Simulation of conjugate radiation–forced convection heat transfer in a porous medium using the lattice Boltzmann method

In this paper, a lattice Boltzmann method is employed to simulate the conjugate radiation–forced convection heat transfer in a porous medium. The absorbing, emitting, and scattering phenomena are fully included in the model. The effects of different parameters of a silicon carbide porous medium including porosity, pore size, conduction–radiation ratio, extinction coefficient and kinematic viscosity ratio on the temperature and velocity distributions are investigated. The convergence times of modified and regular LBMs for this problem are 15 s and 94 s, respectively, indicating a considerable reduction in the solution time through using the modified LBM. Further, the thermal plume formed behind the porous cylinder elongates as the porosity and pore size increase. This result reveals that the thermal penetration of the porous cylinder increases with increasing the porosity and pore size. Finally, the mean temperature at the channel output increases by about 22% as the extinction coefficient of fluid increases in the range of 0–0.03.

     

Synthesis of Arylidene – Isoquinolinones bearing Combretastatin Skeleton by Cyclocarbopalladation/cross coupling Tandem Heck-Suzuki Miaura Reactions using nano catalyst Pd@Py-IL-SPION

Cyclocarbopalladation/cross-coupling cascade intramolecular Heck–Suzuki–Miyaura reactions is applied for the first time by palladium immobilized on pyridine-imidazolium ionic liquid supported magnetic iron oxide nanoparticle catalyst (denoted Pd@Py-IL-SPION) for the last step to synthesize trisubstituted arylidene–isoquinolinones derivatives having Combretastatin skeleton. The reaction is performed via propargylamide intermediates prepared by Ugi 4-CR reactions, which undergoes intramolecular Heck–Suzuki–Miyaura domino reaction to produce the desired trisubstituted arylidene-isoquinolinones. The method shows full regio- and stereoselectivity derives from the particular Pd-catalyzed syn-insertion of triple bond.     

Potentials of boiling heat transfer in advanced thermal energy systems

Journal of Thermal Analysis and Calorimetry - Boiling process is a highly efficient mechanism of heat transfer, which has an important role in industrial and domestic sectors. In this process, a...     

Fabrication of poly(ϵ-caprolactone)/paclitaxel (core)/chitosan/zein/multi-walled carbon nanotubes/doxorubicin (shell) nanofibers against MCF-7 breast cancer

In the present study, paclitaxel (PTX), multi-walled carbon nanotubes (MWCNTs), and doxorubicin (DOX) have been simultaneously doped into the poly(ϵ-caprolactone) (PCL)/chitosan/zein core-shell nanofibers to increase its cytotoxicity for MCF-7 breast cancers killing. The physico-chemical properties of synthesized nanofibers were determined by scanning electron microscope, Fourier-transform infrared spectroscopy, tensile strength, and degradation rate determinations. The in vitro release studies demonstrated the sustained release of drugs from core-shell nanofibrous scaffold. The cytotoxicity and compatibility of core-shell nanofibers were investigated by their treating with MCF-7 breast cancer cells and L929 normal cells, respectively. PCL/PTX/chitosan/zein/MWCNTs/DOX core-shell nanofibers containing 1 wt% MWCNTs, 100 μg ml⁻¹ DOX and 100 μg ml⁻¹ PTX had a high biocompatibility with a 84% MCF-7 cancer cells killing. The in vivo studies revealed the synergic effects of MWCNTs and anticancer drugs on the tumor inhibition. This method could be considered as a new way for developing of MWCNTs loaded-nanofibers for cancer treatment in future.     

Preparation of different graphene nanostructures for hydrogen adsorption

In this study, different types of graphene were synthesized to investigate hydrogen adsorption capacity at different pressures (0–34 bar) at room temperature (298 K). Graphene and nanoporous graphene were prepared by Chemical Vapor Deposition (CVD) method, using methane as a carbon source at a temperature of 900 °C over copper plates and nickel oxide nanocatalyst. The nickel oxide nanocatalyst was prepared by sol–gel method, whereas graphene oxide was prepared through modified Hummer's method. The products were characterized by X‐ray diffraction, field emission‐scanning electron microscopy, energy dispersive spectroscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, Brunauer–Emmett–Teller and Raman spectroscopy. The adsorption of hydrogen was done by volumetric method. High adsorption capacity was achieved in nanoporous graphene because of its high pore volume (2.11 cm³/g) and large specific surface area (850 m²/g). Hydrogen adsorption values for nanoporous graphene, graphene and graphene oxide were determined as 2.56, 1.70 and 0.74 wt%, respectively. In addition, the hydrogen adsorption of graphene nanostructures fitted nicely to the selected two‐parameter and three‐parameter adsorption isotherm models. The adsorption isotherm model coefficients have been found for a 0–34 bar pressure range. The parameter values for all adsorbents showed proper conformity to the model and experimental data. Copyright © 2016 John Wiley & Sons, Ltd.     

