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Zhong Chen

Bio: Zhong Chen is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 80, co-authored 1000 publications receiving 28171 citations. Previous affiliations of Zhong Chen include Institute of High Performance Computing Singapore & National Institute of Education.
Topics: Medicine, Chemistry, Catalysis, Coating, Adsorption


Papers
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Journal ArticleDOI
TL;DR: This work proposes a new approach to reconstruct magnetic resonance images by learning the prior knowledge from these multi-contrast images with graph-based wavelet representations and forms the reconstruction as a bi-level optimization problem to allow misalignment between these images.

16 citations

Journal ArticleDOI
TL;DR: In this paper, the effect of palladium on the mechanical properties and corrosion resistance of copper and aluminum intermetallic compounds (IMCs) has been studied in detail, and the results showed that the addition of a few percent Pd only slightly increases the hardness and Young's modulus of the IMCs.

16 citations

Journal ArticleDOI
TL;DR: A systematic underfill selection approach has been presented to characterize and identify suitable underfill encapsulants for large size flip chip ball grid array (FCBGA) packages, which selected material suitable for 35 × 35 mm2 packages with 15 mm die size.

16 citations

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TL;DR: The results of the mechanical and microstructural characterizations demonstrate that Bi-based two phase glass frit bonding is an effective ceramic bonding method for harsh-environment electronic packaging.

16 citations

Journal ArticleDOI
TL;DR: In this article, the relationship between bouncing dynamics of impact droplets and static liquid adhesion driven by micro-nanostructure features was discussed, and three types of nanostructure (nanotube, nanomesh, and nanowire) superhydrophobic surfaces based on the TiO2 nanomaterials were fabricated.
Abstract: Biomimetic surfaces with various extents of liquid adhesion intensely appeal to many researchers due to their academic significance and potential industry applications. The present work aims to discuss the relationship between bouncing dynamics of impact droplets and static liquid adhesion driven by micro/-nanostructure features. Here, we fabricated three types of nanostructure (nanotube, nanomesh, and nanowire) superhydrophobic surfaces based on the TiO2 nanomaterials, and all of these resultant surfaces were endowed with the robust superhydrophobicity, and showed the low liquid adhesion with the sliding angles from 7.5° to 3°. Subsequently, the bouncing dynamics of impact droplets on these surfaces were evaluated and showed remarkable distinctions with different capacity to rebound off. This is explained in that the impact droplet has induced a higher capillary-induced adhesion force interaction as compared to the static droplet on the nanotube structure surface due to the existence of dynamic pressure ...

16 citations


Cited by
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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

29,323 citations

Journal ArticleDOI
06 Jun 1986-JAMA
TL;DR: The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or her own research.
Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

7,563 citations

Journal ArticleDOI
TL;DR: It is anticipated that this review can stimulate a new research doorway to facilitate the next generation of g-C3N4-based photocatalysts with ameliorated performances by harnessing the outstanding structural, electronic, and optical properties for the development of a sustainable future without environmental detriment.
Abstract: As a fascinating conjugated polymer, graphitic carbon nitride (g-C3N4) has become a new research hotspot and drawn broad interdisciplinary attention as a metal-free and visible-light-responsive photocatalyst in the arena of solar energy conversion and environmental remediation. This is due to its appealing electronic band structure, high physicochemical stability, and “earth-abundant” nature. This critical review summarizes a panorama of the latest progress related to the design and construction of pristine g-C3N4 and g-C3N4-based nanocomposites, including (1) nanoarchitecture design of bare g-C3N4, such as hard and soft templating approaches, supramolecular preorganization assembly, exfoliation, and template-free synthesis routes, (2) functionalization of g-C3N4 at an atomic level (elemental doping) and molecular level (copolymerization), and (3) modification of g-C3N4 with well-matched energy levels of another semiconductor or a metal as a cocatalyst to form heterojunction nanostructures. The constructi...

5,054 citations