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Institution

Nanjing University

EducationNanjing, 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.


Papers
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Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
Lili Wen1, Yi-Zhi Li1, Zhenda Lu1, Jian-Guo Lin1, Chun-Ying Duan1, Qingjin Meng1 
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

Book ChapterDOI
21 Oct 2017
TL;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

NameH-indexPapersCitations
Yi Chen2174342293080
H. S. Chen1792401178529
Zhenan Bao169865106571
Gang Chen1673372149819
Peter G. Schultz15689389716
Xiang Zhang1541733117576
Rui Zhang1512625107917
Yi Yang143245692268
Markku Kulmala142148785179
Jian Yang1421818111166
Wei Huang139241793522
Bin Liu138218187085
Jun Lu135152699767
Hui Li1352982105903
Lei Zhang135224099365
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20242
2023276
20221,087
20219,130
20208,684
20198,203