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This article presents the analysis and optimization method of equivalent impedances specifically for multichannel wireless power transfer (WPT) systems. By establishing the equivalent impedance model and the calculation scheme about output power and system efficiency for multichannel WPT system, the proposed analysis and optimization method is capable to determine the proper range of the load resistances in each channel thereby achieving an ideal transmission performance for multichannel WPT systems. Besides, the optimal selection of the load resistances is capable of offering the great power transmission passageway without cross interference between different channels. Moreover, the proper value of the load resistances can achieve certain power output while maintaining the system efficiency at a relatively high level. Both the simulation and experimental results are provided to demonstrate the feasibility and the performance of the proposed scheme.

Advanced ceramic sponge materials with temperature-invariant high compressibility are urgently needed as thermal insulators, energy absorbers, catalyst carriers, and high temperature air filters. However, the application of ceramic sponge materials is severely limited due to their complex preparation process. Here, we present a facile method for large-scale fabrication of highly compressible, temperature resistant SiO2-Al2O3 composite ceramic sponges by blow spinning and subsequent calcination. We successfully produce anisotropic lamellar ceramic sponges with numerous stacked microfiber layers and density as low as 10 mg cm−3. The anisotropic lamellar ceramic sponges exhibit high compression fatigue resistance, strain-independent zero Poisson’s ratio, robust fire resistance, temperature-invariant compression resilience from −196 to 1000 °C, and excellent thermal insulation with a thermal conductivity as low as 0.034 W m−1 K−1. In addition, the lamellar structure also endows the ceramic sponges with excellent sound absorption properties, representing a promising alternative to existing thermal insulation and acoustic absorption materials., Temperature-invariant highly compressible ceramic sponges are attractive for thermal insulators and energy absorbers, but development is limited by complex preparation processes. Here the authors report large-scale fabrication of silica-alumina composite ceramic sponges via blow spinning and calcination.

Spiral wave is closely related to the occurrence of malignant ventricular arrhythmia. It is important and necessary to study the spiral wave dynamics to better analyze and control spiral waves. In this paper, the dynamics of FitzHugh-Nagumo(FHN) model is identified by using a novel method based on deterministic learning and interpolation method. The FHN model, which has been studied extensively in physical and mathematical science, is often used to study spiral waves. It is a distributed parameter (DPS) described by two coupled partial differential equations (PDEs). To identify the underlying system dynamics of the FHN model globally, we first transform the FHN model into a set of ordinary differential equations (ODEs) by applying the method of lines. Then, we identify the dynamics of the approximation system by employing deterministic learning. That is, the FHN dynamics on a set of spatial grid nodes is accurately identified. To achieve the global identification of the FHN model, the underlying system dynamics of the FHN model on any other spatial point is approximated via an algorithm based on the interpolation method. The effectiveness and feasibility of the proposed method are demonstrated theoretically and numerically.

The problem of finite-time decentralized neural adaptive constrained control is studied for large-scale nonlinear time-delay systems in the non-affine form. The main features of the considered system are that 1) unknown unmatched time-delay interactions are considered, 2) the couplings among the nested subsystems are involved in uncertain nonlinear systems, 3) based on finite-time stability approach, asymmetric saturation actuators and output constraints are studied in large-scale systems. First, the smooth asymmetric saturation nonlinearity and barrier Lyapunov functions are used to achieve the input and output constraints. Second, the appropriately designed Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions, and the neural networks are employed to approximate the unknown nonlinearities. Note that, due to unknown time-delay interactions and the couplings among subsystems, the controller design is more meaningful and challenging. At last, based on finite-time stability theory and Lyapunov stability theory, a decentralized adaptive controller is proposed, which decreases the number of learning parameters. It is shown that the designed controller can ensure that all closed-loop signals are bounded and the tracking error converges to a small neighborhood of the origin. The simulation studies are presented to show the effectiveness of the proposed method.

