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.

Fast parallel algorithms for short-range molecular dynamics

Nanofluids, the fluid suspensions of nanomaterials, have shown many interesting properties, and the distinctive features offer unprecedented potential for many applications. This paper summarizes the recent progress on the study of nanofluids, such as the preparation methods, the evaluation methods for the stability of nanofluids, and the ways to enhance the stability for nanofluids, the stability mechanisms of nanofluids, and presents the broad range of current and future applications in various fields including energy and mechanical and biomedical fields. At last, the paper identifies the opportunities for future research.

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A review on nanofluids: preparation, stability mechanisms, and applications

Recent development in 2D materials beyond graphene

With the arising of global climate change and resource shortage, in recent years, increased attention has been paid to environmentally friendly materials. Trees are sustainable and renewable materials, which give us shelter and oxygen and remove carbon dioxide from the atmosphere. Trees are a primary resource that human society depends upon every day, for example, homes, heating, furniture, and aircraft. Wood from trees gives us paper, cardboard, and medical supplies, thus impacting our homes, school, work, and play. All of the above-mentioned applications have been well developed over the past thousands of years. However, trees and wood have much more to offer us as advanced materials, impacting emerging high-tech fields, such as bioengineering, flexible electronics, and clean energy. Wood naturally has a hierarchical structure, composed of well-oriented microfibers and tracheids for water, ion, and oxygen transportation during metabolism. At higher magnification, the walls of fiber cells have an interes...

https://www.fpl.fs.fed.us/documnts/pdf2016/fpl_2016_zhu001.pdf

Wood-Derived Materials for Green Electronics, Biological Devices, and Energy Applications.

Nanofluids are suspensions of nanoparticles in fluids that show significant enhancement of their properties at modest nanoparticle concentrations. Many of the publications on nanofluids are about u...

https://journals.sagepub.com/doi/pdf/10.1155/2010/519659

Applications of Nanofluids: Current and Future:

In this work, we report a dielectric nanocomposite paper with layered boron nitride (BN) nanosheets wired by one-dimensional (1D) nanofibrillated cellulose (NFC) that has superior thermal and mechanical properties. These nanocomposite papers are fabricated from a filtration of BN and NFC suspensions, in which NFC is used as a stabilizer to stabilize BN nanosheets. In these nanocomposite papers, two-dimensional (2D) nanosheets form a thermally conductive network, while 1D NFC provides mechanical strength. A high thermal conductivity has been achieved along the BN paper surface (up to 145.7 W/m K for 50 wt % of BN), which is an order of magnitude higher than that in randomly distributed BN nanosheet composites and is even comparable to the thermal conductivity of aluminum alloys. Such a high thermal conductivity is mainly attributed to the structural alignment within the BN nanosheet papers; the effects of the interfacial thermal contact resistance are minimized by the fact that the heat transfer is in the ...

Highly Thermally Conductive Papers with Percolative Layered Boron Nitride Nanosheets

Supercooling suppression of microencapsulated phase change materials by optimizing shell composition and structure

Previous research on nanofluids has primarily focused on how to increase thermal conductivity of the fluids. Here, the use of phase change materials as nanoparticles in nanofluids has been proposed to simultaneously enhance the effective thermal conductivity and specific heat of the fluids. As an example, a suspension of indium nanoparticles (melting temperature, 157°C) in polyalphaolefin has been synthesized using a one-step, nanoemulsification method. The fluid’s thermophysical properties, i.e., thermal conductivity, viscosity, and specific heat, and their temperature dependence have been investigated experimentally. The observed melting-freezing phase transition of the indium nanoparticles would considerably augment the fluid’s effective specific heat.

Fangyu Cao

Papers

Highly Thermally Conductive Papers with Percolative Layered Boron Nitride Nanosheets

Supercooling suppression of microencapsulated phase change materials by optimizing shell composition and structure

Synthesis and thermal characterization of phase-changeable indium/polyalphaolefin nanofluids

Preparation of carbon micro-spheres by hydrothermal treatment of methylcellulose sol

Synthesis of carbon–Fe3O4 coaxial nanofibres by pyrolysis of ferrocene in supercritical carbon dioxide