Statistical mechanical constitutive theory of polymer networks: The inextricable links between distribution, behavior, and ensemble

Michael R. Buche and Meredith N. Silberstein
Phys. Rev. E 102, 012501 – Published 2 July 2020

Abstract

A fundamental theory is presented for the mechanical response of polymer networks undergoing large deformation which seamlessly integrates statistical mechanical principles with macroscopic thermodynamic constitutive theory. Our formulation permits the consideration of arbitrary polymer chain behaviors when interactions among chains may be neglected. This careful treatment highlights the naturally occurring correspondence between single-chain mechanical behavior and the equilibrium distribution of chains in the network, as well as the correspondences between different single-chain thermodynamic ensembles. We demonstrate these important distinctions with the extensible freely jointed chain model. This statistical mechanical theory is then extended to the continuum scale, where we utilize traditional macroscopic constitutive theory to ultimately retrieve the Cauchy stress in terms of the deformation and polymer network statistics. Once again using the extensible freely jointed chain model, we illustrate the importance of the naturally occurring statistical correspondences through their effects on the stress-stretch response of the network. We additionally show that these differences vanish when the number of links in the chain becomes sufficiently large enough, and discuss why certain methods perform better than others before this limit is reached.

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  • Received 19 April 2020
  • Accepted 11 June 2020

DOI:https://doi.org/10.1103/PhysRevE.102.012501

©2020 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & ThermodynamicsPolymers & Soft Matter

Authors & Affiliations

Michael R. Buche and Meredith N. Silberstein*

  • Theoretical and Applied Mechanics, Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York 14853, USA

  • *ms2682@cornell.edu

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Issue

Vol. 102, Iss. 1 — July 2020

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