Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Douglas T., Rudnicki, Paul E., Qin, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
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
_version_ 1784808177069457408
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
work_keys_str_mv AT lidouglast distributioncutoffforclustersnearthegelpoint
AT rudnickipaule distributioncutoffforclustersnearthegelpoint
AT qinjian distributioncutoffforclustersnearthegelpoint