Institution
Donghua University
Education•Shanghai, China•
About: Donghua University is a education organization based out in Shanghai, China. It is known for research contribution in the topics: Fiber & Nanofiber. The organization has 21155 authors who have published 21841 publications receiving 393091 citations. The organization is also known as: Dōnghuá Dàxué & China Textile University.
Topics: Fiber, Nanofiber, Electrospinning, Membrane, Graphene
Papers published on a yearly basis
Papers
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TL;DR: In this article, a multi-functional cellulose-based air filter (CFs@ZIF-8 filter) was proposed by in situ growth of ZIF8 nanocrystals on the surface of cellulose fibers, which increased the specific surface area of filter and strengthened the interactions between filter and PMs.
Abstract: The particulate matters (PMs) and toxic gases in air have resulted in serious impacts on public health The development of “green” air filtering materials for isolating these pollutants is of vital importance Here, we prepared a multi-functional cellulose-based air filter (CFs@ZIF-8 filter) by in situ growth of ZIF-8 nanocrystals on the surface of cellulose fibers The incorporation of ZIF-8 nanocrystals increased the specific surface area of filter, strengthened the interactions between filter and PMs, and provided abundant cavities and gas adsorption sites for filter The filtration efficiency of CFs@ZIF-8 filter for PM03 could reach to an ultrahigh level of 999% The gas (nitrogen) adsorption capacity of CFs@ZIF-8 filter was 200 times higher than that of original cellulose-based filter (CFs-filter) The contributions of ZIF-8 on these surpassing properties of CFs@ZIF-8 filter were deeply analyzed This study provided an effective strategy for developing “green” and multi-functional cellulose-based air filter
102 citations
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TL;DR: In this article, a technique based on acoustic emission (AE) signal wavelet analysis is proposed for tool condition monitoring, where the local characterize of frequency band, which contains the main energy of AE signals, is depicted by the wavelet multi-resolution analysis, and the singularity of the signal is represented by wavelet resolution coefficient norm.
Abstract: It is believed that the acoustic emission (AE) signals contain potentially valuable information for tool wear and breakage monitoring and detection. However, AE stress waves produced in the cutting zone are distorted by the transmission path and the measurement systems and it is difficult to obtain an effective result by these raw acoustic emission data. In this article, a technique based on AE signal wavelet analysis is proposed for tool condition monitoring. The local characterize of frequency band, which contains the main energy of AE signals, is depicted by the wavelet multi-resolution analysis, and the singularity of the signal is represented by wavelet resolution coefficient norm. The feasibility for tool condition monitoring is demonstrated by the various cutting conditions in turning experiments.
102 citations
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TL;DR: Wang et al. as discussed by the authors investigated the average removal efficiencies of COD, color, turbidity and no suspended solids (SS) in a 600m3/day pilot plant with biological treatment systems and membrane technology.
102 citations
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TL;DR: In this paper, the authors examined the cooling performance of five jackets with small ventilation units and closable openings on a sweating thermal manikin in four clothing opening conditions in a warm environment.
102 citations
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TL;DR: In this article, the effect of hydrophilic additive polyvinylpyrrolidone (PVP) on the morphology and crystal structure of hollow fiber membranes by phase inversion process was studied.
102 citations
Authors
Showing all 21321 results
Name | H-index | Papers | Citations |
---|---|---|---|
Dongyuan Zhao | 160 | 872 | 106451 |
Xiang Zhang | 154 | 1733 | 117576 |
Seeram Ramakrishna | 147 | 1552 | 99284 |
Kuo-Chen Chou | 143 | 487 | 57711 |
Shuai Liu | 129 | 1095 | 80823 |
Chao Zhang | 127 | 3119 | 84711 |
Tao Zhang | 123 | 2772 | 83866 |
Zidong Wang | 122 | 914 | 50717 |
Xinchen Wang | 120 | 349 | 65072 |
Zhenyu Zhang | 118 | 1167 | 64887 |
Benjamin S. Hsiao | 108 | 602 | 41071 |
Qian Wang | 108 | 2148 | 65557 |
Jian Zhang | 107 | 3064 | 69715 |
Yan Zhang | 107 | 2410 | 57758 |
Richard B. Kaner | 106 | 557 | 66862 |