Multiscale Modeling and Coarse Graining of Polymer Dynamics: Simulations Guided by Statistical Beyond-Equilibrium Thermodynamics

TL;DR

This paper reviews and proposes multiscale modeling methods for polymer dynamics, emphasizing the importance of nonequilibrium thermodynamics to connect microscopic models with macroscopic behavior, especially accounting for dissipative effects.

Contribution

It introduces a new approach guided by nonequilibrium thermodynamics for linking microscopic and macroscopic models in polymer dynamics, including dissipative effects.

Findings

Successful illustration for a flowing polymer melt

Highlights importance of state variables in nonequilibrium modeling

Proposes methods to incorporate dissipative effects

Abstract

We review some recent coarse-graining and multi-scale methods, but also put forward some new ideas for addressing such issues. We find that, if one is guided by nonequilibrium statistical mechanics and thermodynamics, it is possible to design well-founded multi-scale modeling tools that can link microscopic models with macroscopic constitutive equations. Such multi-scale modeling tools benefit from recently proposed approaches for static coarse graining which are mainly built on potentials of mean force. For dynamical properties, however, coarse-grained models need to account for dissipative effects that arise due to fast degrees of freedom that are eliminated in favor of the remaining slowly varying ones. The proper definition of the set of the state variables, effectively representing the nonequilibrium states is the first key to the success of such an approach. Linking the microscopic model with a macroscopic model built on these slowly relaxing variables is the second key. We illustrate the new approach for a flowing, low-molecular polymer melt.