Study of phenol removal by cloud point extraction: a process optimization using experimental design

Detalhes bibliográficos
Autor(a) principal: Silva, Wanessa Paulino Neves
Data de Publicação: 2015
Outros Autores: Nascimento, André Ezequiel Gomes do, Moura, Maria Carlenise Paiva de Alencar, Oliveira, Humberto Neves Maia de, Barros Neto, Eduardo Lins de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRN
Texto Completo: https://repositorio.ufrn.br/handle/123456789/45050
Resumo: The use of nonionic surfactants in liquid–liquid extraction consists of a two-phase process without the presence of an organic solvent. The present study aims to optimize the process of phenol removal from an aqueous solution by applying the cloud point extraction technique. A three-level factorial design and response surface methodology were employed to assess the effects of temperature and surfactant concentration on the extraction process. It was evaluated the effects of these factors on the following parameters: percentage of phenol extracted, ratio between phase volumes, and residual amounts of phenol and surfactant in the dilute phase after separation. Mathematical models were developed to predict the effect of each variable and their interactions with the extraction parameters. A comparison between predicted values using model equations and experimental values exhibited correlation coefficients (R2 ) greater than 0.98. The models were validated by analysis of variance, significance, and prediction, allowing the estimation of process variables. Response surface methodology allowed the optimization of process variables. The results showed phenol removal of up to 95%
id UFRN_b0396ab793011c2e4faa43b051c446f1
oai_identifier_str oai:https://repositorio.ufrn.br:123456789/45050
network_acronym_str UFRN
network_name_str Repositório Institucional da UFRN
repository_id_str
spelling Silva, Wanessa Paulino NevesNascimento, André Ezequiel Gomes doMoura, Maria Carlenise Paiva de AlencarOliveira, Humberto Neves Maia deBarros Neto, Eduardo Lins de2021-11-29T14:21:17Z2021-11-29T14:21:17Z2015-09-25SILVA, Wanessa Paulino Neves; NASCIMENTO, André Ezequiel Gomes do; MOURA, Maria Carlenise Paiva de Alencar ; OLIVEIRA, Humberto Neves Maia de; BARROS NETO, Eduardo Lins de. Study of phenol removal by cloud point extraction: a process optimization using experimental design. Separation and Purification Technology (Print), v. 152, p. 133-139, 2015. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S1383586615301428?via%3Dihub. Acesso em: 26 jul. 2021. DOI: https://doi.org/10.1016/j.seppur.2015.08.007.1383-5866https://repositorio.ufrn.br/handle/123456789/45050The use of nonionic surfactants in liquid–liquid extraction consists of a two-phase process without the presence of an organic solvent. The present study aims to optimize the process of phenol removal from an aqueous solution by applying the cloud point extraction technique. A three-level factorial design and response surface methodology were employed to assess the effects of temperature and surfactant concentration on the extraction process. It was evaluated the effects of these factors on the following parameters: percentage of phenol extracted, ratio between phase volumes, and residual amounts of phenol and surfactant in the dilute phase after separation. Mathematical models were developed to predict the effect of each variable and their interactions with the extraction parameters. A comparison between predicted values using model equations and experimental values exhibited correlation coefficients (R2 ) greater than 0.98. The models were validated by analysis of variance, significance, and prediction, allowing the estimation of process variables. Response surface methodology allowed the optimization of process variables. The results showed phenol removal of up to 95%The use of nonionic surfactants