Electrophoretic deposition of ZnO–CeO2 mixed oxide nanoparticles

ZnO–CeO₂ nanoparticles were synthesized by microwave combustion and deposited by electrophoretic deposition (EPD). The effect of using two different alcohols, ethanol and methanol, was investigated on EPD behavior and morphology of deposited film. Moreover, the effect of concentration of nanoparticles and applied voltage on the mass of deposit and the variation in the current density were investigated. With a change in the alcohol type, the surface morphology of deposition changed and some voids were observed on the deposition surface in ethanol. In all cases, with increasing concentration of nanoparticles in suspension, the number of developed cracks increased. Besides, a rise in voltage led to an increase in the number of cracks. The EPD processes in ethanol and methanol suspension were simulated over time using different zero boundary conditions. Hemi‐spherical morphology was seen for the nanoparticles deposited in ethanol. This kind of growth was simulated based on the changes in electrical field.     

A Novel Model for Predicting the Dense Phase Behavior of 3D Gas‐Solid Fluidized Beds

A novel phenomenological discrete bubble model was developed and tested for prediction of the hydrodynamic behavior of the dense phase of a 3D gas‐solid cylindrical fluidized bed. The mirror image technique was applied to take into account the effects of the bed wall. The simulation results were validated against experimental data reported in the literature that were obtained by positron emission particle tracking. The time‐averaged velocity profiles of particles predicted by the developed model were found to agree well with experimental data. The initial bubble diameter had no significant influence on the time‐averaged circulating pattern of solids in the bed. The model predictions clearly indicate that the developed model can fairly predict the hydrodynamic behavior of the dense phase of 3D gas‐solid cylindrical fluidized beds.     

Adsorption site analysis of impurity embedded single-walled carbon nanotube bundles

Bundle morphology and adsorptive contributions from nanotubes and impurities are studied both experimentally and by simulation using a computer-aided methodology, which employs a small physisorbed probe molecule to explore the porosity of nanotube samples. Grand canonical Monte Carlo simulation of nitrogen adsorption on localized sites of a bundle is carried out to predict adsorption in its accessible internal pore volume and on its external surface as a function of tube diameter. External adsorption is split into the contributions from the clean surface of the outermost nanotubes of the bundle and from the surface of the impurities. The site-specific isotherms are then combined into a global isotherm for a given sample using knowledge of its tube-diameter distribution obtained by Raman spectroscopy. The structural parameters of the sample, such as the fraction of open-ended nanotubes and the contributions from impurities and nanotube bundles to total external surface area, are determined by fitting the experimental nitrogen adsorption data to the simulated isotherm. The degree of closure between experimental and calculated adsorption isotherms for samples manufactured by two different methods, to provide different nanotube morphology and contamination level, further strengthens the validity and resulting interpretations based on the proposed approach. The average number of nanotubes per bundle and average bundle size, within a sample, are also quantified. The proposed method allows for extrapolation of adsorption properties to conditions where the purification process is 100% effective at removing all impurities and opening access to all intrabundle adsorption sites.     

99m Tc-labeled teicoplanin and its biological evaluation in experimental animals for detection of bacterial infection

Labeling of teicoplanin with ^99m Tc using SnCl₂·2H₂O as reducing agent was performed. The dependence of the ^99m Tc-teicoplanin yield on the concentrations of teicoplanin and reducing agent, pH of the reaction mixture, reaction time, and reaction temperature was studied. Under optimum conditions (2 mg of teicoplanin, 5 μg of SnCl₂·2H₂O, pH 9, 30 min, 25°C), the labeling yield of ^99m Tc-teicoplanin of 87.7 ± 1.3% was achieved. ^99m Tc-teicoplanin is stable for 4 h after labeling; then its relative content decreased gradually to reach 81.7 ± 1.1% in 8 h. Biodistribution studies in mice with infection induced in the left thigh by Staphylococcus aureus were carried out. The bacterial infected thigh/contralateral thigh uptake ratio (T/NT) was evaluated. The time for the maximum accumulation of ^99mTc-teicoplanin in the infection site was 2 h after administration of the labeled compound. The abscess-to-muscle ratio for ^99m Tc-teicoplanin was 4.33 ± 0.3, while that for commercially available ^99m Tc-ciprofloxacin was 3.8 ± 0.5 under similar conditions. Thus, ^99m Tc-teicoplanin can be used for infection imaging.     

Experimental study and numerical modeling of arc and weld pool in stationary GTA welding of pure aluminum

In this study, a 2D mathematical model was developed for both arc and weld pool in stationary GTA welding. In arc model, current continuity equation has been solved in both arc and cathode regions without any assumption of fixed current density on the cathode surface which was essential in most previous works. The results of arc model were presented for both copper and aluminum anodes to investigate the effect of anode material on arc properties. It was seen that aluminum anode has lower maximum anode current density and heat flux but the distributions are wider than copper anode. Furthermore, shear stress on anode surface is higher in the case of aluminum anode. Also, calculated results of this study were compared with other available theoretical and experimental results. It has been shown that the agreement between calculated and experimental results was fairly good. The necessary information to simulate the weld pool, including the anode current density and heat flux to the workpiece were taken from the arc model. In this model, due to high thermal conductivity of pure aluminum, fluid flow into the weld pool was ignored. Effects of arc variables, i.e., arc length, applied current and welding time on the shape and size of the weld pool were investigated as well. In order to check the validity of the weld pool model, a comparison between calculated results and the results of our experimental tests was conducted. Generally, these comparisons reveal an acceptable agreement between calculated results and experimental data.     

Design of MMIC oscillators using GaAs 0.2 μm PHEMT technology

We propose a feedback type oscillator and two negative resistance oscillators.These microwave oscillators have been designed in the S band frequency.A relatively symmetric resonator is used in the feed...     

Pressure Management Model for Urban Water Distribution Networks

A technique for leakage reduction is pressure management, which considers the direct relationship between leakage and pressure. To control the hydraulic pressure in a water distribution system, water levels in the storage tanks should be maintained as much as the variations in the water demand allows. The problem is bounded by minimum and maximum allowable pressure at the demand nodes. In this study, a Genetic Algorithm (GA) based optimization model is used to develop the optimal hourly water level variations in a storage tank in different seasons in order to minimize the leakage level. Resiliency and failure indices of the system have been considered as constraints in the optimization model to achieve the minimum required performance. In the proposed model, the results of a water distribution simulation model are used to train an Artificial Neural Network (ANN) model. Outputs of the ANN model as a hydraulic pressure function is then linked to a GA based optimization model to simulate hydraulic pressure and leakage at each node of the water distribution network based on the water level in the storage tank, water consumption and elevation of each node. The proposed model is applied for pressure management of a major pressure zone with an integrated storage facility in the northwest part of Tehran Metropolitan area. The results show that network leakage can be reduced more than 30% during a year when tank water level is optimized by the proposed model.