Abstract: Electron ptychography provides highly sensitive, dose efficient phase images which can be corrected for aberrations after the data has been acquired. This is crucial when very precise quantification is required, such as with sensitivity to charge transfer due to bonding. Drift can now be essentially eliminated as a major impediment to focused probe ptychography, which benefits from the availability of easily interpretable simultaneous Z-contrast imaging. However challenges have remained when quantifying the ptychographic phases of atomic sites. The phase response of a single atom has a negative halo which can cause atoms to reduce in phase when brought closer together. When unaccounted for, as in integrating methods of quantification, this effect can completely obscure the effects of charge transfer. Here we provide a new method of quantification that overcomes this challenge, at least for 2D materials, and is robust to experimental parameters such as noise, sample tilt.

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: 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: 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: 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: In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data.

Abstract: HAADF-STEM tomography is a widely used experimental technique for analyzing nanometer-scale crystalline structures of a large variety of materials in three dimensions. Unfortunately, the acquisition of conventional HAADF-STEM tilt series can easily take up one hour or more, depending on the complexity of the experiment. It is therefore far from straightforward to investigate samples that do not withstand long acquisition or to acquire large amounts of tilt series during a single TEM experiment. The latter would lead to the ability to obtain statistically meaningful 3D data, or to perform in situ 3D characterizations with a much shorter time resolution. Various HAADF-STEM acquisition strategies have been proposed to accelerate the tomographic acquisition and reduce the required electron dose. These methods include tilting the holder continuously while acquiring a projection “movie” and a hybrid, incremental, methodology which combines the benefits of the conventional and continuous technique. However, until now an experimental evaluation has been lacking. In this paper, the different acquisition strategies will be experimentally compared in terms of speed, resolution and electron dose. This evaluation will be performed based on experimental tilt series acquired for various metallic nanoparticles with different shapes and sizes. We discuss the data processing involved with the fast HAADF-STEM tilt series and provide a general guideline when which acquisition strategy should be preferentially used.

Abstract: Lattice strain measurement of nanoscale semiconductor devices is crucial for the semiconductor industry as strain substantially improves the electrical performance of transistors. High resolution scanning transmission electron microscopy (HR-STEM) imaging is an excellent tool that provides spatial resolution at the atomic scale and strain information by applying Geometric Phase Analysis or image fitting procedures. However, HR-STEM images regularly suffer from scanning distortions and sample drift during image acquisition. In this paper, we propose a new scanning strategy that drastically reduces artefacts due to drift and scanning distortion, along with extending the field of view. It consists of the acquisition of a series of independent small subimages containing an atomic resolution image of the local lattice. All subimages are then analysed individually for strain by fitting a nonlinear model to the lattice images. The method allows flexible tuning of spatial resolution and the field of view within the limits of the dynamic range of the scan engine while maintaining atomic resolution sampling within the subimages. The obtained experimental strain maps are quantitatively benchmarked against the Bessel diffraction technique. We demonstrate that the proposed scanning strategy approaches the performance of the diffraction technique while having the advantage that it does not require specialized diffraction cameras.

Abstract: In electron microscopy, the maximum a posteriori (MAP) probability rule has been introduced as a tool to determine the most probable atomic structure from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images exhibiting low contrast-to-noise ratio (CNR). Besides ADF imaging, STEM can also be applied in the annular bright-field (ABF) regime. The ABF STEM mode allows to directly visualize light-element atomic columns in the presence of heavy columns. Typically, light-element nanomaterials are sensitive to the electron beam, limiting the incoming electron dose in order to avoid beam damage and leading to images exhibiting low CNR. Therefore, it is of interest to apply the MAP probability rule not only to ADF STEM images, but to ABF STEM images as well. In this work, the methodology of the MAP rule, which combines statistical parameter estimation theory and model-order selection, is extended to be applied to simultaneously acquired ABF and ADF STEM images. For this, an extension of the commonly used parametric models in STEM is proposed. Hereby, the effect of specimen tilt has been taken into account, since small tilts from the crystal zone axis affect, especially, ABF STEM intensities. Using simulations as well as experimental data, it is shown that the proposed methodology can be successfully used to detect light elements in the presence of heavy elements.

