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

The long-standing popularity of thermoelectric materials has contributed to the creation of various thermoelectric devices and stimulated the development of strategies to improve their thermoelectric performance. In this review, we aim to comprehensively summarize the state-of-the-art strategies for the realization of high-performance thermoelectric materials and devices by establishing the links between synthesis, structural characteristics, properties, underlying chemistry and physics, including structural design (point defects, dislocations, interfaces, inclusions, and pores), multidimensional design (quantum dots/wires, nanoparticles, nanowires, nano- or microbelts, few-layered nanosheets, nano- or microplates, thin films, single crystals, and polycrystalline bulks), and advanced device design (thermoelectric modules, miniature generators and coolers, and flexible thermoelectric generators). The outline of each strategy starts with a concise presentation of their fundamentals and carefully selected examples. In the end, we point out the controversies, challenges, and outlooks toward the future development of thermoelectric materials and devices. Overall, this review will serve to help materials scientists, chemists, and physicists, particularly students and young researchers, in selecting suitable strategies for the improvement of thermoelectrics and potentially other relevant energy conversion technologies.

Advanced Thermoelectric Design: From Materials and Structures to Devices

Fibre reinforced composites in aircraft construction

A strain sensor has been fabricated from a polymer nanocomposite with multiwalled carbon nanotube (MWNT) fillers. The piezoresistivity
of this nanocomposite strain sensor has been investigated based on an improved three-dimensional (3D) statistical resistor network
model incorporating the tunneling effect between the neighboring carbon nanotubes (CNTs), and a fiber reorientation model. The
numerical results agree very well with the experimental measurements. As compared with traditional strain gauges, much higher sensitivity
can be obtained in the nanocomposite sensors when the volume fraction of CNT is close to the percolation threshold. For a small
CNT volume fraction, weak nonlinear piezoresistivity is observed both experimentally and from numerical simulation. The tunneling
effect is considered to be the principal mechanism of the sensor under small strains.

Tunneling effect in a polymer/carbon nanotube nanocompositestrain sensor

Modelling damage evolution in composite laminates subjected to low velocity impact

Analysis of multiple matrix cracking in [±θm/90n]s composite laminates. Part 1: In-plane stiffness properties

Simulation of delamination growth in multidirectional laminates under mode I and mixed mode I/II loadings using cohesive elements

Analysis of multiple matrix cracking in [±θm/90n]s composite laminates. Part 2: Development of transverse ply cracks

For carbon nanotube (CNT) networks, with increasing network density, there may be sudden changes in the properties, such as the sudden change in electrical conductivity at the electrical percolation threshold. In this paper, the change in stiffness of the CNT networks is studied and especially the existence of stiffness threshold is revealed. Two critical network densities are found to divide the stiffness behavior into three stages: zero stiffness, bending dominated and stretching dominated stages. The first critical network density is a criterion to judge whether or not the network is capable of carrying load, defined as the stiffness threshold. The second critical network density is a criterion to measure whether or not most of the CNTs in network are utilized effectively to carry load, defined as bending–stretching transitional threshold. Based on the geometric probability analysis, a theoretical methodology is set up to predict the two thresholds and explain their underlying mechanisms. The stiffness threshold is revealed to be determined by the statical determinacy of CNTs in the network, and can be estimated quantitatively by the stabilization fraction of network, a newly proposed parameter in this paper. The other threshold, bending–stretching transitional threshold, which signs the conversion of dominant deformation mode, is verified to be well evaluated by the proposed defect fraction of network. According to the theoretical analysis as well as the numerical simulation, the average intersection number on each CNT is revealed as the only dominant factor for the electrical percolation and the stiffness thresholds, it is approximately 3.7 for electrical percolation threshold, and 5.2 for the stiffness threshold of 2D networks. For 3D networks, they are 1.4 and 4.4. And it also affects the bending–stretching transitional threshold, together with the CNT aspect ratio. The average intersection number divided by the fourth root of CNT aspect ratio is found to be an invariant at the bending–stretching transitional threshold, which is 6.7 and 6.3 for 2D and 3D networks, respectively. Based on this study, a simple piecewise expression is summarized to describe the relative stiffness of CNT networks, in which the relative stiffness of networks depends on the relative network density as well as the CNT aspect ratio. This formula provides a solid theoretical foundation for the design optimization and property prediction of CNT networks.

Jianyu Zhang

Papers

Analysis of multiple matrix cracking in [±θm/90n]s composite laminates. Part 1: In-plane stiffness properties

Simulation of delamination growth in multidirectional laminates under mode I and mixed mode I/II loadings using cohesive elements

Analysis of multiple matrix cracking in [±θm/90n]s composite laminates. Part 2: Development of transverse ply cracks

Stiffness threshold of randomly distributed carbon nanotube networks

Strengthening effects of twin interface in Cu/Ni multilayer thin films – A molecular dynamics study