Simulating highly entangled polymer melts using Gaussian soft-core potential

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Abstract
The Kremer–Grest (KG) model [Kremer and Grest, J. Chem. Phys. 92(8), 5057–5086 (1990)] laid the groundwork for molecular dynamics (MD) simulations of entangled polymer dynamics and remains the standard approach for investigating both equilibrium and nonequilibrium behavior. However, simulating highly entangled systems with chain lengths exceeding 10 entanglement strands (Ne) in the diffusive regime is still computationally challenging. In this work, we report MD simulations based on a Gaussian soft-core potential to study entangled polymer dynamics over time scales that extend into the diffusive regime, for melts with chain lengths up to N = 2000 ≈ 80Ne. Compared to the classical KG model at the same N, our approach results in a smaller entanglement length Ne and a larger invariant degree of polymerization N̄, while offering significantly improved computational efficiency, enabling it to cover the full time spectrum of entanglement dynamics. The monomer mean-squared displacement, g1(t), exhibits a distinct and robust t1/4 scaling over nearly three decades in time. Notably, for chains with N > 1000, the stress relaxation function G(t) develops a weak, power-law-like quasi-plateau, which is subsequently followed by an exponential decay. For chain lengths up to N = 2000 ≈ 80Ne, both chain diffusion and zero-shear viscosity follow the experimentally observed trends, D ∼ N−2.3 and η ∼ N3.4, respectively, with no clear indication of crossover toward D ∼ N−2.0 or η ∼ N3.0.
Funding Information
  • Hong Kong University of Science and Technology
  • Hong Kong Quantum AI Lab, AIR@InnoHK of the Hong Kong Government

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