Ceramic ultra-thin film materials have attracted much attention because of their unique performance compared to the bulk materials and their vital applications in electronic devices and catalysts. An easy, effective and facile method to fabricate high quality ceramic nano membranes will significantly stimulate their practical applications. Herein, we report a new “Blow-bubble” process to produce large area freestanding ultra-thin ceramic material. We successfully used a blow-bubble method to obtain large area freestanding ultra-thin ZnO film after thermal process, and this method can also be used to other materials like TiO2. This synthesizing process relies on sol-gel method and surface tension. In summary, this work demonstrates a facile, economic and effective method to fabricate large area freestanding ultra-thin ZnO film. The photoconductivity of the ZnO film was also tested.

Aiming at the aerodynamic optimization problem of guided ammunition airfoil, genetic algorithm is used to optimize the lift-drag ratio of the airfoil based CST geometric description method with given inflow velocity and fixed angle of attack. Firstly, the parameter space generated by CST parameterized airfoil description method is performed with binary code and the basic operations of genetic algorithm such as selection, crossover and mutation. Then, the external CFD solver is called to automatically divide the grid and calculate the lift-drag ratio through the control script. Finally, the target solution is obtained by searching. The calculation results show that this method can obtain a optimal target solution in relative less generation for a group of airfoils generated randomly in a certain search space.

In this study, the adaptive tracking control is investigated for a class of stochastic pure-feedback non-linear time-delay systems with output constraint and asymmetric input saturation non-linearity. First, the Gaussian error function is employed to represent a continuous differentiable asymmetric saturation model, and the barrier Lyapunov function is designed to cope with the output constraints. Then, the appropriate Lyapunov–Krasovskii functional and the property of hyperbolic tangent functions are used to address the effects of the unknown time-delay terms, and the neural network is employed to approximate the unknown non-linearities. At last, based on Lyapunov stability theory, a robust adaptive neural controller is proposed, which decreases the number of learning parameters and thus avoids the over-estimation problem. Under the designed neural controller, all the closed-loop signals are guaranteed to be 4-moment (or 2 moment) semi-globally uniformly ultimately bounded and the tracking error converges to a small neighbourhood of the origin for bounded initial conditions. Two simulation examples are presented to further illustrate the effectiveness of the designed method.

An adaptive tracking control is investigated for a class of nonstrict-feedback nonlinear systems with time delays subject to input saturation nonlinearity and output constraint. First, the Gaussian error function is used to express the continuous differentiable asymmetric saturation model, and a barrier Lyapunov function is designed to ensure that the output parameters are restricted. Then, an appropriate Lyapunov–Krasovskii functional is chosen to deal with the unknown time-delay terms, and the neural network is used to model the unknown nonlinearities. Finally, based on Lyapunov stability theory, an adaptive neural controller is designed to establish the closed-loop system stability. The example is provided to further illustrate the effectiveness and applicability of the proposed approach.

This paper deals with the problems concerned with the trajectory tracking control with prescribed performance for marine surface vessels without velocity measurements in uncertain dynamical environments, in the presence of parametric uncertainties, unknown disturbances, and unknown dead-zone. First, only the ship position and heading measurements are available and a high-gain observer is used to estimate the unmeasurable velocities. Second, by utilizing the prescribed performance control, the prescribed tracking control performance can be ensured, while the requirement for the initial error is removed via the preprocessing. At last, based on neural network approximation in combination with backstepping and Lyapunov synthesis, a robust adaptive neural control scheme is developed to handle the uncertainties and input dead-zone characteristics. Under the designed adaptive controller for marine surface vessels, all the signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB), and the prescribed transient and steady tracking control performance is guaranteed. Simulation studies are performed to demonstrate the effectiveness of the proposed method.

Defective TiO2 has attracted increasing attention for use in photocatalytic and electrochemical materials because of its narrowed band-gap and improved visible-light photocatalytic activity. However, a facile and efficient approach for obtaining defect-rich TiO2 still remains a challenge. Herein, we demonstrate such an approach to narrow its bandgap and improve visible-light absorption through implanting abundant defects by aerodynamic levitated laser annealing (ALLA) treatment. Note that the ALLA method not only provides rapid annealing, solidifying and cooling process, but also exhibits high efficiency for homogeneous and defective TiO2 nanoparticles. The laser-annealed TiO2 achieves a high hydrogen evolution rate of 8.54 mmol·h–1·g–1, excellent decomposition properties within 60 min, and outstanding recyclability and stability, all of which are superior to the corresponding properties of commercial P25.

