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Distribution Cutoff for Clusters near the Gel Point
[Image: see text] The mechanical and dynamic properties of developing networks near the gel point are susceptible to the distribution of clusters coexisting with percolating networks. The distribution of cluster numbers follows a broad power law, wrapped by a cutoff function that rapidly decays at a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562459/ https://www.ncbi.nlm.nih.gov/pubmed/36254314 http://dx.doi.org/10.1021/acspolymersau.2c00020 |
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author | Li, Douglas T. Rudnicki, Paul E. Qin, Jian |
author_facet | Li, Douglas T. Rudnicki, Paul E. Qin, Jian |
author_sort | Li, Douglas T. |
collection | PubMed |
description | [Image: see text] The mechanical and dynamic properties of developing networks near the gel point are susceptible to the distribution of clusters coexisting with percolating networks. The distribution of cluster numbers follows a broad power law, wrapped by a cutoff function that rapidly decays at a characteristic size. The form of the cutoff function has been speculated based on known results from lattice percolation and, in certain cases, solved. We obtained this cutoff function from simulated dynamic clusters of polymeric precursor chains using a hybrid Monte Carlo algorithm. The results obtained from three different precursor chain lengths are consistent with each other and are consistent with the expectation from lattice percolation. |
format | Online Article Text |
id | pubmed-9562459 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-95624592022-10-15 Distribution Cutoff for Clusters near the Gel Point Li, Douglas T. Rudnicki, Paul E. Qin, Jian ACS Polym Au [Image: see text] The mechanical and dynamic properties of developing networks near the gel point are susceptible to the distribution of clusters coexisting with percolating networks. The distribution of cluster numbers follows a broad power law, wrapped by a cutoff function that rapidly decays at a characteristic size. The form of the cutoff function has been speculated based on known results from lattice percolation and, in certain cases, solved. We obtained this cutoff function from simulated dynamic clusters of polymeric precursor chains using a hybrid Monte Carlo algorithm. The results obtained from three different precursor chain lengths are consistent with each other and are consistent with the expectation from lattice percolation. American Chemical Society 2022-07-12 /pmc/articles/PMC9562459/ /pubmed/36254314 http://dx.doi.org/10.1021/acspolymersau.2c00020 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Li, Douglas T. Rudnicki, Paul E. Qin, Jian Distribution Cutoff for Clusters near the Gel Point |
title | Distribution
Cutoff for Clusters near the Gel Point |
title_full | Distribution
Cutoff for Clusters near the Gel Point |
title_fullStr | Distribution
Cutoff for Clusters near the Gel Point |
title_full_unstemmed | Distribution
Cutoff for Clusters near the Gel Point |
title_short | Distribution
Cutoff for Clusters near the Gel Point |
title_sort | distribution
cutoff for clusters near the gel point |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562459/ https://www.ncbi.nlm.nih.gov/pubmed/36254314 http://dx.doi.org/10.1021/acspolymersau.2c00020 |
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