The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment

Detalhes bibliográficos
Autor(a) principal: Dalle, Danieli
Data de Publicação: 2022
Outros Autores: Hansen, Betina, Zattera, Ademir Jose, Ornaghi, Heitor Luiz, Monticeli, Francisco Maciel [UNESP], Catto, Andre Luis, Borsoi, Cleide
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1080/15440478.2022.2051670
http://hdl.handle.net/11449/218857
Resumo: Tobacco is a rich source of cellulosic material and one of the most cultivated non-food plants in the world with great potential for incorporation in polymeric matrices. The use of tobacco residues as reinforcing filler requires chemical/physical fiber treatment aiming to maximize compatibility with the polymer. In this study, tobacco residues were treated with two concentrations of NaOH (10 or 15 wt.%) at two-time exposures (3 or 5 h). Four distinct heating rates were used for each condition. It was applied an artificial neural network to model the thermogravimetric curves. After, the fitted ANN curves were used to create a 3D surface response. The equations from 3D surface response allowed the creation of thermogravimetric curves in any heating rate situated between the minimum and maximum range tested.
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spelling The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline TreatmentTobacco residuealkaline treatmentartificial neural networksurface response methodologyTobacco is a rich source of cellulosic material and one of the most cultivated non-food plants in the world with great potential for incorporation in polymeric matrices. The use of tobacco residues as reinforcing filler requires chemical/physical fiber treatment aiming to maximize compatibility with the polymer. In this study, tobacco residues were treated with two concentrations of NaOH (10 or 15 wt.%) at two-time exposures (3 or 5 h). Four distinct heating rates were used for each condition. It was applied an artificial neural network to model the thermogravimetric curves. After, the fitted ANN curves were used to create a 3D surface response. The equations from 3D surface response allowed the creation of thermogravimetric curves in any heating rate situated between the minimum and maximum range tested.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)UNIVATESUniv Caxias Sul, Programa Posgrad Engn Proc Tecnol PGEPROTEC, Rua Francisco Getulio Vargas, BR-1130 Caxias Do Sul, RS, BrazilUniv Vale Taquari UNIVATES, Ciencias Exatas & Engn, Av Avelino Talini 171, Lajeado, RS, BrazilUniv Fed Integracao LatinoAmer UNILA, Engn Mat, Foz Do Iguacu, BrazilUniv Estadual Paulista Unesp, Escola Engn, Dept Mat & Tecnol, Guaratingueta, SP, BrazilUniv Estadual Paulista Unesp, Escola Engn, Dept Mat & Tecnol, Guaratingueta, SP, BrazilTaylor & Francis IncUniv Caxias SulUniv Vale Taquari UNIVATESUniv Fed Integracao LatinoAmer UNILAUniversidade Estadual Paulista (UNESP)Dalle, DanieliHansen, BetinaZattera, Ademir JoseOrnaghi, Heitor LuizMonticeli, Francisco Maciel [UNESP]Catto, Andre LuisBorsoi, Cleide2022-04-28T17:23:33Z2022-04-28T17:23:33Z2022-04-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article10http://dx.doi.org/10.1080/15440478.2022.2051670Journal Of Natural Fibers. Philadelphia: Taylor & Francis Inc, 10 p., 2022.1544-0478http://hdl.handle.net/11449/21885710.1080/15440478.2022.2051670WOS:000778647800001Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal Of Natural Fibersinfo:eu-repo/semantics/openAccess2024-07-02T15:04:15Zoai:repositorio.unesp.br:11449/218857Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-06T00:02:12.627731Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment
title The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment
spellingShingle The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment
Dalle, Danieli
Tobacco residue
alkaline treatment
artificial neural network
surface response methodology
title_short The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment
title_full The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment
title_fullStr The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment
title_full_unstemmed The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment
title_sort The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment
author Dalle, Danieli
author_facet Dalle, Danieli
Hansen, Betina
Zattera, Ademir Jose
Ornaghi, Heitor Luiz
Monticeli, Francisco Maciel [UNESP]
Catto, Andre Luis
Borsoi, Cleide
author_role author
author2 Hansen, Betina
Zattera, Ademir Jose
Ornaghi, Heitor Luiz
Monticeli, Francisco Maciel [UNESP]
Catto, Andre Luis
Borsoi, Cleide
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Univ Caxias Sul
Univ Vale Taquari UNIVATES
Univ Fed Integracao LatinoAmer UNILA
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Dalle, Danieli
Hansen, Betina
Zattera, Ademir Jose
Ornaghi, Heitor Luiz
Monticeli, Francisco Maciel [UNESP]
Catto, Andre Luis
Borsoi, Cleide
dc.subject.por.fl_str_mv Tobacco residue
alkaline treatment
artificial neural network
surface response methodology
topic Tobacco residue
alkaline treatment
artificial neural network
surface response methodology
description Tobacco is a rich source of cellulosic material and one of the most cultivated non-food plants in the world with great potential for incorporation in polymeric matrices. The use of tobacco residues as reinforcing filler requires chemical/physical fiber treatment aiming to maximize compatibility with the polymer. In this study, tobacco residues were treated with two concentrations of NaOH (10 or 15 wt.%) at two-time exposures (3 or 5 h). Four distinct heating rates were used for each condition. It was applied an artificial neural network to model the thermogravimetric curves. After, the fitted ANN curves were used to create a 3D surface response. The equations from 3D surface response allowed the creation of thermogravimetric curves in any heating rate situated between the minimum and maximum range tested.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-28T17:23:33Z
2022-04-28T17:23:33Z
2022-04-06
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1080/15440478.2022.2051670
Journal Of Natural Fibers. Philadelphia: Taylor & Francis Inc, 10 p., 2022.
1544-0478
http://hdl.handle.net/11449/218857
10.1080/15440478.2022.2051670
WOS:000778647800001
url http://dx.doi.org/10.1080/15440478.2022.2051670
http://hdl.handle.net/11449/218857
identifier_str_mv Journal Of Natural Fibers. Philadelphia: Taylor & Francis Inc, 10 p., 2022.
1544-0478
10.1080/15440478.2022.2051670
WOS:000778647800001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal Of Natural Fibers
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 10
dc.publisher.none.fl_str_mv Taylor & Francis Inc
publisher.none.fl_str_mv Taylor & Francis Inc
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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