Abstract: We introduce a new method to measure structure factors from parallel beam electron diffraction (PBED) patterns. Bloch wave refinement routines were developed which can minimise the difference between simulated and experimental Bragg intensities via variation of structure factors, Debye parameters, specimen thickness and -orientation. Due to plane wave illumination, the PBED refinement is highly efficient not only in computational respect, but also concerning the experimental effort since energy filtering is shown to have no significant effect on the refinement results. The PBED method was applied to simulated GaAs diffraction patterns to derive systematic errors and rules for the identification of plausible refinement results. The evaluation of experimental GaAs PBED patterns yields a 200 X-ray structure factor of -6.33±0.14. Additionally, we obtained -6.35±0.13 from two-dimensional convergent beam electron diffraction refinements. Both results confirm density functional theory calculations published by Rosenauer et al. and indicate the inaccuracy of isolated atom scattering data, which is crucial e.g. for the composition evaluation by lattice fringe analysis.

Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atomcounting diagnosed by combining a thorough statistical method and detailed image simulations.

Abstract: The atomic scattering amplitudes of the various atoms of the systems Ga1−xInxAs, GaAs1−xNx and InAs1−xNx are calculated using the density functional theory (DFT) approach. The scattering amplitudes of N, Ga, As and In in the model systems are compared with the frequently used Doyle and Turner values. Deviation from the latter values is found for small scattering vectors (s<0.3Å−1) and for these scattering vectors dependence on the orientation of the scattering vector and the chemical environment is reported. We suggest a parametrization of these modified scattering amplitudes (MASAs) for small scattering vectors (s<1.0Å−1). The MASAs are exploited within zero pressure classical Metropolis Monte Carlo (MC), finite temperature calculations to investigate the effect of quantum well size on the electron {002} structure factor (SF) of Ga1−xInxAs quantum wells.

Abstract: We report on the aptadetection of chloramphenicol (CAP) using electrochemical impedance spectroscopy. The detection principle is based on the changes of the interfacial properties of the electrode after the interaction of the ssDNA aptamers with the target molecules. The electrode surface is partially blocked due to the formation of the aptamer-CAP complex, resulting in an increase of the interfacial electron-transfer resistance of the redox probe detected by electrochemical impedance spectroscopy or cyclic voltammetry. We observed that the ratio of polarization resistance had a linear relationship with the concentrations of CAP in the range of 1.76127 nM, and a detection limit of 1.76 nM was obtained. The covalent binding of CAP-aptamer on the electrode surface combined with the unique properties of aptamers and impedimetric transduction leads to the development of a stable and sensitive electrochemical aptasensor for CAP.

Abstract: Iron mineral containing sensory dendrites in the inner lining of the upper beak of homing pigeons [1] and various bird species [2] are the first candidate structures for an avian magnetic field receptor. A new concept of magnetoreception [3, 4] is based on detailed ultra-structural optical and electron microscopy analyses in combination with synchrotron radiation microscopic X-ray fluorescence analysis (micro-XRF) and microscopic X-ray absorption near edge structures (micro-XANES). Several behavioral experiments [5, 6] and first mathematical simulations [6] affirm our avian magnetoreceptor model. The iron minerals inside the dendrites are housed in three different subcellular compartments (bullets, platelets, vesicles), which could be clearly resolved and identified by electron microscopy on ultrathin sections [1, 3]. Micro-XRF and micro-XANES data obtained at HASYLAB beamline L added information about the elemental distribution and Fe speciation [3], but are averaged over the complete dendrite due to limited spatial resolution. Here we present recently performed micro-XRF maps with sub-micrometer resolution (ESRF ID21), which reveal for the first time subcellular structural information from almost bulk-like dendrite sample material. Due to the thickness of 30 μm the microarchitecture of the dendrites can be considered as undisturbed and artefacts introduced by sectioning might be widely reduced.

