Institution
Nanjing University
Education•Nanjing, China•
About: Nanjing University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 85961 authors who have published 105504 publications receiving 2289036 citations. The organization is also known as: NJU & Nanking University.
Topics: Catalysis, Population, Adsorption, Magnetization, Graphene
Papers published on a yearly basis
Papers
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TL;DR: The results showed that spatially controlled and localized gene delivery system in the bilayered integrated scaffolds could induce the mesenchymal stem cells in different layers to differentiate into chondrocytes and osteoblasts in vitro, respectively, and simultaneously support the articular cartilage and subchondral bone regeneration in the rabbit knee ostochondral defect model.
258 citations
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TL;DR: In this paper, a compact review on the syntheses of BN nanomaterials is presented, including typical zero-dimensional (0D) fullerenes and nanoparticles, onedimensional (1D) nanotubes and nanoribbons, 2D and 3D nanoporous BN.
258 citations
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TL;DR: An N-superdoped 3D graphene network structure with an N-doping level up to 15.8 at% for high-performance supercapacitor is designed and synthesized, in which the graphene foam with high conductivity acts as skeleton and nested with N- superdoped reduced graphene oxide arogels.
Abstract: An N-superdoped 3D graphene network structure with an N-doping level up to 15.8 at% for high-performance supercapacitor is designed and synthesized, in which the graphene foam with high conductivity acts as skeleton and nested with N-superdoped reduced graphene oxide arogels. This material shows a highly conductive interconnected 3D porous structure (3.33 S cm−1), large surface area (583 m2 g−1), low internal resistance (0.4 Ω), good wettability, and a great number of active sites. Because of the multiple synergistic effects of these features, the supercapacitors based on this material show a remarkably excellent electrochemical behavior with a high specific capacitance (of up to 380, 332, and 245 F g−1 in alkaline, acidic, and neutral electrolytes measured in three-electrode configuration, respectively, 297 F g−1 in alkaline electrolytes measured in two-electrode configuration), good rate capability, excellent cycling stability (93.5% retention after 4600 cycles), and low internal resistance (0.4 Ω), resulting in high power density with proper high energy density.
258 citations
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TL;DR: In this article, four interesting cadmium-II or zinc-II metal coordination polymers, namely [Cd2(2,3-pydc)2(bix)3·2H2O]n (1), [Cc2(μ2-OH2)(2,6-pyridine-2, 3-dicarboxylic acid)2 (bix)]n (2), [cc3(SIP)2,SIP]4·8H 2O],n (3), and
Abstract: Four novel interesting cadmium(II) or zinc(II) metal coordination polymers, [Cd2(2,3-pydc)2(bix)3·2H2O]n (1), [Cd2(μ2-OH2)(2,6-pydc)2(bix)]n (2), [Cd3(SIP)2(bix)4·8H2O]n (3), and [Zn2(SIP)(bix)3(OH)·2H2O]n (4) (bix = 1,4-bis(imidazol-1-ylmethyl)-benzene; 2,3-pydc = pyridine-2,3-dicarboxylic acid; 2,6-pydc = pyridine-2,6-dicarboxylic acid; SIP = 5-sulfoisophthalic acid monosodium salt), have been synthesized under hydrothermal conditions and structurally characterized. Polymer 1 features a 3D porous framework with uncoordinated water molecules trapped in the pores. Polymer 2 is a 2D infinite layer framework, and the resulting 2D structure is interconnected by hydrogen-bond interactions to lead to a 3D supramolecular architecture. Polymer 3 also possesses a 3D porous framework; the most prominent cavities are parallel to the a- and b- directions and are filled with free water molecules. Polymer 4 exhibits 4-fold interpenetration related by three different translation vectors. These four compounds exhibit st...
258 citations
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21 Oct 2017TL;DR: This paper propose a joint attribute-preserving embedding model for cross-lingual entity alignment, which jointly embeds the structures of two knowledge bases into a unified vector space and further refines it by leveraging attribute correlations in the knowledge bases.
Abstract: Entity alignment is the task of finding entities in two knowledge bases (KBs) that represent the same real-world object. When facing KBs in different natural languages, conventional cross-lingual entity alignment methods rely on machine translation to eliminate the language barriers. These approaches often suffer from the uneven quality of translations between languages. While recent embedding-based techniques encode entities and relationships in KBs and do not need machine translation for cross-lingual entity alignment, a significant number of attributes remain largely unexplored. In this paper, we propose a joint attribute-preserving embedding model for cross-lingual entity alignment. It jointly embeds the structures of two KBs into a unified vector space and further refines it by leveraging attribute correlations in the KBs. Our experimental results on real-world datasets show that this approach significantly outperforms the state-of-the-art embedding approaches for cross-lingual entity alignment and could be complemented with methods based on machine translation.
257 citations
Authors
Showing all 86514 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
H. S. Chen | 179 | 2401 | 178529 |
Zhenan Bao | 169 | 865 | 106571 |
Gang Chen | 167 | 3372 | 149819 |
Peter G. Schultz | 156 | 893 | 89716 |
Xiang Zhang | 154 | 1733 | 117576 |
Rui Zhang | 151 | 2625 | 107917 |
Yi Yang | 143 | 2456 | 92268 |
Markku Kulmala | 142 | 1487 | 85179 |
Jian Yang | 142 | 1818 | 111166 |
Wei Huang | 139 | 2417 | 93522 |
Bin Liu | 138 | 2181 | 87085 |
Jun Lu | 135 | 1526 | 99767 |
Hui Li | 135 | 2982 | 105903 |
Lei Zhang | 135 | 2240 | 99365 |