Multiscale equilibration of highly entangled isotropic model polymer melts.

Area of Science:

• Polymer Physics
• Computational Materials Science
• Soft Matter Physics

Background:

• Simulating long-chain polymer melts is computationally intensive.
• Accurate modeling requires capturing behavior across multiple length scales, from Kuhn scale to tube scale.
• Existing methods struggle with efficiency and maintaining structural integrity during simulations.

Purpose of the Study:

• To present a computationally efficient multiscale method for preparing equilibrated, isotropic long-chain model polymer melts.
• To generate well-defined Kremer-Grest melts for studying polymer physics phenomena.
• To bridge the gap between coarse-grained and atomistic simulations.

Main Methods:

• Utilized Monte Carlo simulations on a lattice model for large-scale equilibration.
• Incorporated a constrained mode tube model to introduce bead degrees of freedom down to the Kuhn scale.
• Employed parameterized force-capped bead-spring models for gradual introduction of local bead packing.
• Successfully transitioned to the full Kremer-Grest model without structural perturbation.

Main Results:

• Generated Kremer-Grest melts with 1000 chains, 200 entanglements, and 25,000-2,000 beads/chain.
• Achieved excellent agreement in chain statistics with literature results across all accessible length scales.
• Covered experimentally relevant bending rigidities, including those beyond the isotropic-nematic transition limit.

Conclusions:

• The multiscale method is computationally efficient and accurate for polymer melt simulations.
• This approach enables the generation of high-quality polymer melt models for diverse research applications.
• The method successfully reproduces large-scale chain statistics while incorporating fine-scale details.