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Single chain in mean field simulation of flexible and semiflexible polymers: comparison with discrete chain self-consistent field theory

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Abstract

Single chain in mean field (SCMF) simulation is a theoretical framework performing Monte Carlo moves of explicit polymer chains under quasi-instantaneously updated external fields which were originally imported from the self-consistent field theory (SCFT). Even though functional-based hybrid simulations are often used to compare the results of SCFT and MC simulation, the adoption of a finite number of coarse-grained segments makes direct comparison rather difficult. In this study, we perform SCMF simulation of block copolymers using various chain models and quantitatively compare it with discrete chain SCFT (DCSCFT) which finds the mean field solution of polymers with a finite number of segments. By comparing free energy and natural period of the symmetric block copolymer lamellar phase, we systematically show that DCSCFT serves as an intermediate step between SCMF simulation and SCFT. In addition, by adopting angle dependent bond potential, we perform SCMF simulation of semiflexible polymers using bead-spring and freely jointed chain models. As the chain stiffness increases, the lamellar phase tends to align perpendicular to the surfaces when confined between two neutral walls. We also investigate the effects of fluctuation and chain stiffness on the distribution of chain ends. The tendency of chain end segregation towards the surfaces turns out to increase as the chain stiffness increases for both homopolymer and block copolymer systems.

Graphical abstract: Single chain in mean field simulation of flexible and semiflexible polymers: comparison with discrete chain self-consistent field theory

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Article information


Submitted
09 Apr 2020
Accepted
06 May 2020
First published
09 May 2020

Soft Matter, 2020, Advance Article
Article type
Paper

Single chain in mean field simulation of flexible and semiflexible polymers: comparison with discrete chain self-consistent field theory

S. J. Park and J. U. Kim, Soft Matter, 2020, Advance Article , DOI: 10.1039/D0SM00620C

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