Donghua University

About: Donghua University is a education organization based out in Shanghai, China. It is known for research contribution in the topics: Fiber & Nanofiber. The organization has 21155 authors who have published 21841 publications receiving 393091 citations. The organization is also known as: Dōnghuá Dàxué & China Textile University.

Hierarchical heterostructures of MnO2 nanosheets or nanorods grown on Au-coated Co3O4 porous nanowalls for high-performance pseudocapacitance

Abstract: The rational design and fabrication of more multi-component (material-combination) 3D hierarchical heterostructures for high-performance pseudocapacitor applications still remains a challenge. Herein, we have designed and synthesized a 3D hierarchical heterostructure of MnO2 nanosheets or nanorods grown on an Au-coated Co3O4 porous nanowall array, resembling a sandwich configuration of Co3O4@Au@MnO2, by a facial and controllable electrochemical deposition process. Due to their unique self-assembling architecture and characteristics including porous Co3O4 nanowalls, ultrathin MnO2 nanosheets, and a high conductivity Au layer sandwiched between them, each component provides a much-needed critical function for the efficient use of metal oxides for energy storage. The synthesized 3D hierarchical heterostructures exhibited favorable electrochemical performances, such as a high specific capacitances of 851.4 F g−1 at 10 mV s−1 and 1532.4 F g−1 at 1 A g−1, good rate performance and an excellent long-term cycling stability (almost no degradation after 5000 cycles), which are better than those of the reported Co3O4 or MnO2 based electrode materials, and thus could be considered as perspective materials for high-performance electrochemical capacitors.

Self-assembling hybrid NiO/Co3O4 ultrathin and mesoporous nanosheets into flower-like architectures for pseudocapacitance

Abstract: The rational design and synthesis of mesoporous hybrid architecture electrode materials for high-performance pseudocapacitor applications still remains a challenge. Herein, we demonstrate the design and fabrication of hybrid NiO/Co3O4 flower-like mesoporous architectures on a large-scale for high-performance supercapacitors by a facile, environmentally friendly, and low-cost synthetic method. The as-synthesized hybrid NiO/Co3O4 flower-like architectures show a high specific capacitance of 1068 F g−1 at a scan rate of 5 mV s−1 and 1190 F g−1 at a current density of 4 A g−1, a good rate capability even at high current densities and an excellent long-term cycling stability (less than 1% loss of the maximum specific capacitance after 5000 cycles), which can be mainly attributed to their morphological characteristics of mesoporous and ultrathin nanosheets self-assembling into flower-like architectures, as well as a rational composition of the two constituents. The remarkable electrochemical properties, as well as many advantages associated with the synthetic method, should make the present architectures competitive electrode materials for next generation supercapacitors.

Event-Triggered $H_\infty$ State Estimation for Delayed Stochastic Memristive Neural Networks With Missing Measurements: The Discrete Time Case

Abstract: In this paper, the event-triggered $H_\infty $ state estimation problem is investigated for a class of discrete-time stochastic memristive neural networks (DSMNNs) with time-varying delays and missing measurements. The DSMNN is subject to both the additive deterministic disturbances and the multiplicative stochastic noises. The missing measurements are governed by a sequence of random variables obeying the Bernoulli distribution. For the purpose of energy saving, an event-triggered communication scheme is used for DSMNNs to determine whether the measurement output is transmitted to the estimator or not. The problem addressed is to design an event-triggered $H_\infty $ estimator such that the dynamics of the estimation error is exponentially mean-square stable and the prespecified $H_\infty $ disturbance rejection attenuation level is also guaranteed. By utilizing a Lyapunov–Krasovskii functional and stochastic analysis techniques, sufficient conditions are derived to guarantee the existence of the desired estimator, and then, the estimator gains are characterized in terms of the solution to certain matrix inequalities. Finally, a numerical example is used to demonstrate the usefulness of the proposed event-triggered state estimation scheme.

Co9S8 nanoparticles embedded in multiple doped and electrospun hollow carbon nanofibers as bifunctional oxygen electrocatalysts for rechargeable zinc-air battery

Abstract: The development of low-cost electrocatalysts with highly efficient catalytic activity and strong durability toward oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is crucial for rechargeable zinc-air battery. In this work, Co9S8 nanoparticles embedded in N/S dual-doped hollow and porous carbon nanofibers (Co9S8-NSHPCNF) are prepared via the continuous coaxial electrospinning technology followed by pre-oxidation and carbonization treatment. Attributed to synergistic effects between the Co9S8 nanoparticles and NSHPCNF, higher specific surface area, hollow and porous structure, the doping of N and S and better electrical conductivity, the Co9S8-NSHPCNF bifunctional catalysts exhibit preferable performance toward ORR (E1/2 = 0.82 V) and OER (E j = 10 mA cm−2 = 1.58 V) compared to precious metal-based catalysts. In addition, when being used as a cathode catalyst in liquid zinc-air battery, Co9S8-NSHPCNF displays excellent durability. An all solid-state zinc-air battery with Co9S8-NSHPCNF is also fabricated and presents superb charge and discharge cycling performance.