Abstract
We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed to be computationally effective at each scale. Density fluctuations in the melt structure above the tube scale are minimized through a Monte Carlo simulated annealing of a lattice polymer model. Subsequently the melt structure below the tube scale is equilibrated via the Rouse dynamics of a force-capped Kremer-Grest model that allows chains to partially interpenetrate. Finally the Kremer-Grest force field is introduced to freeze the topological state and enforce correct monomer packing. We generate 15 melts of 500 chains of 10.000 beads for varying chain stiffness as well as a number of melts with 1.000 chains of 15.000 monomers. To validate the equilibration process we study the time evolution of bulk, collective, and single-chain observables at the monomeric, mesoscopic, and macroscopic length scales. Extension of the present method to longer, branched, or polydisperse chains, and/or larger system sizes is straightforward.
Highlights
Computer simulations of polymer melts and networks allow unprecedented insights into the relation between microscopic molecular structure and macroscopic material properties such as the viscoelastic response to deformation; see, e.g., [1,2,3,4]
Density fluctuations in the melt structure above the tube scale are minimized through a Monte Carlo simulated annealing of a lattice polymer model
The melt structure below the tube scale is equilibrated via the Rouse dynamics of a force-capped Kremer-Grest model that allows chains to partially interpenetrate
Summary
Computer simulations of polymer melts and networks allow unprecedented insights into the relation between microscopic molecular structure and macroscopic material properties such as the viscoelastic response to deformation; see, e.g., [1,2,3,4]. The first multiscale approach was introduced by Subramanian [25,26], who applied it to linear and branched melts His idea was to start by equilibrating a coarse representation of the polymer, and successively rescale the simulation domain by while doubling the number of beads in the polymer model. We transfer the force-capped melt state to the KG force field and thermalize the conformations to produce the correct local bead packing [Fig. 1(d)] Each of these stages are fast because we are using computationally efficient models at each scale. The largest computational effort goes into this stage, which is given by the entanglement time of the force-capped model This is independent of the large scale molecular structure of the polymers, we can equilibrate an arbitrarily branched polymer melt in the same time as it takes to equilibrate a simple linear melt. In Appendix A we present the equilibration process in the form of an easy to follow recipe, and in Appendix B we derive some results for structure factors
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