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Institution

Nankai University

EducationTianjin, China
About: Nankai University is a education organization based out in Tianjin, China. It is known for research contribution in the topics: Catalysis & Enantioselective synthesis. The organization has 42964 authors who have published 51866 publications receiving 1127896 citations. The organization is also known as: Nánkāi Dàxué.


Papers
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Journal ArticleDOI
TL;DR: In this article, a novel covalently porphyrin-functionalized single-walled carbon nanotubes (SWNTs) have been synthesized by the reaction of SWNTs with in situ generated porphrin diazonium compounds.
Abstract: Novel covalently porphyrin-functionalized single-walled carbon nanotubes (SWNTs) have been synthesized by the reaction of SWNTs with in situ generated porphyrin diazonium compounds. The resulting nanohybrid was characterized by spectroscopic (UV-Vis-NIR, FTIR and Raman) and microscopic (TEM and AFM) methods. The Raman and absorption spectroscopy data showed that the electronic properties of the modified tubes were mostly retained, without damaging their one-dimensional electronic properties. The fluorescence from the porphyrin moiety was almost completely quenched by SWNTs, indicating that the unique direct linkage mode facilitated the effective energy and electron transfer between the excited porphyrin moiety and the extended π-system of SWNTs. This novel nanohybrid material also exhibited excellent optical limiting properties.

193 citations

Proceedings ArticleDOI
14 Jun 2020
TL;DR: Zhang et al. as mentioned in this paper proposed a probabilistic RGB-D saliency detection network via conditional variational autoencoders to model human annotation uncertainty and generate multiple saliency maps for each input image by sampling in the latent space.
Abstract: In this paper, we propose the first framework (UCNet) to employ uncertainty for RGB-D saliency detection by learning from the data labeling process. Existing RGB-D saliency detection methods treat the saliency detection task as a point estimation problem, and produce a single saliency map following a deterministic learning pipeline. Inspired by the saliency data labeling process, we propose probabilistic RGB-D saliency detection network via conditional variational autoencoders to model human annotation uncertainty and generate multiple saliency maps for each input image by sampling in the latent space. With the proposed saliency consensus process, we are able to generate an accurate saliency map based on these multiple predictions. Quantitative and qualitative evaluations on six challenging benchmark datasets against 18 competing algorithms demonstrate the effectiveness of our approach in learning the distribution of saliency maps, leading to a new state-of-the-art in RGB-D saliency detection.

193 citations

Journal ArticleDOI
TL;DR: In this article, a facile and in situ process is proposed to homogeneously anchor hydrous ruthenium oxide (RuO2) nanoparticles on Ti3C2Tx MXene nanosheets.
Abstract: DOI: 10.1002/aenm.201803987 sources[4] due in part to their lengthy life span, high rate capability, and high power density.[5,6] In general, effective strategies to define the interdigitated configuration of MSCs typically fall within two categories. The first category is based on conventional microfabrication technology, utilizing traditional silicon-based techniques such as photolithography and laser scribing.[7,8] While these conventional microfabrication approaches have been successfully demonstrated for the fabrication of microdevices, the requisite processing conditions are not easily integrated into process flows conducive for flexible and wearable substrates. In light of these issues, significant effort has been put forth into developing the latter category of defining interdigitated configurations by printing the electrode materials in the form of a printable ink or gel.[9] Holistically, when considering the limited footprint of a single device, the available capacitance and energy afforded by the electrode ink are the critical barrier hindering more widespread adoption of this technology.[10] Furthermore, the proper printability and deposition behavior of the printed electrode ink also play a critical role in defining the ultimate printed structure.[11] In the search for applicable candidates for printable MSC electrodes, MXene, a new family of 2D layered transition metal carbides or nitrides, has leapt to the forefront as a promising intercalation pseudocapacitor electrode material for energy storage.[12–14] This material is derived from MAX phases, or layered hexagonal carbides and nitrides, where A is an The fabrication of fully printable, flexible micro-supercapacitors (MSCs) with high energy and power density remains a significant technological hurdle. To overcome this grand challenge, the 2D material MXene has garnered significant attention for its application, among others, as a printable electrode material for high performing electrochemical energy storage devices. Herein, a facile and in situ process is proposed to homogeneously anchor hydrous ruthenium oxide (RuO2) nanoparticles on Ti3C2Tx MXene nanosheets. The resulting RuO2@MXene nanosheets can associate with silver nanowires (AgNWs) to serve as a printable electrode with micrometer-scale resolution for high performing, fully printed MSCs. In this printed nanocomposite electrode, the RuO2 nanoparticles contribute high pseudocapacitance while preventing the MXene nanosheets from restacking, ensuring an effective ion highway for electrolyte ions. The AgNWs coordinate with the RuO2@MXene to guarantee the rheological property of the electrode ink, and provide a highly conductive network architecture for rapid charge transport. As a result, MSCs printed from the nanocomposite inks demonstrate volumetric capacitances of 864.2 F cm−3 at 1 mV s−1, long-term cycling performance (90% retention after 10 000 cycles), good rate capability (304.0 F cm−3 at 2000 mV s−1), outstanding flexibility, remarkable energy (13.5 mWh cm−3) and power density (48.5 W cm−3). Micro-Supercapacitor

193 citations

Journal ArticleDOI
Long Zhang1, Fan Zhang1, Xi Yang1, Kai Leng1, Yi Huang1, Yongsheng Chen1 
22 Apr 2013-Small
TL;DR: Supercapacitors based on activated carbon prepared from various pollens show good specific capacitance and large gravimetric and volumetric energy density in ionic liquid electrolytes, which are much better than those of RP20 (commercial activated carbon) or graphene-based supercapacitor.
Abstract: Supercapacitors based on activated carbon prepared from various pollens show good specific capacitance (207 F g(-1) ) and large gravimetric and volumetric energy density (∼88 Wh kg(-1) and ∼44 Wh L(-1) , respectively) in ionic liquid electrolytes, which are much better than those of RP20 (commercial activated carbon) or graphene-based supercapacitors.

193 citations

Journal ArticleDOI
TL;DR: In this article, the synthesis and catalysis of yolk−shell microspheres containing a single Au nanoparticle core and a mesoporous shell of hollow mesophorous silica micro spheres (HMSM) are reported.
Abstract: Synthesis and catalysis of yolk−shell microspheres containing a single Au nanoparticle core and a mesoporous shell of hollow mesoporous silica microspheres (HMSM) are reported. This synthesis employs polystyrene-co-poly(4-vinylpyridine) microspheres as both template to fabricate the HMSM shell through sol−gel process and scaffold to immobilize the Au nanoparticle. Since the single Au nanoparticle core is supernatant within the inert HMSM shell, the yolk−shell catalyst has minimum support effect and is a promising model to explore the origin of Au catalysis. Catalyzed reduction of 4-nitrophenol with NaBH4 demonstrates size-dependent induction or activation and size-dependent activity of the Au nanoparticle core of the yolk−shell catalyst.

193 citations


Authors

Showing all 43397 results

NameH-indexPapersCitations
Yi Chen2174342293080
Peidong Yang183562144351
Jie Zhang1784857221720
Yang Yang1712644153049
Qiang Zhang1611137100950
Bin Liu138218187085
Jun Chen136185677368
Hui Li1352982105903
Jie Liu131153168891
Han Zhang13097058863
Jian Zhou128300791402
Chao Zhang127311984711
Wei Chen122194689460
Xuan Zhang119153065398
Yang Li117131963111
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023186
2022925
20215,270
20204,645
20194,261
20183,520