Institution
Tongji University
Education•Shanghai, China•
About: Tongji University is a education organization based out in Shanghai, China. It is known for research contribution in the topics: Population & Adsorption. The organization has 76116 authors who have published 81176 publications receiving 1248911 citations. The organization is also known as: Tongji & Tóngjì Dàxué.
Topics: Population, Adsorption, Cancer, Finite element method, Lung cancer
Papers published on a yearly basis
Papers
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TL;DR: A survey of emerging SSEs is presented, a perspective on the current challenges and opportunities is provided, and suggestions for future research directions for S SEs and ASSLBs are suggested.
Abstract: All-solid-state lithium batteries (ASSLBs) have the potential to revolutionize battery systems for electric vehicles due to their benefits in safety, energy density, packaging, and operable temperature range. As the key component in ASSLBs, inorganic lithium-ion-based solid-state electrolytes (SSEs) have attracted great interest, and advances in SSEs are vital to deliver the promise of ASSLBs. Herein, a survey of emerging SSEs is presented, and ion-transport mechanisms are briefly discussed. Techniques for increasing the ionic conductivity of SSEs, including substitution and mechanical strain treatment, are highlighted. Recent advances in various classes of SSEs enabled by different preparation methods are described. Then, the issues of chemical stabilities, electrochemical compatibility, and the interfaces between electrodes and SSEs are focused on. A variety of research addressing these issues is outlined accordingly. Given their importance for next-generation battery systems and transportation style, a perspective on the current challenges and opportunities is provided, and suggestions for future research directions for SSEs and ASSLBs are suggested.
809 citations
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TL;DR: The major design principles and criteria for engineering the surface functionality of C-dots for biological applications include brightness, long-term stability, and good biocompatibility are discussed.
Abstract: Nanoparticles are promising scaffolds for applications such as imaging, chemical sensors and biosensors, diagnostics, drug delivery, catalysis, energy, photonics, medicine, and more. Surface functionalization of nanoparticles introduces an additional dimension in controlling nanoparticle interfacial properties and provides an effective bridge to connect nanoparticles to biological systems. With fascinating photoluminescence properties, carbon dots (C-dots), carbon-containing nanoparticles that are attracting considerable attention as a new type of quantum dot, are becoming both an important class of imaging probes and a versatile platform for engineering multifunctional nanosensors. In order to transfer C-dots from proof-of-concept studies toward real world applications such as in vivo bioimaging and biosensing, careful design and engineering of C-dot probes is becoming increasingly important.A comprehensive knowledge of how C-dot surfaces with various properties behave is essential for engineering C-dots...
800 citations
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TL;DR: In this article, a facile two-step solution method to rational design of a novel electrode of hollow NiCo2O4 nanowall arrays on flexible carbon cloth substrate is reported.
Abstract: Metal-organic frameworks (MOFs) are promising porous precursors for the construction of various functional materials for high-performance electrochemical energy storage and conversion. Herein, a facile two-step solution method to rational design of a novel electrode of hollow NiCo2O4 nanowall arrays on flexible carbon cloth substrate is reported. Uniform 2D cobalt-based wall-like MOFs are first synthesized via a solution reaction, and then the 2D solid nanowall arrays are converted into hollow and porous NiCo2O4 nanostructures through an ion-exchange and etching process with an additional annealing treatment. The as-obtained NiCo2O4 nanostructure arrays can provide rich reaction sites and short ion diffusion path. When evaluated as a flexible electrode material for supercapacitor, the as-fabricated NiCo2O4 nanowall electrode shows remarkable electrochemical performance with excellent rate capability and long cycle life. In addition, the hollow NiCo2O4 nanowall electrode exhibits promising electrocatalytic activity for oxygen evolution reaction. This work provides an example of rational design of hollow nanostructured metal oxide arrays with high electrochemical performance and mechanical flexibility, holding great potential for future flexible multifunctional electronic devices.
