the short-range order, refining short-range order parameters is essential for understanding and optimizing material properties. The refinement of short-range order parameters has previously been applied to the diffuse scattering in single-crystal X-ray and single-crystal neutron diffraction data but not yet to the diffuse scattering in single-crystal electron diffraction data. In this work, we will verify the possibility to refine short-range order parameters from the diffuse scattering in single-crystal electron diffraction data. Electron diffraction allows to acquire data on submicron-sized crystals, which are too small to be investigated with single-crystal X-ray and single-crystal neutron diffraction. In the first part of this work, we will refine short-range order parameters from the one-dimensional diffuse scattering in electron diffraction data acquired on the lithium-ion battery cathode material Li1.2Ni0.13Mn0.54Co0.13O2. The number of stacking faults and the twin percentages will be refined from the diffuse scattering using a Monte Carlo refinement. We will also describe a method to determine the spinel/layered phase ratio from the intensities of the Bragg reflections in electron diffraction data. In the second part of this work, we will refine short-range order parameters from the three-dimensional diffuse scattering in both single-crystal electron and single-crystal X-ray diffraction data acquired on Nb0.84CoSb. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms will be refined from the diffuse scattering using a Monte Carlo refinement and a three-dimensional difference pair distribution function refinement. The effect of different experimental parameters on the spatial resolution of the observed diffuse scattering will also be investigated. Finally, the model of the short-range Nb-vacancy order in Nb0.84CoSb will also be applied to LiNi0.5Sn0.3Co0.2O2.

Abstract: BSA-coated Fe3O4 nanoparticles with different hydrodynamic diameters (36 +/- 4 and 85 +/- 10 nm) were synthesized, zeta potential and T2 relaxivity were determined, and their morphology was studied by transmission electron microscopy. Studies on rats with experimental glioma C6 showed that smaller nanoparticles more effectively accumulated in the tumor and circulated longer in brain vessels. Optimization of the hydrodynamic diameter improves the efficiency of MRT contrast agent.