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A Simple Stochastic Reaction Model for Heterogeneous Polymerizations

The stochastic reaction model (SRM) treats polymerization as a pure probability‐based issue, which is widely applied to simulate various polymerization processes. However, in many studies, active centers were assumed to react with the same probability, which cannot reflect the heterogeneous reaction...

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Detalles Bibliográficos
Autores principales: Ma, Jiashu, Li, Jiahao, Yang, Bingbing, Liu, Siwen, Jiang, Bang-Ping, Ji, Shichen, Shen, Xing-Can
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414839/
https://www.ncbi.nlm.nih.gov/pubmed/36015526
http://dx.doi.org/10.3390/polym14163269
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author Ma, Jiashu
Li, Jiahao
Yang, Bingbing
Liu, Siwen
Jiang, Bang-Ping
Ji, Shichen
Shen, Xing-Can
author_facet Ma, Jiashu
Li, Jiahao
Yang, Bingbing
Liu, Siwen
Jiang, Bang-Ping
Ji, Shichen
Shen, Xing-Can
author_sort Ma, Jiashu
collection PubMed
description The stochastic reaction model (SRM) treats polymerization as a pure probability‐based issue, which is widely applied to simulate various polymerization processes. However, in many studies, active centers were assumed to react with the same probability, which cannot reflect the heterogeneous reaction microenvironment in heterogeneous polymerizations. Recently, we have proposed a simple SRM, in which the reaction probability of an active center is directly determined by the local reaction microenvironment. In this paper, we compared this simple SRM with other SRMs by examining living polymerizations with randomly dispersed and spatially localized initiators. The results confirmed that the reaction microenvironment plays an important role in heterogeneous polymerizations. This simple SRM provides a good choice to simulate various polymerizations.
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spelling pubmed-94148392022-08-27 A Simple Stochastic Reaction Model for Heterogeneous Polymerizations Ma, Jiashu Li, Jiahao Yang, Bingbing Liu, Siwen Jiang, Bang-Ping Ji, Shichen Shen, Xing-Can Polymers (Basel) Article The stochastic reaction model (SRM) treats polymerization as a pure probability‐based issue, which is widely applied to simulate various polymerization processes. However, in many studies, active centers were assumed to react with the same probability, which cannot reflect the heterogeneous reaction microenvironment in heterogeneous polymerizations. Recently, we have proposed a simple SRM, in which the reaction probability of an active center is directly determined by the local reaction microenvironment. In this paper, we compared this simple SRM with other SRMs by examining living polymerizations with randomly dispersed and spatially localized initiators. The results confirmed that the reaction microenvironment plays an important role in heterogeneous polymerizations. This simple SRM provides a good choice to simulate various polymerizations. MDPI 2022-08-11 /pmc/articles/PMC9414839/ /pubmed/36015526 http://dx.doi.org/10.3390/polym14163269 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ma, Jiashu
Li, Jiahao
Yang, Bingbing
Liu, Siwen
Jiang, Bang-Ping
Ji, Shichen
Shen, Xing-Can
A Simple Stochastic Reaction Model for Heterogeneous Polymerizations
title A Simple Stochastic Reaction Model for Heterogeneous Polymerizations
title_full A Simple Stochastic Reaction Model for Heterogeneous Polymerizations
title_fullStr A Simple Stochastic Reaction Model for Heterogeneous Polymerizations
title_full_unstemmed A Simple Stochastic Reaction Model for Heterogeneous Polymerizations
title_short A Simple Stochastic Reaction Model for Heterogeneous Polymerizations
title_sort simple stochastic reaction model for heterogeneous polymerizations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414839/
https://www.ncbi.nlm.nih.gov/pubmed/36015526
http://dx.doi.org/10.3390/polym14163269
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