Abstract: Nanoscience and nanotechnologies are of immense importance across many fields of science and for numerous practical applications. In this context, scanning transmission electron microscopy (STEM) and 4D-STEM are among the most powerful characterization methods at the atomic scale. Annular dark-field (ADF)-STEM can be used to quantify atomic structures in 3D by counting atoms based on a single projection image. In 4D-STEM a full diffraction pattern is recorded at each scan step, which enables more dose efficient imaging and the utilization of various advanced imaging modalities, which can however be complex and slow. Both, STEM and 4D-STEM suffer from noise and distortions. In the first section of this work the most important of these distortions are discussed and it is shown how image restoration with a dedicated convolutional neural network (CNN) can be beneficial for atomic structure quantifications in ADF-STEM. In the second part, a new 4D-STEM imaging method real-time-integrated-centre-of-mass (riCOM) is introduced, which is a very dose-efficient and fast algorithm that enables unprecedented live-imaging capabilities for 4D-STEM. It is based on the integrated centre-of-mass approach, but is reformulated with variable integration ranges and optional filters, which allows for a tunable contrast transfer function. This enables the imaging of light and heavy elements simultaneously at very low doses. In the third part another new 4D-STEM method, coined AIRPI (AI-assisted rapid phase imaging) is introduced, which uses a CNN to retrieve a patch of the specimen's phase image for each scan position, based on the diffraction patterns in the probe's immediate surroundings. This allows also live imaging in principle and surpasses comparable state-of-the-art algorithms in terms of resolution also at low doses. Different atomic columns can be reliably distinguished over a wide range of atomic numbers, enabling a very good image interpretability. Further, AIRPI can recover low frequency image components, which preserves thickness information. This is a unique and important feature which could make quantitative 4D-STEM feasible.

Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.

Abstract: As a semiconductor ferroelectric, GeTe has become a focus of renewed attention due to the recent discovery of giant Rashba splitting. It already has a wide range of applications, from thermoelectricity to data storage. Its stability in ambient air, as well as the structure and properties of an oxide layer, define the processing media for device production and operation. Here, we studied a reaction between the GeTe (111) surface and molecular oxygen for crystals having solely inversion domains. We evaluated the reaction kinetics both ex situ and in situ using NAP XPS. The structure of the oxide layer is extensively discussed, where, according to HAADF-STEM and STEM-EDX, nanoscale phase separation of GeO2 and Te is observed, which is unusual for semiconductors. We believe that such behaviour is closely related to the ferroelectric properties and the domain structure of GeTe.

Abstract: Temperature-programmed oxygen isotopic exchange study was performed on nanocrystalline tin dioxide-based materials synthesized via sol-gel route and modified by palladium. Such materials are widely used as resistive gas sensors. The experiments were carried out in a flow-reactor up to complete isotopic substitution of oxygen. Substantial rates of isotopic exchange for SnO2 were observed from about 700 K. The distribution of isotopic molecules O-16(2). (OO)-O-16-O-18 and O-18(2) corresponds to simple dioxygen heteroexchange mechanism with single lattice oxygen atom. The modification of SnO2 by Pd introduced multiple heteroexchange mechanism with preliminary O-2 dissociation on the clusters surface. Spill-over of atomic oxygen from Pd to the surface of SnO2 and fast exchange with lattice oxygen result in more than 100% increase of apparent heteroexchange rate. The exchange on SnO2/Pd was shown to be a complex process involving partial deactivation of the catalytic centers at temperature higher than 750 K. (C) 2011 Elsevier Inc. All rights reserved.

Abstract: The properties and applications of metallic nanoparticles are inseparably connected not only to their detailed morphology and composition but also to their structural configuration and mutual interactions. As a result, the assemblies often have superior properties as compared to individual nanoparticles. Although it has been reported that nanoparticles can form highly symmetric clusters, if the configuration can be predicted as a function of the synthesis parameters, more targeted and accurate synthesis will be possible. We present here a theoretical model that accurately predicts the structure and configuration of self-assembled gold nanoclusters. The validity of the model is verified using quantitative experimental data extracted from electron tomography 3D reconstructions of different assemblies. The present theoretical model is generic and can in principle be used for different types of nanoparticles, providing a very wide window of potential applications.

Abstract: The metallic interface between two oxide insulators, such as LaAlO3/SrTiO3 (LAO/STO), provides new opportunities for electronics and spintronics. However, due to the presence of multiple orbital populations, tailoring the interfacial properties such as the ground state and metal-insulator transitions remains challenging. Here, an unforeseen tunability of the phase diagram of LAO/STO is reported by alloying LAO with a ferromagnetic LaMnO3 insulator without forming lattice disorder and at the same time without changing the polarity of the system. By increasing the Mn-doping level, x, of LaAl1-xMnxO3/STO (0 <= x <= 1), the interface undergoes a Lifshitz transition at x = 0.225 across a critical carrier density of n(c) = 2.8 x 10(13) cm(-2), where a peak T-SC approximate to 255 mK of superconducting transition temperature is observed. Moreover, the LaAl1-xMnxO3 turns ferromagnetic at x >= 0.25. Remarkably, at x = 0.3, where the metallic interface is populated by only d(xy) electrons and just before it becomes insulating, a same device with both signatures of superconductivity and clear anomalous Hall effect (7.6 x 10(12) cm(-2) < n(s) <= 1.1 x 10(13) cm(-2)) is achieved reproducibly. This provides a unique and effective way to tailor oxide interfaces for designing on-demand electronic and spintronic devices.

