Improved Gaussian self-consistent method - Applications to homopolymers with different architectures in dilute solution

TL;DR

This paper introduces an improved Gaussian self-consistent (GSC) method that accurately predicts properties of homopolymers in dilute solutions, showing strong agreement with Monte Carlo simulations without relying on virial expansion.

Contribution

The paper presents a novel GSC approach that directly evaluates mean energy and accounts for hard sphere repulsion, enhancing accuracy over previous methods.

Findings

GSC results closely match Monte Carlo simulations across various polymer architectures.

The method effectively captures coil-to-globule transition behaviors.

Good agreement achieved without using Edwards' virial expansion.

Abstract

A version of the Gaussian self-consistent (GSC) method, which avoids the use of the Edwards' virial expansion, is presented. Instead, the mean energy is evaluated directly via a convolution of the attractive part of the pair-wise non-bonded potential with the Gaussian trial radial distribution function. The hard sphere repulsion is taken into account via a suitably generalised Carnahan-Starling term. Comparison of the mean-squared inter-monomer distances and radius of gyration, as well as of the mean energy, between the results from the GSC calculations and Monte Carlo (MC) simulation in continuous space are made across the coil-to-globule transition for isolated ring, open and star homopolymers of varied lengths and flexibility. Importantly, both techniques utilise the same polymer model so that the data points could be directly superimposed. A surprisingly good overall agreement is found between these GSC and MC results. Caveats of the Gaussian technique and ways for going beyond it are also discussed.