In this paper, the problem of decentralized adaptive neural backstepping control is investigated for high-order stochastic nonlinear systems with unknown interconnected nonlinearity and prescribed performance under arbitrary switchings. For the control of high-order nonlinear interconnected systems, it is assumed that unknown system dynamics and arbitrary switching signals are unknown. First, by utilizing the prescribed performance control (PPC), the prescribed tracking control performance can be ensured, while the requirement for the initial error is removed. Second, at each recursive step, only one adaptive parameter is constructed to overcome the over-parameterization, and RBF neural networks are employed to tackle the difficulties caused by completely unknown system dynamics. At last, based on the common Lyapunov stability method, the decentralized adaptive neural control method is proposed, which decreases the number of learning parameters. It is shown that the designed common controller can ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and the prescribed tracking control performance is guaranteed under arbitrary switchings. The simulation results are presented to further illustrate the effectiveness of the proposed control scheme.

Large-scale growth of low-cost, efficient, and durable non-noble metal-based electrocatalysts for water splitting is crucial for future renewable energy systems. Atomic layer deposition (ALD) provides a promising route for depositing uniform thin coatings of electrocatalysts, which are useful in many technologies, including the splitting of water. In this communication, we report the growth of a NiO/Ni catalyst directly on carbon fiber paper by atomic layer deposition and report subsequent reduction and oxidation annealing treatments. The 10–20 nm NiO/Ni nanoparticle catalysts can reach a current density of 10 mA·cm−2 at an overpotential of 189 mV for hydrogen evolution reactions and 257 mV for oxygen evolution reactions with high stability. We further successfully achieved a water splitting current density of 10 mA·cm−2 at 1.78 V using a typical NiO/Ni coated carbon fiber paper two-electrode setup. The results suggest that nanoparticulate NiO/Ni is an active, stable, and noble-metal-free electrocatalyst, which facilitates a method for future water splitting applications.

Machinable zirconia blocks with gradient colors are fundamental for fabrication of full-contour esthetic dental restorations. The aim of this study was to process and evaluate bi-colored zirconia ceramics as a pilot dental material by using well-established techniques. Two commercially available partially stabilized zirconia granules, one undoped and one doped with 0.202 wt% Fe2O3, resulted in white and yellow colors after sintering, respectively. Bi-colored zirconia was fabricated by two-step dry pressing of both zirconia granules one above the other to form green bodies, followed by cold isostatic pressing (CIP) and, a two-step pressureless sintering finally at 1450 degrees C. The dilatometer results showed that the Fe2O3 doped zirconia sintered slightly rapid, but the difference of shrinkage between two powders was

Two-dimensional (2D) nanoscale oxides have attracted research interest owing to their electronic, magnetic optical and catalytic properties. If they could be manufactured on a large scale, 2D oxides would be attractive for applications ranging from electronics to energy conversion and storage. Herein, we report facile fabrication of oxide nanosheets by rapid thermal annealing of corresponding hydrous-chloride compounds. By heating CrCl3·6H2O, ZrOCl2·8H2O, AlCl3·6H2O and YCl3·6H2O crystals as precursors, we immediately collect large quantities of ultrathin Cr2O3, ZrO2, Al2O3 and Y2O3 nanosheets, respectively. The formation of layered nanosheets relies on exfoliation driven by rapid evaporation of water and/or other gas molecules generated under annealing. Our route allows simple, efficient and inexpensive production of 2D oxides. As a demonstration, we evaluate Cr2O3 nanosheets prepared by our method as anodes in lithium-ion batteries and find superior performance in comparison with their microcrystalline counterparts., Oxide nanosheets are of interest for a range of applications. Here the authors demonstrate a simple route combining gas evolution and exfoliation of hydrated chloride precursors for making large quantities of oxide nanosheets of various compositions.

