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Stochastic Event-Driven Molecular Dynamics

机译：随机事件驱动的分子动力学

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A novel Stochastic Event-Driven Molecular Dynamics (SEDMD) algorithm is developed for the simulation of polymer chains suspended in a solvent. SEDMD combines event-driven molecular dynamics (EDMD) with the Direct Simulation Monte Carlo (DSMC) method. The polymers are represented as chains of hard-spheres tethered by square wells and interact with the solvent particles with hard-core potentials. The algorithm uses EDMD for the simulation of the polymer chain and the interactions between the chain beads and the surrounding solvent particles. The interactions between the solvent particles themselves are not treated deterministically as in EDMD, rather, the momentum and energy exchange in the solvent is determined stochastically using DSMC. The coupling between the solvent and the solute is consistently represented at the particle level retaining hydrodynamic interactions and thermodynamic fluctuations. However, unlike full MD simulations of both the solvent and the solute, in SEDMD the spatial structure of the solvent is ignored. The SEDMD algorithm is described in detail and applied to the study of the dynamics of a polymer chain tethered to a hard-wall subjected to uniform shear. SEDMD closely reproduces results obtained using traditional EDMD simulations with two orders of magnitude greater efficiency. Results question the existence of periodic (cycling) motion of the polymer chain. (c) 2007 Elsevier Inc. All rights reserved.
机译：为模拟悬浮在溶剂中的聚合物链，开发了一种新颖的随机事件驱动分子动力学（SEDMD）算法。 SEDMD将事件驱动的分子动力学（EDMD）与直接模拟蒙特卡洛（DSMC）方法结合在一起。聚合物表示为由方形孔束缚的硬球链，并与具有硬核电势的溶剂颗粒相互作用。该算法使用EDMD模拟聚合物链以及链珠与周围溶剂颗粒之间的相互作用。溶剂颗粒本身之间的相互作用不像EDMD中那样确定性地处理，而是使用DSMC随机确定溶剂中的动量和能量交换。溶剂和溶质之间的偶合始终以颗粒水平表示，保持了流体动力学相互作用和热力学波动。但是，与溶剂和溶质的完整MD模拟不同，在SEDMD中，溶剂的空间结构被忽略。详细描述了SEDMD算法，并将其应用于研究拴系在承受均匀剪切力的硬壁上的聚合物链的动力学。 SEDMD紧密复制了使用传统EDMD仿真获得的结果，效率提高了两个数量级。结果质疑聚合物链的周期性（循环）运动的存在。 （c）2007 Elsevier Inc.保留所有权利。

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