Polymer models with optimal good-solvent behavior

TL;DR

This paper introduces three continuum polymer models with a tunable parameter to optimize good-solvent behavior, revealing conditions for asymptotic behavior and applications to DNA modeling.

Contribution

It identifies a specific parameter value where different polymer models exhibit optimal good-solvent behavior, enabling efficient long-chain simulations and topological studies.

Findings

All models show asymptotic behavior at a specific parameter r*.

Thick self-avoiding chains are suitable for topological and dynamical studies.

The models provide insights into DNA as a good-solvent polymer.

Abstract

We consider three different continuum polymer models, that all depend on a tunable parameter r that determines the strength of the excluded-volume interactions. In the first model chains are obtained by concatenating hard spherocylinders of height b and diameter rb (we call them thick self- avoiding chains). The other two models are generalizations of the tangent hard-sphere and of the Kremer-Grest models. We show that, for a specific value r*, all models show an optimal behavior: asymptotic long-chain behavior is observed for relatively short chains. For r < r*, instead, the behavior can be parametrized by using the two-parameter model that also describes the thermal crossover close to the {\theta} point. The bonds of thick self-avoiding chains cannot cross each other and, therefore, the model is suited for the investigation of topological properties and for dynamical studies. Such a model also provides a coarse-grained description of double-stranded DNA, so that we can use our results to discuss under which conditions DNA can be considered as a model good-solvent polymer.