Abstract: We study the mechanisms of CO2 conversion in a nanosecond repetitively pulsed (NRP) discharge, by means of a chemical kinetics model. The calculated conversions and energy efficiencies are in reasonable agreement with experimental results over a wide range of specific energy input values, and the same applies to the evolution of gas temperature and CO2 conversion as a function of time in the afterglow, indicating that our model provides a realistic picture of the underlying mechanisms in the NRP discharge and can be used to identify its limitations and thus to suggest further improvements. Our model predicts that vibrational excitation is very important in the NRP discharge, explaining why this type of plasma yields energy-efficient CO2 conversion. A significant part of the CO2 dissociation occurs by electronic excitation from the lower vibrational levels toward repulsive electronic states, thus resulting in dissociation. However, vibration−translation (VT) relaxation (depopulating the higher vibrational levels) and CO + O recombination (CO + O + M → CO2 + M), as well as mixing of the converted gas with fresh gas entering the plasma in between the pulses, are limiting factors for the conversion and energy efficiency. Our model predicts that extra cooling, slowing down the rate of VT relaxation and of the above recombination reaction, thus enhancing the contribution of the highest vibrational levels to the overall CO2 dissociation, can further improve the performance of the NRP discharge for energy-efficient CO2 conversion.

Abstract: Theoretical studies on molecule-metal surface reactions have so far been limited to small surface unit cells due to computational costs. Here, for the first time molecular dynamics simulations on very large surface unit cells at the level of density functional theory are performed, allowing a direct comparison to experiments performed on a curved crystal. Specifically, the reaction of D-2 on a curved Pt crystal is investigated with a neural network potential (NNP). The developed NNP is also accurate for surface unit cells considerably larger than those that have been included in the training data, allowing dynamical simulations on very large surface unit cells that otherwise would have been intractable. Important and complex aspects of the reaction mechanism are discovered such as diffusion and a shadow effect of the step. Furthermore, conclusions from simulations on smaller surface unit cells cannot always be transfered to larger surface unit cells, limiting the applicability of theoretical studies of smaller surface unit cells to heterogeneous catalysts with small defect densities.

Abstract: Urban atmospheres in modern cities carry characteristic mixtures of particulate pollution which are potentially aggravating for chronic respiratory patients (CRP). Although air quality surveys can be detailed, the obtained information is not always useful to evaluate human health effects. This paper presents a novel approach to estimate particle deposition rates in airways of CRP, based on real air pollution data. By combining computational fluid dynamics with physical-chemical characteristics of particulate pollution, deposition rates are estimated for particles of different toxicological relevance, that is, minerals, iron oxides, sea salts, ammonium salts, and carbonaceous particles. Also, it enables some qualitative evaluation of the spatial, temporal, and patient specific effects on the particle dose upon exposure to the urban atmosphere. Results show how heavy traffic conditions increases the deposition of anthropogenic particles in the trachea and lungs of respiratory patients (here, +0.28 and +1.5 μg·h1, respectively). In addition, local and synoptic meteorological conditions were found to have a strong effect on the overall dose. However, the pathology and age of the patient was found to be more crucial, with highest deposition rates for toxic particles in adults with a mild anomaly, followed by mild asthmatic children and adults with severe respiratory dysfunctions (7, 5, and 3 μg·h1, respectively).

Abstract: End-group-functionalized hyperbranched polymers were synthesized to act as a carbon nanotube (CNT) surfactant in aqueous solutions. Variation of the percentage of triphenylmethyl (trityl) functionalization and of the molar mass of the hyperbranched polyglycerol (PG) core resulted in the highest measured surfactant efficiency for a 5000 g/mol PG with 5.6% of the available hydroxyl end-groups replaced by trityl functions, as shown by UV-vis measurements. Semiempirical model calculations suggest an even higher efficiency for PG5000 with 2.5% functionalization and maximal molecule specific efficiency in general at low degrees of functionalization. Addition of trityl groups increases the surfactant-nanotube interactions in comparison to unfunctionalized PG because of pi-pi stacking interactions. However, at higher functionalization degrees mutual interactions between trityl groups come into play, decreasing the surfactant efficiency, while lack of water solubility becomes an issue at very high functionalization degrees. Low molar mass surfactants are less efficient compared to higher molar mass species most likely because the higher bulkiness of the latter allows for a better CNT separation and stabilization. The most efficient surfactant studied allowed dispersing 2.85 mg of CNT in 20 mL with as little as 1 mg of surfactant. These dispersions, remaining stable for at least 2 months, were mainly composed of individual CNTs as revealed by electron microscopy.

