Algorithms are designed to implement molecular dynamics (MD) and quantum molecular dynamics (QMD) simulations on emerging concurrent architectures. For systems with finite-range interactions, a domain-decomposition algorithm is used to implement the multiple-time-step (MTS) approach to MD simulations on distributed-memory multiple instruction multiple data (MIMD) machines. Parallel algorithms are also designed for MD simulations of bulk Coulombic systems. The performances of these algorithms are tested on the Intel iPSC/860 system. The computational complexities of these algorithms are O( N) and parallel efficiencies close to 0.9. The core computational kernel of the QMD approach consists of solutions of parabolic partial differential equations (PDE) such as the time-dependent Schrödinger equation or time-dependent Kohn-Sham equation. This problem is coupled with another computationally intensive problem, i.e., solution of elliptic PDEs (the Poisson equation) for the long-range electron-electron interaction. We have designed parallel algorithms for both problems on SIMD (single instruction multiple data) machines. In the past two years, we have used the parallel computer architectures in our Concurrent Computing Laboratory for Materials Simulations (CCLMS) to carry out MD and QMD simulations on network glasses, ceramic composites, nanophase materials, solid C 60 and graphitic tubules, and quantum transport in nanoscale devices. Structural transformation, intermediate-range order and dynamic behavior of SiO 2 glass at high pressures are investigated with molecular dynamics. At high densities, the height of the first sharp diffraction peak is considerably diminished, its position changes from 1.6 to 2.2 Å −1, and a new peak appears at 2.85 Å -1. At twice the normal density, SiO bond length increases, SiO coordination changes from 4 to 6 and OSiO bond-angle changes from 109° to 90°. This is a tetrahedral to octahedral transformation, which was reported recently by Meade, Hem1ey, and Mao. Molecular dynamics simulations of porous silica, in the density range 2.2-0.1 g/cm 3, are carried out on a 41 472 particle system using a MIMD computer. The internal surface area, pore surface-to-volume ratio, pore-size distribution, fractal dimension, correlation length and mean-particle size are determined as a function of the density. Structural transition between a condensed amorphous phase and a low-density porous phase is characterized by these quantities. Various dissimilar porous structures with different fractal dimensions are obtained by controlling the preparation schedule and temperature.
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