Abstract: When considering the modelling of small particle dispersion in the lower part of the Atmospheric Boundary Layer (ABL) using Reynolds Averaged Navier Stokes simulations, the particle paths depend on the velocity profile and on the turbulence kinetic energy, from which the fluctuating velocity components are derived to predict turbulent dispersion. It is therefore important to correctly reproduce the ABL, both for the velocity profile and the turbulence kinetic energy profile. For RANS simulations with the standard kå model, Richards and Hoxey (1993. Appropriate boundary conditions for computational wind engineering models using the kå turbulence model. Journal of Wind Engineering and Industrial Aerodynamics 4647, 145153.) proposed a set of boundary conditions which result in horizontally homogeneous profiles. The drawback of this method is that it assumes a constant profile of turbulence kinetic energy, which is not always consistent with field or wind tunnel measurements. Therefore, a method was developed which allows the modelling of a horizontally homogeneous turbulence kinetic energy profile that is varying with height. By comparing simulations performed with the proposed method to simulations performed with the boundary conditions described by Richards and Hoxey (1993. Appropriate boundary conditions for computational wind engineering models using the kå turbulence model. Journal of Wind Engineering and Industrial Aerodynamics 4647, 145153.), the influence of the turbulence kinetic energy on the dispersion of small particles over flat terrain is quantified.

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: Nanoscale Zr-based metal organic frameworks (MOFs) UiO-66 and UiO-67 were studied as potential anticancer drug delivery vehicles. Two model drugs were used, hydrophobic paclitaxel and hydrophilic cisplatin, and were adsorbed onto/into the nano MOFs (NMOFs). The drug loaded MOFs were further encapsulated inside a modified poly(epsilon-caprolactone) with d-alpha-tocopheryl polyethylene glycol succinate polymeric matrix, in the form of microparticles, in order to prepare sustained release formulations and to reduce the drug toxicity. The drugs physical state and release rate was studied at 37 degrees C using Simulated Body Fluid. It was found that the drug release depends on the interaction between the MOFs and the drugs while the controlled release rates can be attributed to the microencapsulated formulations. The in vitro antitumor activity was assessed using HSC-3 (human oral squamous carcinoma; head and neck) and U-87 MG (human glioblastoma grade IV; astrocytoma) cancer cells. Cytotoxicity studies for both cell lines showed that the polymer coated, drug loaded MOFs exhibited better anticancer activity compared to free paclitaxel and cisplatin solutions at different concentrations.

Abstract: Bifunctionality is a key feature of many industrial catalysts, supported metal clusters and particles in particular, and the development of such catalysts for the CO2 reduction reaction (CO2RR) to hydrocarbons and alcohols is gaining traction in light of recent advancements in the field. Carbon-supported Cu nanoparticles are suitable candidates for integration in the state-of-the-art reaction interfaces, and here, we propose, synthesize, and evaluate a bifunctional Ni–N-doped-C-supported Cu electrocatalyst, in which the support possesses active sites for selective CO2 conversion to CO and Cu nanoparticles catalyze either the direct CO2 or CO reduction to hydrocarbons. In this work, we introduce the scientific rationale behind the concept, its applicability, and the challenges with regard to the catalyst. From the practical aspect, the deposition of Cu nanoparticles onto carbon black and Ni–N–C supports via an ammonia-driven deposition precipitation method is reported and explored in more detail using X-ray diffraction, thermogravimetric analysis, and hydrogen temperature-programmed reduction. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and energy-dispersive X-ray spectroscopy (EDXS) give further evidence of the presence of Cu-containing nanoparticles on the Ni–N–C supports while revealing an additional relationship between the nanoparticle’s composition and the electrode’s electrocatalytic performance. Compared to the benchmark carbon black-supported Cu catalysts, Ni–N–C-supported Cu delivers up to a 2-fold increase in the partial C2H4 current density at −1.05 VRHE (C1/C2 = 0.67) and a concomitant 10-fold increase of the CO partial current density. The enhanced ethylene production metrics, obtained by virtue of the higher intrinsic activity of the Ni–N–C support, point out toward a synergistic action between the two catalytic functionalities.

