Flow-Induced Disentanglement in Shear and Elongational Flows of Entangled Polymers: A Hi-Fidelity Molecular Simulation Study

University Of Tennessee Knoxville, Knoxville TN

Investigators

Abstract

PI: Edwards, Brian Proposal Number: 1602890 The goal of the proposed research is to understand the behavior of macromolecules (like polymers or proteins) and the way that these macromolecules get entangled and disentangled when the fluid velocity is high. While this is a fundamental problem that can be answered by observations at the molecular scale, it can have significant macroscopic effects that are important during the processing of fluids common in the petrochemical and the food industry, e.g., polymers, surfactants, and liquid crystals. Many theories have been proposed to explain the microstructural responses of these complex liquids under flow, but each invariably diverged from experiment at high strain rates. Recent evidence suggests that part of the reason for these divergences is that most flow models track bulk-average properties that have effectively discarded the short-timescale dynamical phenomena of the individual molecules. It has recently been observed via nonequilibrium molecular dynamics (NEMD) simulations of moderately-entangled polyethylene liquids that a remarkable dynamical response occurs at high strain rates in both shear and elongational flows: the polymeric liquid experiences a dramatic decrease in the number of chain entanglements, which leads to a network of highly-stretched chains that form effective tube-like structures through which neighboring chains experience anisotropic diffusion. In shear dominated flows, this ultimately leads to chain rotation and retraction cycles, which give rise to characteristic timescales that are much shorter than the reptation time of the liquid. This project will study this behavior using an unprecedented suite of NEMD and Dissipative Particle Dynamics (DPD) simulations of polyethylene liquids with up to 50 entanglements per chain. In addition, the knowledge gained will be harvested to develop a mesoscopic anisotropic diffusion model that can be applied to high strain-rate flows. Results of the proposed work could contribute to more efficient modeling of existing processes and to the design of new fluid materials, or the processes to manufacture them. Data resulting from this work will become available to the research community through the PolyHub storage site. There are also outreach and education activities planned that involve the development of educational modules.