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 two-dimensional correlation spectroscopy in inhomogeneous fields: New application of intermolecular zero-quantum coherences

Abstract: A new pulse sequence is proposed based on intermolecular zero-quantum coherences (iZQCs) to obtain high-resolution two-dimensional (2D) correlation spectroscopy (COSY) in inhomogeneous fields via three-dimensional (3D) acquisition. This sequence extends the high-resolution iZQC approaches from one dimension to two dimensions. Since the iZQC evolution periods in the new sequence are insensitive to the field inhomogeneities, high-resolution COSY spectra can be recovered from inhomogeneous fields by projecting the 3D data onto the indirectly acquired 2D plane. Theoretical expressions were derived according to the distant dipolar field treatment combined with product operator formalism. Both the experimental observations and computer simulations are consistent with the theoretical predictions. The new sequence thus provides an attractive way to eliminate the influences of field inhomogeneity on the conventional COSY methods, which may be useful for the study of chemical and biological materials.

Poly Tri-s-triazines as Visible Light Sensitizers in Titania-Based Composite Photocatalysts: Promotion of Melon Development from Urea over Acid Titanates

Abstract: Photocatalysis has become increasingly popular for applications in the energy and environmental fields. However, in its conventional form as a pristine (white) semiconductor oxide, e.g., titania (TiO2), the photocatalyst has a wide band gap and does not respond to a large fraction of the solar power available across the visible region. Recently, some success has been reported in the in situ synthesis and deposition of melon [poly (tri-s-triazine) with an empirical formulation of H3C6N9] onto TiO2 to act as a visible sensitizer. In the present contribution, we report the interesting finding that composites based on hydrogen titanate cores bearing shells of melon and the related graphitic carbon nitride (g-C3N4) as sensitizers are far superior in simulated solar (visible) light-driven photodegradation of methyl orange (MO) dye and ethanol photo-oxidation as compared to the individual components. These layered titanate nanotubes/nanobelts also offer a practical advantage by promoting the build-up of melon fr...

Joint sparse reconstruction of multi-contrast MRI images with graph based redundant wavelet transform

Abstract: Multi-contrast images in magnetic resonance imaging (MRI) provide abundant contrast information reflecting the characteristics of the internal tissues of human bodies, and thus have been widely utilized in clinical diagnosis. However, long acquisition time limits the application of multi-contrast MRI. One efficient way to accelerate data acquisition is to under-sample the k-space data and then reconstruct images with sparsity constraint. However, images are compromised at high acceleration factor if images are reconstructed individually. We aim to improve the images with a jointly sparse reconstruction and Graph-based redundant wavelet transform (GBRWT). First, a sparsifying transform, GBRWT, is trained to reflect the similarity of tissue structures in multi-contrast images. Second, joint multi-contrast image reconstruction is formulated as a l2, 1 norm optimization problem under GBRWT representations. Third, the optimization problem is numerically solved using a derived alternating direction method. Experimental results in synthetic and in vivo MRI data demonstrate that the proposed joint reconstruction method can achieve lower reconstruction errors and better preserve image structures than the compared joint reconstruction methods. Besides, the proposed method outperforms single image reconstruction with joint sparsity constraint of multi-contrast images. The proposed method explores the joint sparsity of multi-contrast MRI images under graph-based redundant wavelet transform and realizes joint sparse reconstruction of multi-contrast images. Experiment demonstrate that the proposed method outperforms the compared joint reconstruction methods as well as individual reconstructions. With this high quality image reconstruction method, it is possible to achieve the high acceleration factors by exploring the complementary information provided by multi-contrast MRI.

3D-printed integrative probeheads for magnetic resonance

Abstract: Magnetic resonance (MR) technology has been widely employed in scientific research, clinical diagnosis and geological survey. However, the fabrication of MR radio frequency probeheads still face difficulties in integration, customization and miniaturization. Here, we utilized 3D printing and liquid metal filling techniques to fabricate integrative radio frequency probeheads for MR experiments. The 3D-printed probehead with micrometer precision generally consists of liquid metal coils, customized sample chambers and radio frequency circuit interfaces. We screened different 3D printing materials and optimized the liquid metals by incorporating metal microparticles. The 3D-printed probeheads are capable of performing both routine and nonconventional MR experiments, including in situ electrochemical analysis, in situ reaction monitoring with continues-flow paramagnetic particles and ions separation, and small-sample MR imaging. Due to the flexibility and accuracy of 3D printing techniques, we can accurately obtain complicated coil geometries at the micrometer scale, shortening the fabrication timescale and extending the application scenarios. Here, the authors combine 3D printing and liquid metal filling techniques to fabricate customised probeheads for magnetic resonance experiments. They demonstrate in situ electrochemical nuclear magnetic resonance analysis, reaction monitoring with continues-flow separation and small-sample imaging.

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...