792 citations
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TL;DR: The proposed opinion-unaware BIQA method does not need any distorted sample images nor subjective quality scores for training, yet extensive experiments demonstrate its superior quality-prediction performance to the state-of-the-art opinion-aware BIZA methods.
Abstract: Existing blind image quality assessment (BIQA) methods are mostly opinion-aware. They learn regression models from training images with associated human subjective scores to predict the perceptual quality of test images. Such opinion-aware methods, however, require a large amount of training samples with associated human subjective scores and of a variety of distortion types. The BIQA models learned by opinion-aware methods often have weak generalization capability, hereby limiting their usability in practice. By comparison, opinion-unaware methods do not need human subjective scores for training, and thus have greater potential for good generalization capability. Unfortunately, thus far no opinion-unaware BIQA method has shown consistently better quality prediction accuracy than the opinion-aware methods. Here, we aim to develop an opinion-unaware BIQA method that can compete with, and perhaps outperform, the existing opinion-aware methods. By integrating the features of natural image statistics derived from multiple cues, we learn a multivariate Gaussian model of image patches from a collection of pristine natural images. Using the learned multivariate Gaussian model, a Bhattacharyya-like distance is used to measure the quality of each image patch, and then an overall quality score is obtained by average pooling. The proposed BIQA method does not need any distorted sample images nor subjective quality scores for training, yet extensive experiments demonstrate its superior quality-prediction performance to the state-of-the-art opinion-aware BIQA methods. The MATLAB source code of our algorithm is publicly available at www.comp.polyu.edu.hk / $\sim $ cslzhang/IQA/ILNIQE/ILNIQE.htm.
783 citations
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University of Oxford1, Virginia Commonwealth University2, Capital Medical University3, Nanjing Medical University4, Hebei Medical University5, Harbin Medical University6, Shantou University7, Sichuan University8, Sun Yat-sen University9, Chongqing University10, Jinan University11, Xi'an Jiaotong University12, Shanxi Medical University13, Zhengzhou University14, Lanzhou University15, Central South University16, Jiangsu University17, Wuhan University18, Zhejiang Chinese Medical University19, China Medical University (PRC)20, Kanazawa Medical University21, Tianjin First Center Hospital22, Tongji University23, Fourth Military Medical University24, Max Planck Society25, Shanghai Jiao Tong University26, Fudan University27, Peking Union Medical College28, King Abdulaziz University29, Macau University of Science and Technology30, University of Copenhagen31, East China Normal University32
TL;DR: Using low-coverage whole-genome sequencing of 5,303 Chinese women with recurrent MDD selected to reduce phenotypic heterogeneity, and 5,337 controls screened to exclude MDD, two loci contributing to risk of MDD on chromosome 10 are identified: one near the SIRT1 gene and the other in an intron of the LHPP gene.
Abstract: Genomic analysis of 5,303 Chinese women with recurrent major depressive disorder (MDD) enables the identification and replication of two genome-wide significant loci contributing to risk of MDD on chromosome 10: one near the SIRT1 gene; the other in an intron of the LHPP gene.
745 citations
Authors
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Name | H-index | Papers | Citations |
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Gang Chen | 167 | 3372 | 149819 |
Yang Yang | 164 | 2704 | 144071 |
Georgios B. Giannakis | 137 | 1321 | 73517 |
Jian Li | 133 | 2863 | 87131 |
Jianlin Shi | 127 | 859 | 54862 |
Zhenyu Zhang | 118 | 1167 | 64887 |
Ju Li | 109 | 623 | 46004 |
Peng Wang | 108 | 1672 | 54529 |
Qian Wang | 108 | 2148 | 65557 |
Yan Zhang | 107 | 2410 | 57758 |
Richard B. Kaner | 106 | 557 | 66862 |
Han-Qing Yu | 105 | 718 | 39735 |
Wei Zhang | 104 | 2911 | 64923 |
Fabio Marchesoni | 104 | 607 | 74687 |
Feng Li | 104 | 995 | 60692 |