New Development of Monte Carlo Techniques for Studying Bottle-brush Polymers

TL;DR

This paper introduces advanced Monte Carlo algorithms tailored for studying complex bottle-brush polymers, enabling efficient simulations of their structure and behavior under various conditions, and validating theoretical predictions with high-statistics results.

Contribution

It develops generalized and fast Monte Carlo algorithms for simulating bottle-brush polymers with complex architectures and flexible backbones, improving computational efficiency and accuracy.

Findings

Validated theoretical predictions of side chain behavior.

Analyzed radial monomer density profiles.

Demonstrated no change in gyration radius autocorrelation with backbone length.

Abstract

Due to the complex characteristics of bottle-brush polymers, it became a challenge to develop an efficient algorithm for studying such macromolecules under various solvent conditions or some constraints in the space by using computer simulations. In the limit of a bottle-brush polymer with a rather stiff backbone (straight rigid backbone), we generalize the variant of the biased chain growth algorithm, the pruned-enriched Rosenbluth method, for simulating polymers with complex architecture, from star polymers to bottle-brush polymers, on the simple cubic lattice. With the high statistics of our Monte Carlo results, we check the theoretical predictions of side chain behavior and radial monomer density profile. For the comparison of the experimental data for bottle-brush polymers with a flexible backbone and flexible side chains, based on the bond fluctuation model we propose another fast Monte Carlo algorithm combining the local moves, the pivot move, and an adjustable simulation lattice box. By monitoring the autocorrelation functions of gyration radii for the side chains and for the backbone, we see that for fixed side chain length there is no change in the behavior of these two functions as the backbone length increases. Our extensive results cover the range which is accessible for the comparison to experimental data and for the checking of the theoretically predicted scaling laws.