Institution
Beihang University
Education•Beijing, China•
About: Beihang University is a education organization based out in Beijing, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 67002 authors who have published 73507 publications receiving 975691 citations. The organization is also known as: Beijing University of Aeronautics and Astronautics.
Topics: Control theory, Microstructure, Nonlinear system, Artificial neural network, Feature extraction
Papers published on a yearly basis
Papers
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TL;DR: Promising research points include the development of more appropriate techniques of experiments both in vitro and in vivo to detect and analyze the biocompatibility and cytotoxicity of MNPs and understand the possible influencing mechanism of the two properties.
Abstract: It is generally recognized that nanoparticles possess unique physicochemical properties that are largely different from those of conventional materials, specifically the electromagnetic properties of magnetic nanoparticles (MNPs). These properties have attracted many researchers to launch investigations into their potential biomedical applications, which have been reviewed in this article. First, common types of MNPs were briefly introduced. Then, the biomedical applications of MNPs were reviewed in seven parts: magnetic resonance imaging (MRI), cancer therapy, the delivery of drugs and genes, bone and dental repair, tissue engineering, biosensors, and in other aspects, which indicated that MNPs possess great potentials for many kinds of biomedical applications due to their unique properties. Although lots of achievements have been obtained, there is still a lot of work to do. New synthesis techniques and methods are still needed to develop the MNPs with satisfactory biocompatibility. More effective methods need to be exploited to prepare MNPs-based composites with fine microstructures and high biomedical performances. Other promising research points include the development of more appropriate techniques of experiments both in vitro and in vivo to detect and analyze the biocompatibility and cytotoxicity of MNPs and understand the possible influencing mechanism of the two properties. More comprehensive investigations into the diagnostic and therapeutic applications of composites containing MNPs with "core-shell" structure and deeper understanding and further study into the properties of MNPs to reveal their new biomedical applications, are also described in the conclusion and perspectives part.
234 citations
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TL;DR: In this article, the authors present a case study where machine learning schemes are applied to analyze VANETs measurement data for efficiently and reliably transmitting big data for road safety/infotainment and intelligent transportation systems.
Abstract: VANETs enable information exchange among vehicles, other end devices and public networks, which plays a key role in road safety/infotainment, intelligent transportation systems, and self-driving systems. As vehicular connectivity soars, and new on-road mobile applications and technologies emerge, VANETs are generating an ever-increasing amount of data, requiring fast and reliable transmissions through VANETs. On the other hand, a variety of VANETs related data can be analyzed and utilized to improve the performance of VANETs. In this article, we first review VANETs technologies to efficiently and reliably transmit big data. Then, the methods employing big data for studying VANETs characteristics and improving VANETs performance are discussed. Furthermore, we present a case study where machine learning schemes are applied to analyze VANETs measurement data for efficiently
234 citations
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TL;DR: Results provide the possibility of SnSe use as NIBs anodes, when used as the anode material for Na-ion batteries (NIBs), with a high capacity, superior rate capability, and high energy density in a full cell.
Abstract: SnSe with 3D hierarchical nanostructure composed of interconnected single-crystal SnSe nanosheets is synthesized via a fast and effective strategy. Unexpectedly, when used as the anode material for Na-ion batteries (NIBs), the SnSe exhibits a high capacity (738 mA h g-1 ), superior rate capability (40 A g-1 ), and high energy density in a full cell. These results provide the possibility of SnSe use as NIBs anodes.
233 citations
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TL;DR: A solvent-based intercalation method to achieve p-type, n-type and degenerately doped semiconductors in the same parent material at the atomically thin limit is demonstrated and can open a new avenue connecting the previously disparate worlds of integrated circuits andatomically thin materials.
Abstract: Doped semiconductors are the most important building elements for modern electronic devices
1
. In silicon-based integrated circuits, facile and controllable fabrication and integration of these materials can be realized without introducing a high-resistance interface2,3. Besides, the emergence of two-dimensional (2D) materials enables the realization of atomically thin integrated circuits4–9. However, the 2D nature of these materials precludes the use of traditional ion implantation techniques for carrier doping and further hinders device development
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. Here, we demonstrate a solvent-based intercalation method to achieve p-type, n-type and degenerately doped semiconductors in the same parent material at the atomically thin limit. In contrast to naturally grown n-type S-vacancy SnS2, Cu intercalated bilayer SnS2 obtained by this technique displays a hole field-effect mobility of ~40 cm2 V−1 s−1, and the obtained Co-SnS2 exhibits a metal-like behaviour with sheet resistance comparable to that of few-layer graphene
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. Combining this intercalation technique with lithography, an atomically seamless p–n–metal junction could be further realized with precise size and spatial control, which makes in-plane heterostructures practically applicable for integrated devices and other 2D materials. Therefore, the presented intercalation method can open a new avenue connecting the previously disparate worlds of integrated circuits and atomically thin materials. Intercalation of copper and cobalt atoms into n-type SnS2 enables seamless integration of metal, and n- and p-type semiconductors in one parent 2D material.
233 citations
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TL;DR: In this paper, the authors show that the presence of nanoparticles enhances thermal conduction under macroscopically static conditions mainly due to nanoparticle structuring / networking, while the natural convective heat transfer coefficient decreases systematically with increasing nanoparticle concentration, and the deterioration is partially attributed to the high viscosity of nanofluids.
Abstract: This paper summarises some of our recent work on the heat transfer of nanofluids (dilute liquid suspensions of nanoparticles). It covers heat conduction, convective heat transfer under both natural and forced flow conditions, and boiling heat transfer in the nucleate regime. The results show that, despite considerable data scattering, the presence of nanoparticles enhances thermal conduction under macroscopically static conditions mainly due to nanoparticle structuring / networking. The natural convective heat transfer coefficient is observed to decrease systematically with increasing nanoparticle concentration, and the deterioration is partially attributed to the high viscosity of nanofluids. However, either enhancement or deterioration of convective heat transfer is observed under the forced flow conditions and particle migration is suggested to be an important mechanism. The results also show that the boiling heat transfer is enhanced in the nucleate regime for both alumina and titania nanofluids, and the enhancement is more sensitive to the concentration change for TiO(2) nanofluids. It is concluded that there is still some way to go before we can tailor-make nanofluids for any targeted applications.
233 citations
Authors
Showing all 67500 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
H. S. Chen | 179 | 2401 | 178529 |
Alan J. Heeger | 171 | 913 | 147492 |
Lei Jiang | 170 | 2244 | 135205 |
Wei Li | 158 | 1855 | 124748 |
Shu-Hong Yu | 144 | 799 | 70853 |
Jian Zhou | 128 | 3007 | 91402 |
Chao Zhang | 127 | 3119 | 84711 |
Igor Katkov | 125 | 972 | 71845 |
Tao Zhang | 123 | 2772 | 83866 |
Nicholas A. Kotov | 123 | 574 | 55210 |
Shi Xue Dou | 122 | 2028 | 74031 |
Li Yuan | 121 | 948 | 67074 |
Robert O. Ritchie | 120 | 659 | 54692 |
Haiyan Wang | 119 | 1674 | 86091 |