On the statistical physics and thermodynamics of polymer networks: a Eulerian theory for entropic elasticity
Siyu Wang, Heng Xiao, Lin Zhan

TL;DR
This paper introduces a Eulerian thermodynamic framework for polymer networks that captures molecular kinematics and predicts entropic elasticity, outperforming traditional models and revealing a novel biaxial instability phase transition.
Contribution
It develops a new Eulerian variational approach based on thermodynamic equilibrium, linking molecular chain behavior to continuum deformation with improved predictive accuracy.
Findings
The hyperelastic model with two parameters outperforms existing models.
The model aligns with Biot-chain and Hencky strain energies in respective limits.
A new biaxial instability phase transition is identified in chain orientation.
Abstract
This study presents a Eulerian theory to elucidate the molecular kinematics in polymer networks and their connection to continuum deformation, grounded in fundamental statistical physics and thermodynamics. Three key innovations are incorporated: 1. The network behavior is described through a global thermodynamic equilibrium condition that maximizes the number of accessible microstates for all segments, instead of directly dealing with the well-established single-chain models commonly adopted in traditional approaches. A variational problem is then posed in the Eulerian framework to identify this equilibrium state under geometric fluctuation constraints. Its solution recaptures the classical single-chain model and reveals the dependence of chain kinematics upon continuum deformation. 2. The chain stretch and orientation probability are found to be explicitly specified through the…
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Taxonomy
TopicsComputational Drug Discovery Methods · Slime Mold and Myxomycetes Research · Graph theory and applications
