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Institution

Shanghai University

EducationShanghai, Shanghai, China
About: Shanghai University is a education organization based out in Shanghai, Shanghai, China. It is known for research contribution in the topics: Microstructure & Graphene. The organization has 59583 authors who have published 56840 publications receiving 753549 citations. The organization is also known as: Shànghǎi Dàxué.


Papers
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Journal ArticleDOI
TL;DR: The results support the viewpoint that the ZnO nanoparticle toxicity comes from the dissolved Zn(2+) in the culture medium or inside cells and highlight the need for caution during the use and disposal of ZNO manufactured nanomaterials.
Abstract: Given the intensive application of nanoscale zinc oxide (ZnO) materials in our life, growing concerns have arisen about its unintentional health and environmental impacts. In this study, the neurotoxicity of different sized ZnO nanoparticles in mouse neural stem cells (NSCs) was investigated. A cell viability assay indicated that ZnO nanoparticles manifested dose-dependent, but no size-dependent toxic effects on NSCs. Apoptotic cells were observed and analyzed by confocal microscopy, transmission electron microscopy examination, and flow cytometry. All the results support the viewpoint that the ZnO nanoparticle toxicity comes from the dissolved Zn(2+) in the culture medium or inside cells. Our results highlight the need for caution during the use and disposal of ZnO manufactured nanomaterials to prevent the unintended environmental and health impacts.

323 citations

Journal ArticleDOI
TL;DR: The results suggest, for the first time, the CPC-exosomes can be used as a therapeutic vehicle for cardioprotection, and highlights a new perspective for using non-cell exosomes for cardiac disease.

323 citations

Journal ArticleDOI
Dengsong Zhang1, Tingting Yan1, Liyi Shi1, Zheng Peng1, Xiaoru Wen1, Jianping Zhang1 
TL;DR: Graphene/carbon nanotube (GR/CNT) composites were prepared by a modified exfoliation approach and used as capacitive deionization (CDI) electrodes.
Abstract: Graphene/carbon nanotube (GR/CNT) composites were prepared by a modified exfoliation approach and used as capacitive deionization (CDI) electrodes. SEM and TEM images demonstrate that the CNTs are successfully inserted into the GR. Nitrogen sorption analysis and electrochemical impedance spectroscopy show that the GR/CNT composites have a larger specific surface area and higher conductivity as compared with GR, which is due to the inserted CNTs inhibiting the aggregation and increasing the conductivity in the vertical direction. Through cyclic voltammetry and galvanostatic charge/discharge evaluation, we can conclude that the prepared composites have higher specific capacitance values and better stability, suggesting that the GR/CNT composite electrodes have a higher electrosorption capacity. Power and energy density analysis shows that the GR/CNT composite electrodes have higher power density and energy density and the energy density decay is relatively slow in a wide range of power as compared with GR, which indicates that the composite electrodes exhibit low energy consumption for capacitive deionization. The desalination capacity was evaluated by a batch mode electrosorptive experiment in a NaCl aqueous solution. As compared with GR and commercial activated carbon, the GR/CNT composite electrodes exhibit excellent desalination behavior, which is attributed to the improved electric conductivity and higher accessible surface area, which are quite beneficial for the electrosorption of ions onto the electrodes. The GR/CNT composites are confirmed to be promising materials for CDI electrodes.

322 citations

Journal ArticleDOI
TL;DR: It is shown that global synchronization of coupled DNNs is ensured by a suitable design of the coupling matrix and the inner linking matrix and by using the Lyapunov functional methods and Hermitian matrix theory.
Abstract: This paper formulates the model and then studies its dynamics of a system of linearly and diffusively coupled identical delayed neural networks (DNNs), which is generalization of delayed Hopfied neural networks (DHNNs) and delayed cellular neural networks (DCNNs). In particularly, a simple yet generic sufficient condition for global synchronization of such coupled DNNs is derived based on the Lyapunov functional methods and Hermitian matrix theory. It is shown that global synchronization of coupled DNNs is ensured by a suitable design of the coupling matrix and the inner linking matrix. Furthermore, the result is applied to some typical chaotic neural networks. Finally, numerical simulations are presented to demonstrate the effectiveness of the approach.

320 citations

Journal ArticleDOI
TL;DR: Graphene-coated hollow mesoporous carbon spheres (GHMCSs) were originally designed and originally used as efficient electrode materials for capacitive deionization in this paper.
Abstract: Graphene-coated hollow mesoporous carbon spheres (GHMCSs) are rationally designed and originally used as efficient electrode materials for capacitive deionization. The GHMCSs are fabricated by a simple template-directed method using phenolic polymer coated polystyrene spheres as templates. The resulting graphene-based composites have a hierarchically porous nanostructure with hollow mesoporous carbon spheres uniformly embedded in the graphene sheets. The hierarchically porous structure of GHMCS electrodes can guarantee fast transport of salt ions, and the improved specific surface area of GHMCSs provides more adsorption sites for the formation of an electrical double layer. In addition, the graphene sheets in the GHMCSs as the interconnected conductive networks lead to fast charge transfer. The unique GHMCS structure exhibits enhanced electrochemical performance with high specific capacitance, low inner resistance and long cycling lifetime. Besides, a remarkable capacitive deionization behavior of GHMCSs with low energy consumption is obtained in a NaCl solution. The proposed carbon composite architectures are expected to lay the foundation for the design and fabrication of high-performance electrodes in the field of energy and electrochemistry.

318 citations


Authors

Showing all 59993 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Yang Yang1712644153049
Yang Liu1292506122380
Zhen Li127171271351
Xin Wang121150364930
Jian Liu117209073156
Xin Li114277871389
Wei Zhang112118993641
Jianjun Liu112104071032
Liquan Chen11168944229
Jin-Quan Yu11143843324
Jonathan L. Sessler11199748758
Peng Wang108167254529
Qian Wang108214865557
Wei Zhang104291164923
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023182
2022741
20216,318
20205,569
20195,063
20184,235