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.

High-Resolution 1H NMR Spectroscopy of Fish Muscle, Eggs and Small Whole Fish via Hadamard-Encoded Intermolecular Multiple-Quantum Coherence

Abstract: National Natural Science Foundation of China [11074209, 11174239, 21203155]; Fundamental Research Fund for the Central Universities [2010121008]

The Impact of Luminous Properties of Red, Green, and Blue Mini-LEDs on the Color Gamut

Abstract: Color gamut is of the paramount importance in the display. Light–current–voltage ( $L-I-V$ ) characteristics of red, green, and blue flip-chip mini-light-emitting diodes (LEDs) ( $100\,\,\mu \text{m}\,\,\times 200\,\,\mu \text{m}$ ) are investigated at temperatures similar to the operational temperatures. Both the ideality factor and the temperature dependence of external quantum efficiency (EQE) suggest that the nonradiative loss in red mini-LED is higher. We also illustrate the intensive lateral luminous intensity fluctuation for red mini-LED under the over-driving current by capturing the spatial emission mapping. The influence of temperature and driving current on the chromaticity coordinates of mini-LEDs is determined. Furthermore, we propose a drive-current algorithm to maximize the color gamut of the trichromatic mixed light at different temperatures. The results indicate that, for the application of self-emitting mini-LED displays, the maximum color gamut is more sensitive to green emission, whereas enhancing the radiative recombination in red mini-LED could contribute a lot to the improvement on net performance.

Multi-contrast brain magnetic resonance image super-resolution using the local weight similarity

Abstract: Low-resolution images may be acquired in magnetic resonance imaging (MRI) due to limited data acquisition time or other physical constraints, and their resolutions can be improved with super-resolution methods. Since MRI can offer images of an object with different contrasts, e.g., T1-weighted or T2-weighted, the shared information between inter-contrast images can be used to benefit super-resolution. In this study, an MRI image super-resolution approach to enhance in-plane resolution is proposed by exploring the statistical information estimated from another contrast MRI image that shares similar anatomical structures. We assume some edge structures are shown both in T1-weighted and T2-weighted MRI brain images acquired of the same subject, and the proposed approach aims to recover such kind of structures to generate a high-resolution image from its low-resolution counterpart. The statistical information produces a local weight of image that are found to be nearly invariant to the image contrast and thus this weight can be used to transfer the shared information from one contrast to another. We analyze this property with comprehensive mathematics as well as numerical experiments. Experimental results demonstrate that the image quality of low-resolution images can be remarkably improved with the proposed method if this weight is borrowed from a high resolution image with another contrast. Multi-contrast MRI Image Super-resolution with Contrast-invariant Regression Weights

Corrugated graphene layers for sea water desalination using capacitive deionization

Abstract: The effect of the electric field and surface morphology of corrugated graphene (GE) layers on their capacitive deionization process is studied using molecular dynamics simulations. Deionization performances are evaluated in terms of water flow rate and ion adsorption and explained by analysing the water density distribution, radial distribution function and distribution of the ions inside the GE layers. The simulation results reveal that corrugation of GE layers reduces the water flow rate but largely enhances ion adsorption in comparison to the flat GE layers. Such enhancement is mainly due to the adsorption of ions on the GE layers due to the anchoring effect in the regions with wide interlayer distances. Moreover, it reveals that the entrance configuration of the GE layers also has a significant effect on the performance of deionization. Overall, the results from this study will be helpful in designing effective electrode configurations for capacitive deionization.

I and i

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 …

Fast parallel algorithms for short-range molecular dynamics

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.

Principles of Neural Science

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

Graphitic Carbon Nitride (g-C3N4)-Based Photocatalysts for Artificial Photosynthesis and Environmental Remediation: Are We a Step Closer To Achieving Sustainability?

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...