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Institution

Donghua University

EducationShanghai, China
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.
Topics: Fiber, Nanofiber, Electrospinning, Membrane, Graphene


Papers
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Journal ArticleDOI
TL;DR: Recent progress regarding the intrinsic structure-property relationship of CNT fibers, as well as the strategies of enhancing their mechanical and conductive properties are briefly summarized, providing helpful guidance for scouting ideally structured CNT fiber for specific flexible electronic applications.
Abstract: The development of fiber-based smart electronics has provoked increasing demand for high-performance and multifunctional fiber materials. Carbon nanotube (CNT) fibers, the 1D macroassembly of CNTs, have extensively been utilized to construct wearable electronics due to their unique integration of high porosity/surface area, desirable mechanical/physical properties, and extraordinary structural flexibility, as well as their novel corrosion/oxidation resistivity. To take full advantage of CNT fibers, it is essential to understand their mechanical and conductive properties. Herein, the recent progress regarding the intrinsic structure-property relationship of CNT fibers, as well as the strategies of enhancing their mechanical and conductive properties are briefly summarized, providing helpful guidance for scouting ideally structured CNT fibers for specific flexible electronic applications.

160 citations

Journal ArticleDOI
TL;DR: A Lyapunov function candidate whose entries are polynomials is calculated in order to facilitate the use of Itô's differential rule and its first- and second-order derivatives are calculated in terms of parameter-dependent linear matrix inequalities (PDLMIs).
Abstract: In this paper, the distributed H∞ filtering problem is addressed for a class of polynomial nonlinear stochastic systems in sensor networks. For a Lyapunov function candidate whose entries are polynomials, we calculate its first- and second-order derivatives in order to facilitate the use of Ito's differential rule. Then, a sufficient condition for the existence of a feasible solution to the addressed distributed H∞ filtering problem is derived in terms of parameter-dependent linear matrix inequalities (PDLMIs). For computational convenience, these PDLMIs are further converted into a set of sums of squares that can be solved effectively by using the semidefinite programming technique. Finally, a numerical simulation example is provided to demonstrate the effectiveness and applicability of the proposed design approach.

160 citations

Journal ArticleDOI
TL;DR: In this article, the electrospun one-dimensional TiO2/graphene oxide (GO) composite nanofibers photocatalysts using polyvinylpyrrolidone (PVP) as a fiberizing carrier were reported.
Abstract: The present study reports the electrospun one-dimensional TiO2/graphene oxide (GO) composite nanofibers photocatalysts using polyvinylpyrrolidone (PVP) as a fiberizing carrier. Continuous TiO2 nanofibers segregated by the well-dispersed GO with the content even high as 5 wt% were obtained after the carrier PVP was burnt away at 500 °C. The observed lower excitonic intensity from photoluminescent study in the TiO2/GO samples than that in bare TiO2 nanofibers indicated that the recombination of photoinduced electrons and holes in TiO2 could be effectively inhibited in the composite nanofibers. Photocatalytic studies suggested that the TiO2/GO composite nanofibers showed higher mobility of charge carriers and enhanced photocatalytic activity than bare TiO2 nanofibers under visible light irradiation. In addition, photocatalytic performance of the TiO2/GO composites nanofibers was enhanced with increasing the GO concentration in the composite nanofibers. The results presented herein provide new insights into TiO2/GO composites materials as high performance photocatalysts with potential uses in environmental remediation.

160 citations

Journal ArticleDOI
TL;DR: The current paper investigated the removal of the azo dye Orange II from water using advanced oxidation processes based on sulfate radicals and found that Co(3)O(4) was distributed on GO and the leach of cobalt ions was low.

159 citations

Journal ArticleDOI
TL;DR: A set of general nonlinear equations described by sector-bounded nonlinearities is utilized to model the system and sensors in networks and a sufficient condition is derived to guarantee the H∞ performance as well as the exponential mean-square stability of the resulting filtering error dynamics.
Abstract: In this paper, the problem of distributed H∞ filtering in sensor networks using a stochastic sampled-data approach is investigated. A set of general nonlinear equations described by sector-bounded nonlinearities is utilized to model the system and sensors in networks. Each sensor receives the information from both the system and its neighbors. The signal received by each sensor is sampled by a sampler separately with stochastic sampling periods before it is employed by the corresponding filter. By converting the sampling periods into bounded time-delays, the design problem of the stochastic sampled-data based distributed H∞ filters amounts to solving the H∞ filtering problem for a class of stochastic nonlinear systems with multiple bounded time-delays. Then, by constructing a new Lyapunov functional and employing both the Gronwall's inequality and the Jenson integral inequality, a sufficient condition is derived to guarantee the H∞ performance as well as the exponential mean-square stability of the resulting filtering error dynamics. Subsequently, the desired sampled-data based distributed H∞ filters are designed in terms of the solution to certain matrix inequalities that can be solved effectively by using available software. Finally, a numerical simulation example is exploited to demonstrate the effectiveness of the proposed sampled-data distributed H∞ filtering scheme.

159 citations


Authors

Showing all 21321 results

NameH-indexPapersCitations
Dongyuan Zhao160872106451
Xiang Zhang1541733117576
Seeram Ramakrishna147155299284
Kuo-Chen Chou14348757711
Shuai Liu129109580823
Chao Zhang127311984711
Tao Zhang123277283866
Zidong Wang12291450717
Xinchen Wang12034965072
Zhenyu Zhang118116764887
Benjamin S. Hsiao10860241071
Qian Wang108214865557
Jian Zhang107306469715
Yan Zhang107241057758
Richard B. Kaner10655766862
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202371
2022421
20212,465
20202,190
20192,003
20181,605