The Use of the Artificial Neural Network (ANN) for Modeling of Thermogravimetric Curves of Tobacco Stalk Waste Exposed to Alkaline Treatment
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
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. |
id |
UNSP_57873b19933d9f26e6021513cc72c0a8 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/218857 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
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 |
|
_version_ |
1808129574835322880 |