Molecular Simulation Guided Constitutive Modeling on Finite Viscoelasticity of Elastomers
Ying Li (Northwestern University), Shan Tang (Chongqing University), Brendan C. Abberton (Northwestern University), Martin Kroger (ETH Zurich), Wing Kam Liu (Northwestern University)
Computational Materials Design via Multi-scale Modeling
Wed 1:30 - 2:50
Barus-Holley 190
A predictive multiscale computational framework has been developed to study the finite viscoelastic properties of elastomers. Using the Inverse Boltzmann Method, both the static structures and dynamic behavior of all-atomistic models of elastomers can be reproduced by a simple coarse-grained model, which bridges the scale from nano to meso. On this coarse-grained level, the entangled network of elastomers is described via a primitive path analysis (Z1 code). This description allows extraction of the tube diameter and primitive chain length, quantities required to bridge the scale from meso to micro. Furthermore, by making the affine-deformation assumption, a continuum constitutive law for elastomers has been developed from the tube model of primitive paths, which bridges the scale from micro to macro. In this way, the different scales are crossed by using different bridging laws, which enable us to directly predict the viscoelastic properties of elastomers using a bottom-up approach. Our predicted dynamic moduli, zero-rate shear viscosities, and relaxation moduli of natural rubbers are found to be in excellent agreement with experimental results. The developed multiscale computational framework can also be naturally extended to the finite deformation regime. Both the tube diameter and primitive chain length are found to increase with deformation, which enhances the viscous energy dissipation of elastomers under extremely large deformations. To the authors’ knowledge, this is the first work in which a multiscale computational framework has been proposed to predict the finite viscoelastic properties of elastomers from the molecular level. Not only can the method put forth in this research be used to predict the viscoelastic properties of elastomers in a bottom-up fashion, it can also be applied to design the elastomers with targeted functions, within a top-down approach.