Polyurea is an alternating copolymer with excellent viscoelastic properties for dissipating shock and impact loads; however, a molecular-level understanding of how its chemistry relates to its performance remains elusive. While molecular dynamics simulations can in theory draw connections between molecular structure and viscoelastic properties, in practice the long relaxation times associated with polymer dynamics make such calculations prohibitively expensive. To address this issue, we have developed a coarse-grained (CG) model of polyurea in which each of the phenylmethaneaminobenzoate and tetramethylene-oxide units making up the polyurea chains are treated using individual CG beads. The parameters for the intra-and intermolecular force field of the CG model have been obtained in a rigorous manner by using the iterative Boltzmann inversion approach. We have validated the CG model against densities, heat capacities, and chain conformations obtained from fully atomistic MD simulations for oligomeric polyurea chains. A time-dependent dynamic rescaling method is proposed that allows for quantitative predictions of stress relaxation beyond microsecond time scales. The CG model introduced here opens up avenues to study the molecular structure−function relationship of polyurea and polyureabased materials.

To explore the relationship between microscopic structure and viscoelastic properties of polyurea, a coarsegrained (CG) model is developed by a structure matching method and validated against experiments conducted on a controlled, benchmark material. Using the Green-Kubo method, the relaxation function is computed from the autocorrelation of the stress tensor, sampled over equilibrium MD simulations, and mapped to a real time scale established by matching self-diffusion rates of atomistic and CG models. Master curves computed from the predicted stress relaxation function are then compared with dynamic mechanical analysis experiments mapped to a wide frequency range by time-temperature superposition, as well as measurements of ultrasonic shear wave propagation. Computational simulations from monodisperse and polydisperse configurations, representative of the benchmark polyurea, show excellent agreement with the experimental measurements over a multidecade range of loading frequency. V C 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016, 54, 797-810 KEYWORDS: coarse-grained molecular dynamics; mechanical properties; polyurea INTRODUCTION Knowledge of the connections between chemistry, structure, and properties is needed to develop improved polymers with a materials-by-design approach. Computational models offer promise in identifying these relationships, but unfortunately they typically lack predictive capability beyond a small range of properties. Molecular dynamics (MD) simulations can provide tremendous insight into how the fine details of chemistry, chain architecture, and microstructure affect many physical properties; however, they face well-known limitations in both time and length scales. The goal of this work is to develop coarse-grained (CG) models that enable molecular simulations to reach more representative time and length scales to investigate the viscoelastic properties of polyurea, a thermorheologically complex block copolymer, for which theoretical rheological models are difficult to apply.

We investigate the thermomechanical response of semi-crystalline polyethylene under shock compression by performing molecular dynamics (MD) simulations using a new coarse-graining scheme inspired by the embedded atom method. The coarse-graining scheme combines the iterative Boltzmann inversion method and least squares optimization to parameterize interactions between coarse-grained sites, including a many-body potential energy designed to improve the representability of the model across a wide range of thermodynamic states. We demonstrate that a coarse-grained model of polyethylene, calibrated to match target structural and thermodynamic data generated from isothermal MD simulations at different pressures, can also accurately predict the shock Hugoniot response. Analysis of the rise in temperature along the shock Hugoniot and comparison with analytical predictions from the Mie-Grüneisen equation of state are performed to thoroughly explore the thermodynamic consistency of the model. As the coarse-graining model affords nearly two orders of magnitude reduction in simulation time compared to all-atom MD simulations, the proposed model can help identify how nanoscale structure in semi-crystalline polymers, such as polyethylene, influences mechanical behavior under extreme loading.

Estimating entropy production directly from experimental trajectories is of great current interest but often requires a large amount of data or knowledge of the underlying dynamics. In this paper, we propose a minimal strategy using the short-time Thermodynamic Uncertainty Relation (TUR) by means of which we can simultaneously and quantitatively infer the thermodynamic force field acting on the system and the (potentially exact) rate of entropy production from experimental short-time trajectory data. We benchmark this scheme first for an experimental study of a colloidal particle system where exact analytical results are known, prior to studying the case of a colloidal particle in a hydrodynamical flow field, where neither analytical nor numerical results are available. In the latter case, we build an effective model of the system based on our results. In both cases, we also demonstrate that our results match with those obtained from another recently introduced scheme.