Stochastic Event-Driven Molecular Dynamics

Authors:
Aleksandar Donev;Alejandro L. Garcia;Berni J. Alder
Affiliations:
Lawrence Livermore National Laboratory, P.O. Box 808, Livermore, CA 94551-9900, United States;Department of Physics, San Jose State University, San Jose, CA 95192, United States;Lawrence Livermore National Laboratory, P.O. Box 808, Livermore, CA 94551-9900, United States
Venue:
Journal of Computational Physics
Year:
2008

Citing 7
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Abstract

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.