CuInS2/SiNWs/Si composite material for application as potential photoelectrode for photoelectrochemical hydrogen generation

This work aims at developing a new composite material based on nanosized semiconducting CuInS₂ (CIS) particles combined with silicon nanowires grown on a silicon substrate (SiNWs/Si) for photoelectrochemical (PEC)-splitting of water. The CIS particles were prepared via a colloidal method using N-methylimidazole (NMI) as the solvent and an annealing treatment. The SiNWs were obtained by chemical etching of silicon (100) substrates assisted by a metal. The CIS/SiNWs/Si composite material was obtained by deposition of an aliquot of a suspension of CIS particles onto the SiNWs/Si substrate, using spin coating followed by a drying step. The XRD pattern demonstrated that CuInS₂ grows in the tetragonal/chalcopyrite phase, while SiNWs/Si presents a cubic structure. The SEM images show semi-spherical particles (～10 nm) distributed on the surface of silicon nanowires (～10 μm). The EIS measurements reveal n-type conductivity for CIS, SiNWs/Si and CIS/SiNWs/Si materials, which could favour the oxidation reaction of water molecules.     

CFD Modeling of Active Volume Creation in a Non‐Newtonian Fluid Agitated by Submerged Recirculating Jets

Computational fluid dynamics (CFD) models were employed to investigate flow conditions inside a model reactor in which yield stress non‐Newtonian liquid is mobilized using submerged recirculating jets. The simulation results agree well with the experimental results of active volume in the reactor obtained using flow visualization by the authors in a previous study. The models developed are capable of predicting a critical jet velocity (v_c) that determines the extent of active volume obtained due to jet mixing. The v_c values are influenced both by the rheological properties of the liquid and the nozzle orientation. The liquid with higher effective viscosity leads to higher v_c for a downward facing injection nozzle. However, an upward facing injection nozzle along with a downward facing suction nozzle generates enhanced complementary flow fields which overcome the rheological constraints of the liquid and lead to lower v_c.     

High‐performance thermosets with tailored properties derived from methacrylated eugenol and epoxy‐based vinyl ester

A renewable chemical, eugenol, is methacrylated to produce methacrylated eugenol (ME) employing the Steglich esterification reaction without any solvent. The resulting ME is used as a low‐viscosity co‐monomer to replace styrene in a commercial epoxy‐based vinyl ester resin (VE). The volatility and viscosity of ME and styrene are compared. The effect of ME loading and temperature on the viscosity of the VE–ME resin is investigated. Moreover, the thermomechanical properties, curing extent and thermal stability of the fully cured VE–ME thermosets are systematically examined. The results indicate that ME is a monomer with low volatility and low viscosity, and therefore the incorporation of ME monomer in VE resins allows significant reduction of viscosity. Moreover, the viscosity of the VE–ME resin can be tailored by adjusting the ME loadings and processing temperature to meet commercial liquid molding technology requirements. The glass transition temperatures of VE–ME thermosets range from 139 to 199 °C. In addition, more than 95% of the monomer is incorporated and fixed in the crosslinked network structure of VE–ME thermosets. Overall, the developed ME monomer exhibits promising potential for replacing styrene as an effective low‐viscosity co‐monomer. The VE–ME resins show great advantages for use in polymer matrices for high‐performance fiber‐reinforced composites. This work is of great significance to the vinyl ester industry by providing detailed experimental support. © 2018 Society of Chemical Industry     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Design and Fabrication of Concentration‐Gradient Generators with Two and Three Inlets in Microfluidic Chips

A simple and low‐cost method for designing and fabricating concentration‐gradient generators with two and three inlets is proposed which can generate different concentration gradients at varying flow velocities. The microchannel structure was designed in S‐shape and left‐right symmetry. The concentration‐gradient generator was simulated based on the finite element method. The microchannels were processed on a computer numerical control (CNC) engraving and milling machine on poly(methylmethacrylate) substrate, and then two concentration‐gradient generators were fabricated by hot bonding technology. The results of experiment and simulation were compared to prove the feasibility of the method. Flow velocity was an important factor for generating different concentration gradients. The concentration‐gradient profiles of the generators with two and three inlets present approximately linear and quadratic curves.     

Al2O3/Yttria‐Stabilized Zirconia Hollow‐Fiber Membrane Incorporated with Iron Oxide for Pb(II) Removal

Removal by absorptive ceramic membranes can simultaneously absorb and separate metal ions from water. Alumina/yttria‐stabilized zirconia (Al₂O₃/YSZ) hollow‐fiber membranes, fabricated using phase inversion and sintering process, were deposited with iron oxide by an in‐situ hydrothermal process. The results showed that α‐Fe₂O₃ was produced and incorporated across the membranes. A reduction in flux was recorded with the deposition of α‐Fe₂O_3. However, it improved the adsorption capacity for heavy metal adsorption. The adsorption‐separation test demonstrated that the optimized membrane is able to completely remove Pb(II) ions after two hours.     

A simple model for deep dynamic stall conditions

The present study is focused on modeling of dynamic stall behavior of a pitching airfoil. The deep stall regime is in particular considered. A model is proposed, which has a low implementation and computational complexity but yet is able to deal with different types of dynamic stall conditions, including those characterized by multiple vortex shedding at the airfoil leading edge. The proposed model is appraised against an extensive data set of experimental (α,C_L) curves for NACA0012. The results of an existing widely used model, having comparable complexity, are also shown for comparison. The proposed model is able to well reproduce not only the classic curves of deep dynamic stall but also the curves characterized by lift oscillations at high angles of attack due to the shedding of multiple vortices. Furthermore, the model appears to be robust to variations of its parameters from the optimal values and of the airfoil geometry. Finally, the model is successfully implemented in a commercial CFD software and applied to the simulation of a vertical axis wind turbine within the actuator cylinder approach. The accuracy of the prediction of the turbine power coefficient in the whole rotation cycle is very good for the optimal working condition of the turbine, for which the model parameters were calibrated. Fairly good accuracy is also obtained in significantly different working conditions without any further calibration.