SMFs-supported Pd nanocatalysts in selective acetylene hydrogenation:Pore structure-dependent deactivation mechanism

In the present study,CNFs,ZnO and Al2O3 were deposited on the SMFs panels to investigate the deactivation mechanism of Pd-based catalysts in selective acetylene hydrogenation reaction.The examined supports were characterized by SEM,NH3-TPD and N2adsorption-desorption isotherms to indicate their intrinsic characteristics.Furthermore,in order to understand the mechanism of deactivation,the resulted green oil was characterized using FTIR and SIM DIS.FTIR results confirmed the presence of more unsaturated constituents and then,more branched hydrocarbons formed upon the reaction over alumina-supported catalyst in comparison with the ones supported on CNFs and ZnO,which in turn,could block the pores mouths.Besides the limited hydrogen transfer,N2 adsorption-desorption isotherms results supported that the lowest pore diameters of Al2O3/SMFs close to the surface led to fast deactivation,compared with the other catalysts,especially at higher temperatures.     

SMFs-supported Pd nanocatalysts in selective acetylene hydrogenation: Pore structure-dependent deactivation mechanism

In the present study, CNFs, ZnO and Al₂O₃ were deposited on the SMFs panels to investigate the deactivation mechanism of Pd-based catalysts in selective acetylene hydrogenation reaction. The examined supports were characterized by SEM, NH₃-TPD and N₂ adsorption-desorption isotherms to indicate their intrinsic characteristics. Furthermore, in order to understand the mechanism of deactivation, the resulted green oil was characterized using FTIR and SIM DIS. FTIR results confirmed the presence of more unsaturated constituents and then, more branched hydrocarbons formed upon the reaction over alumina-supported catalyst in comparison with the ones supported on CNFs and ZnO, which in turn, could block the pores mouths. Besides the limited hydrogen transfer, N₂ adsorption-desorption isotherms results supported that the lowest pore diameters of Al₂O₃/SMFs close to the surface led to fast deactivation, compared with the other catalysts, especially at higher temperatures.     

Immersed boundary—thermal lattice Boltzmann method for the moving simulation of non-isothermal elliptical particles

Journal of Thermal Analysis and Calorimetry - The study is concerned with the understanding of elliptical particles’ transport behavior coupled with heat transfer effects. A combination of...     

Application of a dispersive micro‐solid‐phase extraction method for pre‐concentration and ultra‐trace determination of cadmium ions in water and biological samples

A method for the trace determination of cadmium ions in water, human urine and human blood serum samples using ultrasonic‐assisted dispersive micro‐solid‐phase extraction (UA‐D‐μSPE) was developed. Silica‐coated magnetic nanoparticles were coated with polythiophene, and the resulting sorbent was characterized using thermogravimetry, differential thermal analysis, scanning electron microscopy, Fourier transform infrared spectrometry and X‐ray diffraction. Following UA‐D‐μSPE, cadmium ions were quantified using graphite furnace atomic absorption spectrometry. A Box–Behnken design was used for optimization of important sorption and desorption parameters in UA‐D‐μSPE: in the sorption step, pH of solution, sorption amount and sonication time for sorption; in the desorption step, concentration of eluent, volume of eluent and sonication time. The optimum conditions for the method were: pH of solution, 7.5; sonication time for sorption, 3 min; sorption amount, 35 mg; type and concentration of eluent, HCl and 1.1 mol l^?1; volume of eluent, 360 μl; sonication time for desorption, 110 s. Under the optimized conditions the limit of detection and relative standard deviation for the detection of cadmium ions by UA‐D‐μSPE were found to be 0.8 ng l^?1 and <6%, respectively.     

Determination of the Heat Transfer Coefficient of Metal Oxide Based Water Nanofluids in a Laminar Flow Regime Using an Adaptive Neuro-Fuzzy Inference System

In order to enhance the thermal properties of turbine oil (TO), three different nanoparticles (CuO, Al₂O₃, and TiO₂) are loaded into the TO. To measure the thermal performance of nanoparticle-based TO nanofluids at laminar flow and under constant heat flux boundary conditions, an experimental setup was applied. The obtained data clearly demonstrate the positive effect of all nanoparticles on the heat transfer rate of TO. As the most important factor, the heat transfer coefficient of the abovementioned two-phase systems is increased upon increasing both the volume concentration and the flow rate. An adaptive neuro-fuzzy inference system (ANFIS) is applied for modeling the effect of critical parameters on the heat transfer coefficient of nanoparticle-TO based nanofluids numerically. The results are compared with experimental ones for training and test data. The results suggest that the developed model is valid enough and promising for predicting the extant of the heat transfer coefficient. R² and MSE values for all data were 0.990208751 and 108.1150734, respectively. Based on the results, it is obvious that our proposed modeling by ANFIS is efficient and valid, which can be expanded for more general states.