A network model of transient polymers: exploring the micromechanics of nonlinear viscoelasticity. Journal Article uri icon

Overview

abstract

  • Dynamic networks contain crosslinks that re-associate after disconnecting, imparting them with viscoelastic properties. While continuum approaches have been developed to analyze their mechanical response, these approaches can only describe their evolution in an average sense, omitting local, stochastic mechanisms that are critical to damage initiation or strain localization. To address these limitations, we introduce a discrete numerical model that mesoscopically coarse-grains the individual constituents of a dynamic network to predict its mechanical and topological evolution. Each constituent consists of a set of flexible chains that are permanently cross-linked at one end and contain reversible binding sites at their free ends. We incorporate nonlinear force-extension of individual chains via a Langevin model, slip-bond dissociation through Eyring's model, and spatiotemporally-dependent bond attachment based on scaling theory. Applying incompressible, uniaxial tension to representative volume elements at a range of constant strain rates and network connectivities, we then compare the mechanical response of these networks to that predicted by the transient network theory. Ultimately, we find that the idealized continuum approach remains suitable for networks with high chain concentrations when deformed at low strain rates, yet the mesoscale model proves necessary for the exploration of localized stochastic events, such as variability of the bond kinetics, or the nucleation of micro-cavities that likely conceive damage and fracture.

publication date

  • October 6, 2021

Date in CU Experts

  • February 10, 2022 8:55 AM

Full Author List

  • Wagner RJ; Hobbs E; Vernerey FJ

author count

  • 3

Other Profiles

Electronic International Standard Serial Number (EISSN)

  • 1744-6848

Additional Document Info

start page

  • 8742

end page

  • 8757

volume

  • 17

issue

  • 38