Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions

Autores
Fortunatti, Cecilia; Sarmoria, Claudia; Brandolin, Adriana; Asteasuain, Mariano
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work, we develop a mathematical model of a RAFT copolymerization process able to predict average molecular properties as well as the full bivariate molecular weight distribution – copolymer composition distribution (MWD-CCD) of the copolymer. This model takes into account the three main kinetic theories proposed in the literature. The bivariate MWD-CCD is obtained by means of the 2D probability generating function (pgf) technique. This modeling technique can be used without any simplifying assumptions or a priori knowledge of the distribution shape. The results highlight the advantages of simulation as a powerful tool to get insight in the relationship between operating conditions and molecular structure.
Fil: Fortunatti, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Sarmoria, Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Brandolin, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Asteasuain, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Materia
Copolymerization
Modeling
Molecular Weight Distribution (Mwd)
Probability Generating Function (Pgf)
Reversible Addition Fragmentation Chain Transfer (Raft)
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/64829
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/64829
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functionsFortunatti, CeciliaSarmoria, ClaudiaBrandolin, AdrianaAsteasuain, MarianoCopolymerizationModelingMolecular Weight Distribution (Mwd)Probability Generating Function (Pgf)Reversible Addition Fragmentation Chain Transfer (Raft)https://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2In this work, we develop a mathematical model of a RAFT copolymerization process able to predict average molecular properties as well as the full bivariate molecular weight distribution – copolymer composition distribution (MWD-CCD) of the copolymer. This model takes into account the three main kinetic theories proposed in the literature. The bivariate MWD-CCD is obtained by means of the 2D probability generating function (pgf) technique. This modeling technique can be used without any simplifying assumptions or a priori knowledge of the distribution shape. The results highlight the advantages of simulation as a powerful tool to get insight in the relationship between operating conditions and molecular structure.Fil: Fortunatti, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Sarmoria, Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Brandolin, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Asteasuain, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaElsevier Science2017-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/64829Fortunatti, Cecilia; Sarmoria, Claudia; Brandolin, Adriana; Asteasuain, Mariano; Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions; Elsevier Science; Computational Materials Science; 136; 8-2017; 280-2960927-0256CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.commatsci.2017.04.013info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0927025617301969info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:33:50Zoai:ri.conicet.gov.ar:11336/64829instacron: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:34982025-09-29 09:33:51.125CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions
title Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions
spellingShingle Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions
Fortunatti, Cecilia
Copolymerization
Modeling
Molecular Weight Distribution (Mwd)
Probability Generating Function (Pgf)
Reversible Addition Fragmentation Chain Transfer (Raft)
title_short Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions
title_full Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions
title_fullStr Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions
title_full_unstemmed Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions
title_sort Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization 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 Copolymerization
Modeling
Molecular Weight Distribution (Mwd)
Probability Generating Function (Pgf)
Reversible Addition Fragmentation Chain Transfer (Raft)
topic Copolymerization
Modeling
Molecular Weight Distribution (Mwd)
Probability Generating Function (Pgf)
Reversible Addition Fragmentation Chain Transfer (Raft)
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, we develop a mathematical model of a RAFT copolymerization process able to predict average molecular properties as well as the full bivariate molecular weight distribution – copolymer composition distribution (MWD-CCD) of the copolymer. This model takes into account the three main kinetic theories proposed in the literature. The bivariate MWD-CCD is obtained by means of the 2D probability generating function (pgf) technique. This modeling technique can be used without any simplifying assumptions or a priori knowledge of the distribution shape. The results highlight the advantages of simulation as a powerful tool to get insight in the relationship between operating conditions and molecular structure.
Fil: Fortunatti, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Sarmoria, Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Brandolin, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Asteasuain, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
description In this work, we develop a mathematical model of a RAFT copolymerization process able to predict average molecular properties as well as the full bivariate molecular weight distribution – copolymer composition distribution (MWD-CCD) of the copolymer. This model takes into account the three main kinetic theories proposed in the literature. The bivariate MWD-CCD is obtained by means of the 2D probability generating function (pgf) technique. This modeling technique can be used without any simplifying assumptions or a priori knowledge of the distribution shape. The results highlight the advantages of simulation as a powerful tool to get insight in the relationship between operating conditions and molecular structure.
publishDate 2017
dc.date.none.fl_str_mv 2017-08
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/11336/64829
Fortunatti, Cecilia; Sarmoria, Claudia; Brandolin, Adriana; Asteasuain, Mariano; Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions; Elsevier Science; Computational Materials Science; 136; 8-2017; 280-296
0927-0256
CONICET Digital
CONICET
url http://hdl.handle.net/11336/64829
identifier_str_mv Fortunatti, Cecilia; Sarmoria, Claudia; Brandolin, Adriana; Asteasuain, Mariano; Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions; Elsevier Science; Computational Materials Science; 136; 8-2017; 280-296
0927-0256
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.commatsci.2017.04.013
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0927025617301969
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
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 13.070432

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