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A Hybrid Monte Carlo Self-Consistent Field Model of Physical Gels of Telechelic Polymers
[Image: see text] We developed a hybrid Monte Carlo self-consistent field technique to model physical gels composed of ABA triblock copolymers and gain insight into the structure and interactions in such gels. The associative A blocks of the polymers are confined to small volumes called nodes, while...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical Society
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328284/ https://www.ncbi.nlm.nih.gov/pubmed/30362745 http://dx.doi.org/10.1021/acs.jctc.7b01264 |
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author | Bergsma, J. Leermakers, F. A. M. Kleijn, J. M. van der Gucht, J. |
author_facet | Bergsma, J. Leermakers, F. A. M. Kleijn, J. M. van der Gucht, J. |
author_sort | Bergsma, J. |
collection | PubMed |
description | [Image: see text] We developed a hybrid Monte Carlo self-consistent field technique to model physical gels composed of ABA triblock copolymers and gain insight into the structure and interactions in such gels. The associative A blocks of the polymers are confined to small volumes called nodes, while the B block can move freely as long as it is connected to the A blocks. A Monte Carlo algorithm is used to sample the node configurations on a lattice, and Scheutjens–Fleer self-consistent field (SF-SCF) equations are used to determine the change in free energy. The advantage of this approach over more coarse grained methods is that we do not need to predefine an interaction potential between the nodes. Using this MC-SCF hybrid simulation, we determined the radial distribution functions of the nodes and structure factors and osmotic compressibilities of the gels. For a high number of polymers per node and a solvent-B Flory–Huggins interaction parameter of 0.5, phase separation is predicted. Because of limitations in the simulation volume, we did however not establish the full phase diagram. For comparison, we performed some coarse-grained MC simulations in which the nodes are modeled as single particles with pair potentials extracted from SF-SCF calculations. At intermediate concentrations, these simulations gave qualitatively similar results as the MC-SCF hybrid. However, at relatively low and high polymer volume fractions, the structure of the coarse-grained gels is significantly different because higher-order interactions between the nodes are not accounted for. Finally, we compare the predictions of the MC-SCF simulations with experimental and modeling data on telechelic polymer networks from literature. |
format | Online Article Text |
id | pubmed-6328284 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American
Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-63282842019-01-17 A Hybrid Monte Carlo Self-Consistent Field Model of Physical Gels of Telechelic Polymers Bergsma, J. Leermakers, F. A. M. Kleijn, J. M. van der Gucht, J. J Chem Theory Comput [Image: see text] We developed a hybrid Monte Carlo self-consistent field technique to model physical gels composed of ABA triblock copolymers and gain insight into the structure and interactions in such gels. The associative A blocks of the polymers are confined to small volumes called nodes, while the B block can move freely as long as it is connected to the A blocks. A Monte Carlo algorithm is used to sample the node configurations on a lattice, and Scheutjens–Fleer self-consistent field (SF-SCF) equations are used to determine the change in free energy. The advantage of this approach over more coarse grained methods is that we do not need to predefine an interaction potential between the nodes. Using this MC-SCF hybrid simulation, we determined the radial distribution functions of the nodes and structure factors and osmotic compressibilities of the gels. For a high number of polymers per node and a solvent-B Flory–Huggins interaction parameter of 0.5, phase separation is predicted. Because of limitations in the simulation volume, we did however not establish the full phase diagram. For comparison, we performed some coarse-grained MC simulations in which the nodes are modeled as single particles with pair potentials extracted from SF-SCF calculations. At intermediate concentrations, these simulations gave qualitatively similar results as the MC-SCF hybrid. However, at relatively low and high polymer volume fractions, the structure of the coarse-grained gels is significantly different because higher-order interactions between the nodes are not accounted for. Finally, we compare the predictions of the MC-SCF simulations with experimental and modeling data on telechelic polymer networks from literature. American Chemical Society 2018-10-26 2018-12-11 /pmc/articles/PMC6328284/ /pubmed/30362745 http://dx.doi.org/10.1021/acs.jctc.7b01264 Text en Copyright © 2018 American Chemical Society This is an open access article published under a Creative Commons Non-Commercial No Derivative Works (CC-BY-NC-ND) Attribution License (http://pubs.acs.org/page/policy/authorchoice_ccbyncnd_termsofuse.html) , which permits copying and redistribution of the article, and creation of adaptations, all for non-commercial purposes. |
spellingShingle | Bergsma, J. Leermakers, F. A. M. Kleijn, J. M. van der Gucht, J. A Hybrid Monte Carlo Self-Consistent Field Model of Physical Gels of Telechelic Polymers |
title | A Hybrid Monte Carlo Self-Consistent Field Model of
Physical Gels of Telechelic Polymers |
title_full | A Hybrid Monte Carlo Self-Consistent Field Model of
Physical Gels of Telechelic Polymers |
title_fullStr | A Hybrid Monte Carlo Self-Consistent Field Model of
Physical Gels of Telechelic Polymers |
title_full_unstemmed | A Hybrid Monte Carlo Self-Consistent Field Model of
Physical Gels of Telechelic Polymers |
title_short | A Hybrid Monte Carlo Self-Consistent Field Model of
Physical Gels of Telechelic Polymers |
title_sort | hybrid monte carlo self-consistent field model of
physical gels of telechelic polymers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328284/ https://www.ncbi.nlm.nih.gov/pubmed/30362745 http://dx.doi.org/10.1021/acs.jctc.7b01264 |
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