Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions

Autores
Fortunatti, Cecilia; Sarmoria, Claudia; Brandolin, Adriana; Asteasuain, Mariano
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work, a model for the RAFT polymerization following the slow fragmentation approach was developed in order to obtain the full molecular weight distribution (MWD) using probability generating functions (pgf). A combination of univariate and bivariate pgf is applied to deal with the univariate chain length distributions of macroradical, dormant and dead polymer chains, and the bivariate distribution of the two arms intermediate adduct. This allows rigorous modeling of the polymerization system without simplifying assumptions. For comparison purposes, the population balances were solved by direct integration of the resulting equations. Our results show that the pgf technique allows obtaining an accurate solution efficiently in terms of computational time. What is more, the model provides a detailed characterization of the polymer that could be of great help for grasp the process fundamentals.
Fil: Fortunatti, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Sarmoria, Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Brandolin, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Asteasuain, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Materia
Modeling
Molecular Weight Distribution
Probability Generating Function
Raft Polymerization
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/13515
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functionsFortunatti, CeciliaSarmoria, ClaudiaBrandolin, AdrianaAsteasuain, MarianoModelingMolecular Weight DistributionProbability Generating FunctionRaft Polymerizationhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2In this work, a model for the RAFT polymerization following the slow fragmentation approach was developed in order to obtain the full molecular weight distribution (MWD) using probability generating functions (pgf). A combination of univariate and bivariate pgf is applied to deal with the univariate chain length distributions of macroradical, dormant and dead polymer chains, and the bivariate distribution of the two arms intermediate adduct. This allows rigorous modeling of the polymerization system without simplifying assumptions. For comparison purposes, the population balances were solved by direct integration of the resulting equations. Our results show that the pgf technique allows obtaining an accurate solution efficiently in terms of computational time. What is more, the model provides a detailed characterization of the polymer that could be of great help for grasp the process fundamentals.Fil: Fortunatti, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); ArgentinaFil: Sarmoria, Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); ArgentinaFil: Brandolin, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); ArgentinaFil: Asteasuain, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); ArgentinaElsevier2014-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/13515Fortunatti, Cecilia; Sarmoria, Claudia; Brandolin, Adriana; Asteasuain, Mariano; Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions; Elsevier; Computers and Chemical Engineering; 66; 7-2014; 214-2200098-1354enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135414000490info:eu-repo/semantics/altIdentifier/url/http://dx.doi.org/10.1016/j.compchemeng.2014.02.017info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:08:51Zoai:ri.conicet.gov.ar:11336/13515instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:08:51.965CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions
title Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions
spellingShingle Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions
Fortunatti, Cecilia
Modeling
Molecular Weight Distribution
Probability Generating Function
Raft Polymerization
title_short Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions
title_full Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions
title_fullStr Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions
title_full_unstemmed Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions
title_sort Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions
dc.creator.none.fl_str_mv Fortunatti, Cecilia
Sarmoria, Claudia
Brandolin, Adriana
Asteasuain, Mariano
author Fortunatti, Cecilia
author_facet Fortunatti, Cecilia
Sarmoria, Claudia
Brandolin, Adriana
Asteasuain, Mariano
author_role author
author2 Sarmoria, Claudia
Brandolin, Adriana
Asteasuain, Mariano
author2_role author
author
author
dc.subject.none.fl_str_mv Modeling
Molecular Weight Distribution
Probability Generating Function
Raft Polymerization
topic Modeling
Molecular Weight Distribution
Probability Generating Function
Raft Polymerization
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In this work, a model for the RAFT polymerization following the slow fragmentation approach was developed in order to obtain the full molecular weight distribution (MWD) using probability generating functions (pgf). A combination of univariate and bivariate pgf is applied to deal with the univariate chain length distributions of macroradical, dormant and dead polymer chains, and the bivariate distribution of the two arms intermediate adduct. This allows rigorous modeling of the polymerization system without simplifying assumptions. For comparison purposes, the population balances were solved by direct integration of the resulting equations. Our results show that the pgf technique allows obtaining an accurate solution efficiently in terms of computational time. What is more, the model provides a detailed characterization of the polymer that could be of great help for grasp the process fundamentals.
Fil: Fortunatti, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Sarmoria, Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Brandolin, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Asteasuain, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
description In this work, a model for the RAFT polymerization following the slow fragmentation approach was developed in order to obtain the full molecular weight distribution (MWD) using probability generating functions (pgf). A combination of univariate and bivariate pgf is applied to deal with the univariate chain length distributions of macroradical, dormant and dead polymer chains, and the bivariate distribution of the two arms intermediate adduct. This allows rigorous modeling of the polymerization system without simplifying assumptions. For comparison purposes, the population balances were solved by direct integration of the resulting equations. Our results show that the pgf technique allows obtaining an accurate solution efficiently in terms of computational time. What is more, the model provides a detailed characterization of the polymer that could be of great help for grasp the process fundamentals.
publishDate 2014
dc.date.none.fl_str_mv 2014-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/13515
Fortunatti, Cecilia; Sarmoria, Claudia; Brandolin, Adriana; Asteasuain, Mariano; Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions; Elsevier; Computers and Chemical Engineering; 66; 7-2014; 214-220
0098-1354
url http://hdl.handle.net/11336/13515
identifier_str_mv Fortunatti, Cecilia; Sarmoria, Claudia; Brandolin, Adriana; Asteasuain, Mariano; Prediction of the full molecular weight distribution in RAFT polymerization using probability generating functions; Elsevier; Computers and Chemical Engineering; 66; 7-2014; 214-220
0098-1354
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135414000490
info:eu-repo/semantics/altIdentifier/url/http://dx.doi.org/10.1016/j.compchemeng.2014.02.017
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.993085

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