Hua Zhang

Bio: Hua Zhang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Graphene. The author has an hindex of 163, co-authored 1503 publications receiving 116769 citations. Previous affiliations of Hua Zhang include Shenzhen University & Zhengzhou University.

Hydrophilic Nitrogen and Sulfur Co‐doped Molybdenum Carbide Nanosheets for Electrochemical Hydrogen Evolution

Abstract: Nitrogen and sulfur dual-doped Mo2 C nanosheets provide low operating potential (-86 mV for driving 10 mA cm(-2) of current density). Co-doping of N and S heteroatoms can improve the wetting property of the Mo2C electrocatalyst in aqueous solution and induce synergistic effects via σ-donation and π-back donation with hydronium cation.

Ag@MoS2 Core-Shell Heterostructure as SERS Platform to Reveal the Hydrogen Evolution Active Sites of Single-Layer MoS2.

Abstract: Understanding the reaction mechanism for the catalytic process is essential to the rational design and synthesis of highly efficient catalysts. MoS2 has been reported to be an efficient catalyst toward the electrochemical hydrogen evolution reaction (HER), but it still lacks direct experimental evidence to reveal the mechanism for MoS2-catalyzed electrochemical HER process at the atomic level. In this work, we develop a wet-chemical synthetic method to prepare the single-layer MoS2-coated polyhedral Ag core-shell heterostructure (Ag@MoS2) with tunable sizes as efficient catalysts for the electrochemical HER. The Ag@MoS2 core-shell heterostructures are used as ideal platforms for the real-time surface-enhanced Raman spectroscopy (SERS) study owing to the strong electromagnetic field generated in the plasmonic Ag core. The in situ SERS results provide solid Raman spectroscopic evidence proving the S-H bonding formation on the MoS2 surface during the HER process, suggesting that the S atom of MoS2 is the catalytic active site for the electrochemical HER. It paves the way on the design and synthesis of heterostructures for exploring their catalytic mechanism at atomic level based on the in situ SERS measurement.

An optical neural chip for implementing complex-valued neural network.

Abstract: Complex-valued neural networks have many advantages over their real-valued counterparts. Conventional digital electronic computing platforms are incapable of executing truly complex-valued representations and operations. In contrast, optical computing platforms that encode information in both phase and magnitude can execute complex arithmetic by optical interference, offering significantly enhanced computational speed and energy efficiency. However, to date, most demonstrations of optical neural networks still only utilize conventional real-valued frameworks that are designed for digital computers, forfeiting many of the advantages of optical computing such as efficient complex-valued operations. In this article, we highlight an optical neural chip (ONC) that implements truly complex-valued neural networks. We benchmark the performance of our complex-valued ONC in four settings: simple Boolean tasks, species classification of an Iris dataset, classifying nonlinear datasets (Circle and Spiral), and handwriting recognition. Strong learning capabilities (i.e., high accuracy, fast convergence and the capability to construct nonlinear decision boundaries) are achieved by our complex-valued ONC compared to its real-valued counterpart.

Two-dimensional transition metal dichalcogenide nanomaterials for biosensing applications

Abstract: Biosensors are powerful tools used to monitor biological and biochemical processes, ranging from clinical diagnosis to disease therapy. The huge demands for bioassays greatly promote the development of new nanomaterials as sensing platforms. Two-dimensional (2D) nanomaterials with superior properties, such as large surface areas and excellent conductivities, are excellent candidates for biosensor applications. Among them, single- or few-layered transition metal dichalcogenide (TMD) nanomaterials represent an emerging class of 2D nanomaterials with unique physical, chemical, and electronic properties. In this mini-review, we summarize the recent progress in 2D TMD nanomaterial-based biosensors for the sensitive detection of various kinds of targets, including nucleic acid, proteins, and small biomolecules, based on different sensors like optical sensors and electrochemical sensors, and bioelectronic sensors. Finally, the challenges and opportunities in this promising field are also proposed.

VO2 nanoflake arrays for supercapacitor and Li-ion battery electrodes: performance enhancement by hydrogen molybdenum bronze as an efficient shell material

Abstract: Hydrogen molybdenum bronze (HMB) is electrochemically deposited as a homogeneous shell on VO2 nanoflakes grown on graphene foam (GF), forming a GF + VO2/HMB integrated electrode structure. Asymmetric supercapacitors based on the GF + VO2/HMB cathode and neutral electrolyte are assembled and show enhanced performance with weaker polarization, higher specific capacitance and better cycling life than the unmodified GF + VO2 electrode. Capacitances of 485 F g−1 (2 A g−1) and 306 F g−1 (32 A g−1) are obtained because of the exceptional 3D porous architecture and conductive network. In addition, the GF + VO2/HMB electrodes are also characterized as the cathode of lithium ion batteries. Very stable capacities at rates up to 30 C are demonstrated for 500 cycles. This new type of shell material is expected to have its generic function in other metal oxide based nanostructures.

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.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Electronics and optoelectronics of two-dimensional transition metal dichalcogenides.

Abstract: Single-layer metal dichalcogenides are two-dimensional semiconductors that present strong potential for electronic and sensing applications complementary to that of graphene.