Abstract: Laser-induced manipulation of magnetism at the nanoscale is a rapidly growing research topic with potential for applications in spintronics. In this work, we address the role of the scattering cross section, thermal effects, and laser fluence on the magnetic, structural, and chemical stability of individual magnetic nanoparticles excited by single femtosecond laser pulses. We find that the energy transfer from the fs laser pulse to the nanoparticles is limited by the Rayleigh scattering cross section, which in combination with the light absorption of the supporting substrate and protective layers determines the increase in the nanoparticle temperature. We investigate individual Co nanoparticles (8 to 20 nm in size) as a prototypical model system, using x-ray photoemission electron microscopy and scanning electron microscopy upon excitation with single femtosecond laser pulses of varying intensity and polarization. In agreement with calculations, we find no deterministic or stochastic reversal of the magnetization in the nanoparticles up to intensities where ultrafast demagnetization or all-optical switching is typically reported in thin films. Instead, at higher fluences, the laser pulse excitation leads to photo-chemical reactions of the nanoparticles with the protective layer, which results in an irreversible change in the magnetic properties. Based on our findings, we discuss the conditions required for achieving laser-induced switching in isolated nanomagnets.

Abstract: Morphological characterization of nanoparticle assemblies and hybrid nanomaterials is critical in determining their structure-property relationships as well as in the development of structures with desired properties. Electron tomography has become a widely utilized technique for the three-dimensional characterization of nanoparticle assemblies. However, the extraction of quantitative morphological parameters from the reconstructed volume can be a complex and labor-intensive task. In this study, we aim to overcome this challenge by automating the volumetric segmentation process applied to three-dimensional reconstructions of nanoparticle assemblies. The key to enabling automated characterization is to assess the performance of different volumetric segmentation methods in accurately extracting predefined quantitative descriptors for morphological characterization. In our methodology, we compare the quantitative descriptors obtained through manual segmentation with those obtained through automated segmentation methods, to evaluate their accuracy and effectiveness. To show generality, our study focuses on the characterization of assemblies of CdSe/CdS quantum dots, gold nanospheres and CdSe/CdS encapsulated in polymeric micelles, and silica-coated gold nanorods decorated with both CdSe/CdS or PbS quantum dots. We use two unsupervised segmentation algorithms: the watershed transform and the spherical Hough transform. Our results demonstrate that the choice of automated segmentation method is crucial for accurately extracting the predefined quantitative descriptors. Specifically, the spherical Hough transform exhibits superior performance in accurately extracting quantitative descriptors, such as particle size and interparticle distance, thereby allowing for an objective, efficient, and reliable volumetric segmentation of complex nanoparticle assemblies.

Abstract: A wave-packet time evolution method, based on the split-operator technique, is developed to investigate the scattering of quasiparticles at a normal-superconductor interface of arbitrary profile and shape. As a practical application, we consider a system where low-energy electrons can be described as Dirac particles, which is the case for most two-dimensional materials, such as graphene and transition-metal dichalcogenides. However, the method is easily adapted for other cases such as electrons in few-layer black phosphorus or any Schrodinger quasiparticles within the effective mass approximation in semiconductors. We employ the method to revisit Andreev reflection in mono-, bi-, and trilayer graphene, where specular-and retro-reflection cases are observed for electrons scattered by a steplike superconducting region. The effect of opening a zero-gap channel across the superconducting region on the electron and hole scattering is also addressed, as an example of the versatility of the technique proposed here.

Abstract: In this work, we used a solution-processed TiO2 layer between Cu2ZnSnSe4 and CdS buffer layer to reduce the recombination at the p–n junction. Introducing the TiO2 layer showed a positive impact on VOC but fill factor and efficiency decreased. Using a KCN treatment, we could create openings in the TiO2 layer, as confirmed by transmission electron microscopy measurements. Formation of these openings in the TiO2 layer led to the improvement of the short-circuit current, fill factor, and the efficiency of the modified solar cells.

Abstract: The size, morphology and configuration of Ni4Ti3 precipitates in a single-crystal NiTi alloy have been investigated by two-dimensional transmission electron microscopy-based image analysis and three-dimensional reconstruction from slice-and-view images obtained in a focused ion beam/scanning electron microscopy (FIB/SEM) dual-beam system. Average distances between the precipitates measured along the compression direction correlate well between both techniques, while particle shape and configuration data is best obtained from FIB/SEM. Precipitates form pockets of B2 of 0.54 ìm in the compression direction and 1 ìm perpendicular to the compression direction.