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.

Interface Reactions and Shear Strength of Lead-Free Sn-3.5Ag Solder with Ni-W-P Metallization

Abstract: Conventional electroless Ni-P metallizations have been found to be inadequate for providing long term protection of the underlying metallization due to their P content, which leads to complicated interfacial reactions. The use of lead-free solder accelerates interfacial reaction because its Sn content is higher than that in conventional Pb-Sn solders. It is believed that codeposition of W into the Ni-P can effectively retard Ni-P precipitation and Ni crystallization, and thus enhance the solder joint reliability. In this study, the microstructure and shear joint strength of electrolytic Ni, electroless Ni-P and electroless Ni-W-P metallizations were investigated. All 3 metallizations were subjected to reflow soldering followed by thermal aging, and finally ball shear tests. It was found that electrolytic Ni and electroless Ni-W-P behave similarly in terms of IMC thickening rates and ball shear strength, and both have outperformed Ni-P.

Determining the enantioselectivity of asymmetric hydrogenation through parahydrogen-induced hyperpolarization

Abstract: Asymmetric hydrogenation plays an essential role for both academic research and industry to produce enantiomeric pure chiral molecules. Although nuclear magnetic resonance (NMR) is powerful in determining the yields of hydrogenation, it is still challenging to use NMR for chirality-related analysis. Herein, we applied parahydrogen-induced hyperpolarization (PHIP) NMR to determine the enantioselectivity of asymmetric hydrogenation and the absolute chirality of products. We hyperpolarized two types of unsaturated amino acid precursors, i.e., methyl-α-acetoamido cinnamate and (E)-ethyl 3-acetamidobut-2-enoate. Hydrogenation of prochiral substrates with parahydrogen gave temporary hyperpolarized diastereoisomers, which exhibit different PHIP patterns distinguishable in 1H NMR. After assigning the NMR peaks by density functional theory calculations, we simulated the PHIP patterns of all the possible temporary hyperpolarized diastereoisomers and unambiguously assigned the chirality of the products and the enantioselectivity of asymmetric hydrogenation. Our work demonstrates the application and potential of PHIP in revealing the mechanism of asymmetric hydrogenation.

A Simple and Fast Iterative Soft-thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging.

Abstract: Compressed sensing has shown great potentials in accelerating magnetic resonance imaging. Fast image reconstruction and high image quality are two main issues faced by this new technology. It has been shown that, redundant image representations, e.g. tight frames, can significantly improve the image quality. But how to efficiently solve the reconstruction problem with these redundant representation systems is still challenging. This paper attempts to address the problem of applying fast iterative soft-thresholding algorithm (FISTA) to tight frames based magnetic resonance image reconstruction. By introducing the canonical dual frame, we construct an orthogonal projection operator on the range of the analysis sparsity operator and propose a new algorithm, called the projected FISTA (pFISTA). We theoretically prove that pFISTA converges to the minimum of a function with a balanced tight frame sparsity. One major advantage of pFISTA is that only one extra parameter, the step size, is introduced and the numerical solution is stable to it in terms of image reconstruction errors, thus allowing easily setting in many fast magnetic resonance imaging applications.

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...