A series of specimens with different surface morphology, pre-sintering process, and sintering temperature were designed for studying the improvement of bond strength between zirconia framework and veneering porcelain. Shear strength test, Scanning Electron Microscope (SEM), and Energy Dispersive Spectrometer (EDS) were adopted in the investigation. A remarkably enhance of average bond strength from 24.1 MPa to 37.2 MPa was obtained by performing humps on zirconia substrate. Moreover, a pre-sintering process for bonding porcelain was beneficial to the increasing of bond strength. Hence, during all-ceramic dental restoration fabrication, it is promising to perform surface treatment on zirconia and conduct pre-sintering procedure on bonding porcelain for the improvement of bond strength between zirconia framework and veneering porcelain.

Direct coagulation casting is a novel near-net-shape method for forming ceramic green bodies from homogenous high-solids-loaded particle suspensions. It is based on the principle of the in situ coagulation of a powder suspension via a reaction-rate-controlled internal-enzyme(urease)-catalyzed reaction after casting. Low-viscosity ( 62 vol%) of SiC, boron, and carbon powder mixtures with a high surface area (>7-10 m 2 /g) have been prepared at pH 10. Salt ions (up to 1-2 mol/L) are created by the urease-catalyzed decomposition of urea, to destabilize the suspensions. The coagulation kinetics and the strength of the wet green bodies have been investigated. The reaction rate is strongly dependent on the temperature (in the range of 5°-30°C) and the enzyme concentration (for the range of 4-16 units/g SiC) and is independent of the substrate (urea) concentration for urea concentrations of

A water-based route for processing s-Si3N4 from alpha-Si3N4, Al2O3, and Y2O3 powder mixtures was established. The surface charges and isoelectric points of the three different powders were investigated within the pH range from pH 3 to pH 12. Citric acid diammonium salt was found to be an effective deflocculant for shifting the isoelectric points to pH 3.5 for Al2O3 and to pH 6 for Y2O3. Aluminum hydroxide (Al(OH)3) showed strong interaction with the Si3N4 powder, shifting the isoelectric point from pH 7 to pH 5.5. Low-viscosity, high-solids-loading suspensions (60-63 vol%) thus were possible at pH 9.7. The preparation of homogeneous and stable suspensions with a solids content of ≤61 vol% and a viscosity

By the Wurtz reductive coupling reaction of dichloromethylphenethylsilane (D) and trichlorosilane (T), trichloromethylsilane or trichlorophenylsilane, two series of branched copolysilanes, polymethylphenethylsilene-co-methylsilynes and polymethylphenethylsilene-co-phenylsilynes, were designed and synthesized using the two procedures of ‘‘pre-polymerization’’ and ‘‘mixed-polymerization’’. Through the characterization of gel permation chromatography, UV, and 1 H-NMR, the properties of such copolysilanes were determined and discussed. It was discovered that the branching structure of the Si-backbone of copolysilanes could be controlled by the D/T ratios and the synthetic procedures of copolymerization of dichorosilane (R1R2SiCl2) to trichlorosilane (RSiCl3), and the molecular weights of the branched copolysilanes could be dramatically enhanced with the pre-polymerization procedure even if there are bulky substituents along with the Si-skeleton of the polysilanes. 2002 Elsevier Science Ltd. All rights reserved.

The Weibull modulus of toughened ceramics was evaluated. The fracture of the toughened ceramics was assumed to be initiated by surface cracks induced during small-scale contacts such as grinding and polishing and an exponential function was selected to describe the R-curve behavior. Based on a brief theoretical analysis, a numerical simulation procedure was designed to predict the fracture strength for toughened ceramics with different R-curve characteristics. The Weibull modulus of each toughened ceramic was estimated and compared with that of the un-toughened base material. It was concluded that an increase in Weibull modulus can always result from toughening. The increase in Weibull modulus was found to be related directly to the relative crack tolerance, i.e., the ratio of the initial crack size to the critical crack size. This suggests that the improvement in crack stability due to toughening is the main reason for the increased Weibull modulus.

The pseudoelastic behaviour of 12 mol% Ce–TZP + 10 wt% Al2O3 ceramics in the loading–unloading cycles was found for the first time at room temperature, and corresponding reversible tm martensitic transformation mechanism was clearly identified the possibility of reversible ferroelastic domain switching at room temperature was also discussed.