Abstract: Ptychography provides high dose efficiency images that can reveal light elements next to heavy atoms. However, despite ptychography having an otherwise single signed contrast transfer function, contrast reversals can occur when the projected potential becomes strong for both direct and iterative inversion ptychography methods. It has recently been shown that these reversals can often be counteracted in direct ptychography methods by adapting the focus. Here we provide an explanation of why the best contrast is often found with the probe focused to the middle of the sample. The phase contribution due to defocus at each sample slice above and below the central plane in this configuration effectively cancels out, which can prevent contrast reversals when dynamical scattering effects are not overly strong. In addition we show that the convergence angle can be an important consideration for removal of contrast reversals in relatively thin samples.

Abstract: Conversion of solar energy into thermal energy helps reducing consumption of non-renewable energies. Cermets (ceramicmetal composites) are versatile materials suitable, amongst other applications, for solar selective absorbers. Although the presence of metallic Ni particles in the dielectric matrix is a prerequisite for efficient solar selective absorption in NiCrOx cermets, no clear evidence of such particles is reported so far. By combining comprehensive chemical and structural analyses, we reveal the presumed nanostructure which is at the origin of the remarkable optical properties of this cermet material. Using sputtered NiCrOx layers in a solar absorber multilayer stack on aluminium substrate allows us to achieve solar absorptance as high as α=96.1% while keeping thermal emissivity as low as ε=2.2%, both values being comparable to best values recorded so far. With the nanostructure of sputtered NiCrOx cermets eventually revealed, further optimization of solar absorbers can be anticipated and technological exploitation of cermet materials in other applications can be foreseen.

Abstract: Numerical simulations of flow and pollutant dispersion in urban environments have the potential to support design and policy decisions that could reduce the population's exposure to air pollution. Reynolds-averaged Navier-Stokes simulations are a common modeling technique for urban flow and dispersion, but several sources of uncertainty in the simulations can affect the accuracy of the results. The present study proposes a method to quantify the uncertainty related to variability in the inflow boundary conditions. The method is applied to predict flow and pollutant dispersion in downtown Oklahoma City and the results are compared to field measurements available from the Joint Urban 2003 measurement campaign. Three uncertain parameters that define the inflow profiles for velocity, turbulence kinetic energy and turbulence dissipation are defined: the velocity magnitude and direction, and the terrain roughness length. The uncertain parameter space is defined based on the available measurement data, and a non-intrusive propagation approach that employs 729 simulations is used to quantify the uncertainty in the simulation output. A variance based sensitivity analysis is performed to identify the most influential uncertain parameters, and it is shown that the predicted tracer concentrations are influenced by all three uncertain variables. Subsequently, we specify different probability distributions for the uncertain inflow variables based on the available measurement data and calculate the corresponding means and 95% confidence intervals for comparison with the field measurements at 35 locations in downtown Oklahoma City. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: Advances in the synthesis of porous microspheres and in their functionalization are increasing the interest in applications of alumina. This paper deals with coatings plasma deposited from 3-aminopropyltriethoxysilane by means of dielectric barrier discharges on alumina porous microspheres, shaped by a vibrational droplet coagulation technique. Aims of the work are the functionalization of the particles with active amino groups, as well as the evaluation of their surface coverage and of the penetration of the coatings into their pores. A multi-diagnostic approach was used for the chemical/morphological characterization of the particles. It was found that 5 min exposure to plasma discharges promotes the deposition of homogeneous coatings onto the microspheres and within their pores, down to 1 μm.

Abstract: This work focuses on the use of tailored copper oxide nanoarchitectures as multi-functional materials for the sustainable production of hydrogen and its on-line detection. An innovative copper(II) precursor, Cu(hfa)2TMEDA, was adopted in the CVD of CuxO (x=1,2) nanosystems under both O2 and O2+H2O atmospheres on Si(100) and Al2O3 substrates. A multi-technique characterization indicates that both the phase composition (from Cu2O to CuO) and morphology (from continuous films to entangled quasi-1D nanosystems) can be tailored by varying the growth temperature and reaction atmosphere. The obtained CuxO nanodeposits are active in the photocatalytic H2 production from aqueous solutions under UV-Vis irradiation and display interesting gas sensing performances towards hydrogen detection even at moderate temperatures.