Institution
Nanjing University of Science and Technology
Education•Nanjing, China•
About: Nanjing University of Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Control theory & Catalysis. The organization has 31581 authors who have published 36390 publications receiving 525474 citations. The organization is also known as: Nánjīng Lǐgōng Dàxué & Nánlǐgōng.
Papers published on a yearly basis
Papers
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TL;DR: A two-phase test sample representation method for face recognition using the representation ability of each training sample to determine M “nearest neighbors” for the test sample and uses the representation result to perform classification.
Abstract: In this paper, we propose a two-phase test sample representation method for face recognition. The first phase of the proposed method seeks to represent the test sample as a linear combination of all the training samples and exploits the representation ability of each training sample to determine M “nearest neighbors” for the test sample. The second phase represents the test sample as a linear combination of the determined M nearest neighbors and uses the representation result to perform classification. We propose this method with the following assumption: the test sample and its some neighbors are probably from the same class. Thus, we use the first phase to detect the training samples that are far from the test sample and assume that these samples have no effects on the ultimate classification decision. This is helpful to accurately classify the test sample. We will also show the probability explanation of the proposed method. A number of face recognition experiments show that our method performs very well.
498 citations
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TL;DR: Unique features of lens-free computational imaging tools are discussed and some of their emerging results for wide-field on-chip microscopy, such as the achievement of a numerical aperture of ∼0.8–0.9 across a field of view (FOV) of more than 20 mm2, which corresponds to an image with more than 1.5 gigapixels.
Abstract: In this perspective, the authors present the basic features of lens-free computational imaging tools and report performance comparisons with conventional microscopy methods. They also discuss the challenges that these computational on-chip microscopes face for their wide-scale biomedical application.
486 citations
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TL;DR: The criteria for judicious selection of MOFs in fabricating MOF-based membranes are given and the remaining challenges and future opportunities in this field are defined.
Abstract: Metal–organic frameworks (MOFs) represent a fascinating class of solid crystalline materials which can be self-assembled in a straightforward manner by the coordination of metal ions or clusters with organic ligands. Owing to their intrinsic porous characteristics, unique chemical versatility and abundant functionalities, MOFs have received substantial attention for diverse industrial applications, including membrane separation. Exciting research activities ranging from fabrication strategies to separation applications of MOF-based membranes have appeared. Inspired by the marvelous achievements of MOF-based membranes in gas separations, liquid separations are also being explored for the purpose of constructing continuous MOFs membranes or MOF-based mixed matrix membranes. Although these are in an emerging stage of vigorous development, most efforts are directed towards improving the liquid separation efficiency with well-designed MOF-based membranes. Therefore, as an increasing trend in membrane separation, the field of MOF-based membranes for liquid separation is highlighted in this review. The criteria for judicious selection of MOFs in fabricating MOF-based membranes are given. Special attention is paid to rational design strategies for MOF-based membranes, along with the latest application progress in the area of liquid separations, such as pervaporation, water treatment, and organic solvent nanofiltration. Moreover, some attractive dual-function applications of MOF-based membranes in the removal of micropollutants, degradation, and antibacterial activity are also reviewed. Finally, we define the remaining challenges and future opportunities in this field. This Tutorial Review provides an overview and outlook for MOF-based membranes for liquid separations. Further development of MOF-based membranes for liquid separation must consider the demands of strict separation standards and environmental safety for industrial application.
483 citations
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TL;DR: In this article, metal-organic framework (MOF)-derived carbon materials (CMs) have drawn great interest in many fields of application, such as energy storage and conversion, environmental remediation, and catalysis.
476 citations
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TL;DR: This successful fabrication of a robust, anti-icing, UV-durable, and anticorrosion superhydrophobic surface could yield a prospective candidate for various practical applications.
Abstract: A superhydrophobic steel surface was prepared through a facile method: combining hydrogen peroxide and an acid (hydrochloric acid or nitric acid) to obtain hierarchical structures on steel, followed by a surface modification treatment. Empirical grid maps based on different volumes of H2O2/acid were presented, revealing a wettability gradient from “hydrophobic” to “rose effect” and finally to “lotus effect”. Surface grafting has been demonstrated to be realized only on the oxidized area. As-prepared superhydrophobic surfaces exhibited excellent anti-icing properties according to the water-dripping test under overcooled conditions and the artificial “steam-freezing” (from 50 °C with 90% humidity to the −20 °C condition) test. In addition, the surfaces could withstand peeling with 3M adhesive tape at least 70 times with an applied pressure of 31.2 kPa, abrasion by 400 grid SiC sandpaper for 110 cm under 16 kPa, or water impacting for 3 h without losing superhydrophobicity, suggesting superior mechanical dur...
476 citations
Authors
Showing all 31818 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jian Yang | 142 | 1818 | 111166 |
Liming Dai | 141 | 781 | 82937 |
Hui Li | 135 | 2982 | 105903 |
Jian Zhou | 128 | 3007 | 91402 |
Shuicheng Yan | 123 | 810 | 66192 |
Zidong Wang | 122 | 914 | 50717 |
Xin Wang | 121 | 1503 | 64930 |
Xuan Zhang | 119 | 1530 | 65398 |
Zhenyu Zhang | 118 | 1167 | 64887 |
Xin Li | 114 | 2778 | 71389 |
Zeshui Xu | 113 | 752 | 48543 |
Xiaoming Li | 113 | 1932 | 72445 |
Chunhai Fan | 112 | 702 | 51735 |
H. Vincent Poor | 109 | 2116 | 67723 |
Qian Wang | 108 | 2148 | 65557 |