Abstract: Magnetotransport properties of a pseudomorphic GsAs/Ga0.8In0.2As/Ga0.75Al0.25As heterostructure are investigated in pulsed magnetic fields up to 50 T and at temperatures of T = 1.4 and 4.2 K. The structure studied consists of a Si delta layer parallel to a Ga0.8In0.2As quantum well (QW). The dark electron density of the structure is n(c) = 1.67 x 10(16) m(-2). By illumination the density can be increased up to a factor of 4; this way the second subband in the Ga0.08In0.2As QW can become populated as well as the Si delta layer. The presence of electrons in the delta layer results in drastic changes in the transport data, especially at magnetic fields beyond 30 T. The phenomena observed are interpreted as (i) magnetic freeze-out of carriers in the delta layer when a low density of electrons is present in the delta layer, and (ii) quantization of the electron motion in the two-dimensional electron gases in both the Ga0.8In0.2As QW and the Si delta layer in the case of high densities. These conclusions are corroborated by the numerical results of our theoretical model. We obtain satisfactory agreement between model and experiment.

Abstract: The combination of energy-dispersive X-ray spectroscopy (EDX) and electron tomography is a powerful approach to retrieve the 3D elemental distribution in nanomaterials, providing an unprecedented level of information for complex, multi-component systems, such as semiconductor devices, as well as catalytic and plasmonic nanoparticles. Unfortunately, the applicability of EDX tomography is severely limited because of extremely long acquisition times and high electron irradiation doses required to obtain 3D EDX reconstructions with an adequate signal-to-noise ratio. One possibility to address this limitation is intelligent denoising of experimental data using prior expectations about the objects of interest. Herein, this approach is followed using the deep learning methodology, which currently demonstrates state-of-the-art performance for an increasing number of data processing problems. Design choices for the denoising approach and training data are discussed with a focus on nanoparticle-like objects and extremely noisy signals typical for EDX experiments. Quantitative analysis of the proposed method demonstrates its significantly enhanced performance in comparison to classical denoising approaches. This allows for improving the tradeoff between the reconstruction quality, acquisition time and radiation dose for EDX tomography. The proposed method is therefore especially beneficial for the 3D EDX investigation of electron beam-sensitive materials and studies of nanoparticle transformations.

Abstract: SrFe0.75Mo0.25O3-delta has been recently discovered as an extremely efficient electrode for intermediate temperature solid oxide fuel cells (IT-SOFCs). We have performed structural and magnetic studies to fully characterize this multifunctional material. We have observed by powder neutron diffraction (PND) and transmission electron microscopy (TEM) that its crystal symmetry is better explained with a tetragonal symmetry (I4/mcm space group) than with the previously reported orthorhombic symmetry (Pnma space group). The temperature dependent magnetic properties indicate an exceptionally high magnetic ordering temperature (T-N similar to 750 K), well above room temperature. The ordered magnetic structure at low temperature was determined by PND to be an antiferromagnetic coupling of the Fe cations. Mossbauer spectroscopy corroborated the PND results. A detailed study, with X-ray absorption spectroscopy (XAS), in agreement with the Mossbauer results, confirmed the formal oxidation states of the cations to be mixed valence Fe3+/4+ and Mo6+.

Abstract: Under high-enough values of perpendicularly-applied magnetic field and current, a type-II superconductor presents a finite resistance caused by the vortex motion driven by the Lorentz force. To recover the dissipation-free conduction state, strategies for minimizing vortex motion have been intensely studied in the last decades. However, the non-local vortex motion, arising in areas depleted of current, has been scarcely investigated despite its potential application for logic devices. Here, we propose a route to transfer vortices carried by non-local motion through long distances (up to 10 micrometers) in 50 nm-wide superconducting WC nanowires grown by Ga+ Focused Ion Beam Induced Deposition. A giant non-local electrical resistance of 36 Omega has been measured at 2 K in 3 mu m-long nanowires, which is 40 times higher than signals reported for wider wires of other superconductors. This giant effect is accounted for by the existence of a strong edge confinement potential that hampers transversal vortex displacements, allowing the long-range coherent displacement of a single vortex row along the superconducting channel. Experimental results are in good agreement with numerical simulations of vortex dynamics based on the time-dependent Ginzburg-Landau equations. Our results pave the way for future developments on information technologies built upon single vortex manipulation in nano-superconductors.