Yujuan Wang

Bio: Yujuan Wang is an academic researcher from Southeast University. The author has contributed to research in topics: Thermal conductivity & Lubrication. The author has an hindex of 7, co-authored 14 publications receiving 280 citations.

Temperature effects on the friction characteristics of graphene

Abstract: An atomic force microscope is used to study the nanoscale frictional characteristics of graphene exfoliated onto weakly adherent silica substrates. Different from the decrease in the friction force with temperature for Si tips sliding on silica substrates, the friction forces for the same tip sliding on a graphene surface have an increasing trend with temperature. Through exploring the morphologies of graphene in both suspended and supported states and at different temperatures, it is found that surface fluctuations are the main reason behind the suppression of the thermal lubrication, which leads to an increase in the friction force with temperature.

Thermal Conductivity Measurement for Carbon-Nanotube Suspensions with 3ω Method

Abstract: The stable and homogeneneous aqueous suspension of carbon nanotubes was prepared in this study. The stability of the nanofluids was improved greatly due to the use of a new dispersant, humic acid. The thermal conductivity of the aqueous suspension was measured with the 3ω method. The experimental results showed that the thermal conductivity of the suspensions increases with the temperature and also is nearly proportional to the loading of the nanoparticles. The thermal conductivity enhancement of single-walled carbon nanotubes (SWNTs) suspensions is better than that of the multi-walled carbon nanotubes (MWNTs) suspensions. Especially for a volume fraction of 0.3846% SWNTs, the thermal conductivity is enhanced by 40.5%. Furthermore, the results at 30°C match well with Jang and Choi’s model.

Molecular dynamics simulations and drug discovery

Abstract: This review discusses the many roles atomistic computer simulations of macromolecular (for example, protein) receptors and their associated small-molecule ligands can play in drug discovery, including the identification of cryptic or allosteric binding sites, the enhancement of traditional virtual-screening methodologies, and the direct prediction of small-molecule binding energies. The limitations of current simulation methodologies, including the high computational costs and approximations of molecular forces required, are also discussed. With constant improvements in both computer power and algorithm design, the future of computer-aided drug design is promising; molecular dynamics simulations are likely to play an increasingly important role.

Accelerating molecular modeling applications with graphics processors

Abstract: Molecular mechanics simulations offer a computational approach to study the behavior of biomolecules at atomic detail, but such simulations are limited in size and timescale by the available computing resources. State- of-the-art graphics processing units (GPUs) can perform over 500 billion arithmetic operations per second, a tremen- dous computational resource that can now be utilized for general purpose computing as a result of recent advances in GPU hardware and software architecture. In this article, an overview of recent advances in programmable GPUs is presented, with an emphasis on their application to molecular mechanics simulations and the programming techni- ques required to obtain optimal performance in these cases. We demonstrate the use of GPUs for the calculation of long-range electrostatics and nonbonded forces for molecular dynamics simulations, where GPU-based calculations are typically 10-100 times faster than heavily optimized CPU-based implementations. The application of GPU accel- eration to biomolecular simulation is also demonstrated through the use of GPU-accelerated Coulomb-based ion placement and calculation of time-averaged potentials from molecular dynamics trajectories. A novel approximation to Coulomb potential calculation, the multilevel summation method, is introduced and compared with direct Cou- lomb summation. In light of the performance obtained for this set of calculations, future applications of graphics processors to molecular dynamics simulations are discussed.

Rational Design of Particle Mesh Ewald Compatible Lennard-Jones Parameters for +2 Metal Cations in Explicit Solvent.

Abstract: Metal ions play significant roles in biological systems. Accurate molecular dynamics (MD) simulations on these systems require a validated set of parameters. Although there are more detailed ways to model metal ions, the nonbonded model, which employs a 12–6 Lennard-Jones (LJ) term plus an electrostatic potential, is still widely used in MD simulations today due to its simple form. However, LJ parameters have limited transferability due to different combining rules, various water models, and diverse simulation methods. Recently, simulations employing a Particle Mesh Ewald (PME) treatment for long-range electrostatics have become more and more popular owing to their speed and accuracy. In the present work, we have systematically designed LJ parameters for 24 +2 metal (M(II)) cations to reproduce different experimental properties appropriate for the Lorentz–Berthelot combining rules and PME simulations. We began by testing the transferability of currently available M(II) ion LJ parameters. The results showe...