Abstract: The hot working of 5xxx series alloys with Mg ≥3.5 wt% is a concern due to the precipitation of β (Al3Mg2) phase at grain boundaries favoring Inter Granular Corrosion (IGC). The mechanical and corrosion properties of a new 5028-H116 Al-Mg-Sc alloy under various β precipitates distribution is analyzed by imposing different cooling rates from the hot forming temperature (i.e. 325 °C). The mechanical properties are maintained regardless of the heat treatment. However, the different nucleation sites and volume fractions of β precipitates for different cooling rates critically affect IGC. Controlled furnace cooling after the 325 °C heat treatment is ideal in 5028-H116 alloy to reduce susceptibility to IGC after sensitization.

Abstract: A recently developed healable Al-Mg2Si designed by the programmed damage and repair (PDR) strategy is studied considering the role microstructural defects play on precipitation, damage, and healing. The alloy incorporates sacrificial Mg2Si particles that precipitate after friction stir processing (FSP). They act as damage localization sites and are healable based on the solid-state diffusion of Al-matrix. A combination of different transmission electron microscopy (TEM) imaging techniques enabled the visualization and quantification of various crystallographic defects and the spatial distribution of Mg2Si precipitates. Intragrain nucleation is found to be the dominant mechanism for precipitation during FSP whereas grain boundaries and subgrain boundaries mainly lead to coarsening of the precipitates. The statistical and spatial analyses of the damaged particles have shown particle fracture as the dominant damage mechanism which is strongly dependent on the size and aspect ratio of the particles whereas the damage was not found to depend on the location of the precipitates within the matrix. The damaged particles are associated with dislocations accumulated around them. The interplay of these dislocations is directly visualized during healing based on in situ TEM heating which revealed recovery in the matrix as an operative mechanism during the diffusion healing of the PDR alloy.

Abstract: Hydrogen blistering, i.e. precipitation of supersaturated hydrogen at elevated temperatures, increases porosity during heat treatments in 4xxx series Al alloys manufactured by laser powder bed fusion (LPBF), as demonstrated by 3D X-ray nano-imaging in AlSi12. This paper proposes the design of a healable Al alloy to suppress hydrogen blistering and improve the damage management. The strategy consists of solute atoms diffusing towards nano-voids and precipitating on their surface, thereby filling the damage sites. A new healable Al alloy was thus developed and successfully manufactured by LPBF. 3D X-ray nano-imaging evidenced that the addition of Mg in 4xxx series Al alloys suppresses the hydrogen blistering. This is expectedly due to Mg in solid solution which increases the hydrogen solubility in the Al matrix and due to the healing of these hydrogen pores. Moreover, a significant healing of voids smaller than 500 nm diameter is observed. In-situ heating inside transmission electron microscopy pointed out that Al matrix diffuses inside the fractured Mg2Si particles, thereby demonstrating the healing ability of the new alloy. This has opened the doors to development of new healable Al alloys manufactured by LPBF as well as to new post-treatments to tailor mechanical properties and microstructure without hydrogen blistering.

Abstract: This work addresses the early stages (<= 1000 h) of the dissolution corrosion behavior of 316L and DIN 1.4970 austenitic stainless steels in contact with oxygen-poor (C-O < 10(-8) mass%), static liquid lead-bismuth eutectic (LBE) at 500 degrees C for 600-1000 h. The objective of this study was to determine the relative early-stage resistance of the uncoated steels to dissolution corrosion and to assess the protectiveness of select candidate coatings (Cr2AlC, Al2O3, V2AlxCy). The simultaneous exposure of steels with intended differences in microstructure and thermomechanical state showed the effects of steel grain size, density of annealing/deformation twins, and secondary precipitates on the steel dissolution corrosion behavior. The findings of this study provide recommendations on steel manufacturing with the aim of using the steels to construct Gen-IV lead-cooled fast reactors.