Abstract: We have expanded the double perovskite family of materials with the unusual combination of layered order in the A sublattice and rock salt order over the B sublattice to compounds NaLaFeWO6 and NaNdFeWO6. The materials have been synthesized and studied by powder X-ray diffraction, neutron diffraction, electron diffraction, magnetic measurements, X-ray absorption spectroscopy, dielectric measurements, and second harmonic generation. At room temperature, the crystal structures of both compounds can be defined in the noncentrosymmetric monoclinic P2(1) space group resulting from the combination of ordering both in the A and B sublattices, the distortion of the cell due to tilting of the octahedra, and the displacement of certain cations. The magnetic studies show that both compounds are ordered antiferromagnetically below T-N approximate to 25 K for NaLaFeWO6 and at similar to 21 K for NaNdFeWO6. The magnetic structure of NaNdFeWO6 has been solved with a propagation vector k = (1/2 0 1/2) as an antiferromagnetic arrangement of Fe and Nd moments. Although the samples are potential multiferroics, the dielectric measurements do not show a ferroelectric response.

Abstract: Alloyed metal nanocatalysts are of environmental and economic importance in a plethora of chemical technologies. During the catalyst lifetime, supported alloy nanoparticles undergo dynamic changes which are well-recognized but still poorly understood. High-temperature O-2-H-2 redox cycling was applied to mimic the lifetime changes in model Pt13In9 nanocatalysts, while monitoring the induced changes by insitu quick X-ray absorption spectroscopy with one-second resolution. The different reaction steps involved in repeated Pt13In9 segregation-alloying are identified and kinetically characterized at the single-cycle level. Over longer time scales, sintering phenomena are substantiated and the intraparticle structure is revealed throughout the catalyst lifetime. The insitu time-resolved observation of the dynamic habits of alloyed nanoparticles and their kinetic description can impact catalysis and other fields involving (bi)metallic nanoalloys.

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.

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: 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: 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: 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: 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: 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: 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.