in liquid–liquid extraction consists of a two-phase process without the presence of an organic solvent. The present study aims to optimize the process of phenol removal from an aqueous solution by applying the cloud point extraction technique. A three-level factorial design and response surface methodology were employed to assess the effects of temperature and surfactant concentration on the extraction process. It was evaluated the effects of these factors on the following parameters: percentage of phenol extracted, ratio between phase volumes, and residual amounts of phenol and surfactant in the dilute phase after separation. Mathematical models were developed to predict the effect of each variable and their interactions with the extraction parameters. A comparison between predicted values using model equations and experimental values exhibited correlation coefficients (R2 ) greater than 0.98. The models were validated by analysis of variance, significance, and prediction, allowing the estimation of process variables. Response surface methodology allowed the optimization of process variables. The results showed phenol removal of up to 95%ELSEVIERAttribution 3.0 Brazilhttps://creativecommons.org/licenses/by-nc-nd/3.0/info:eu-repo/semantics/openAccessPhenolSurfactantTriton X114Cloud point extractionStudy of phenol removal by cloud point extraction: a process optimization using experimental designinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleengreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNORIGINALStudyOfPhenolRemovalByCloudPointExtraction_BARROSNETO_2015.pdfStudyOfPhenolRemovalByCloudPointExtraction_BARROSNETO_2015.pdfArtigoapplication/pdf1467201https://repositorio.ufrn.br/bitstream/123456789/45050/1/StudyOfPhenolRemovalByCloudPointExtraction_BARROSNETO_2015.pdf1fa82b2d91c3fdc906a6292de202bb8fMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8914https://repositorio.ufrn.br/bitstream/123456789/45050/2/license_rdf4d2950bda3d176f570a9f8b328dfbbefMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81569https://repositorio.ufrn.br/bitstream/123456789/45050/3/license.txt6e6f57145bc87daf99079f06b081ff9fMD53123456789/450502021-11-29 11:38:15.167oai:https://repositorio.ufrn.br:123456789/45050TElDRU7Dh0HCoERFIERJU1RSSUJVScOHw4NPIE7Dg08tRVhDTFVTSVZBCgoKQW8gYXNzaW5hciBlIGVudHJlZ2FyIGVzdGHCoGxpY2Vuw6dhLCBvL2EgU3IuL1NyYS4gKGF1dG9yIG91IGRldGVudG9yIGRvcyBkaXJlaXRvcyBkZSBhdXRvcik6CgoKYSkgQ29uY2VkZSDDoCBVbml2ZXJzaWRhZGUgRmVkZXJhbCBkbyBSaW8gR3JhbmRlIGRvIE5vcnRlIG8gZGlyZWl0byBuw6NvLWV4Y2x1c2l2byBkZQpyZXByb2R1emlyLCBjb252ZXJ0ZXIgKGNvbW8gZGVmaW5pZG8gYWJhaXhvKSwgY29tdW5pY2FyIGUvb3UKZGlzdHJpYnVpciBvIGRvY3VtZW50byBlbnRyZWd1ZSAoaW5jbHVpbmRvIG8gcmVzdW1vL2Fic3RyYWN0KSBlbQpmb3JtYXRvIGRpZ2l0YWwgb3UgaW1wcmVzc28gZSBlbSBxdWFscXVlciBtZWlvLgoKYikgRGVjbGFyYSBxdWUgbyBkb2N1bWVudG8gZW50cmVndWUgw6kgc2V1IHRyYWJhbGhvIG9yaWdpbmFsLCBlIHF1ZQpkZXTDqW0gbyBkaXJlaXRvIGRlIGNvbmNlZGVyIG9zIGRpcmVpdG9zIGNvbnRpZG9zIG5lc3RhwqBsaWNlbsOnYS4gRGVjbGFyYQp0YW1iw6ltIHF1ZSBhIGVudHJlZ2EgZG8gZG9jdW1lbnRvIG7Do28gaW5mcmluZ2UsIHRhbnRvIHF1YW50byBsaGUgw6kKcG9zc8OtdmVsIHNhYmVyLCBvcyBkaXJlaXRvcyBkZSBxdWFscXVlciBvdXRyYSBwZXNzb2Egb3UgZW50aWRhZGUuCgpjKSBTZSBvIGRvY3VtZW50byBlbnRyZWd1ZSBjb250w6ltIG1hdGVyaWFsIGRvIHF1YWwgbsOjbyBkZXTDqW0gb3MKZGlyZWl0b3MgZGUgYXV0b3IsIGRlY2xhcmEgcXVlIG9idGV2ZSBhdXRvcml6YcOnw6NvIGRvIGRldGVudG9yIGRvcwpkaXJlaXRvcyBkZSBhdXRvciBwYXJhIGNvbmNlZGVyIMOgIFVuaXZlcnNpZGFkZSBGZWRlcmFsIGRvIFJpbyBHcmFuZGUgZG8gTm9ydGUgb3MgZGlyZWl0b3MgcmVxdWVyaWRvcyBwb3IgZXN0YcKgbGljZW7Dp2EsIGUgcXVlIGVzc2UgbWF0ZXJpYWwgY3Vqb3MgZGlyZWl0b3Mgc8OjbyBkZQp0ZXJjZWlyb3MgZXN0w6EgY2xhcmFtZW50ZSBpZGVudGlmaWNhZG8gZSByZWNvbmhlY2lkbyBubyB0ZXh0byBvdQpjb250ZcO6ZG8gZG8gZG9jdW1lbnRvIGVudHJlZ3VlLgoKU2UgbyBkb2N1bWVudG8gZW50cmVndWUgw6kgYmFzZWFkbyBlbSB0cmFiYWxobyBmaW5hbmNpYWRvIG91IGFwb2lhZG8KcG9yIG91dHJhIGluc3RpdHVpw6fDo28gcXVlIG7Do28gYSBVbml2ZXJzaWRhZGUgRmVkZXJhbCBkbyBSaW8gR3JhbmRlIGRvIE5vcnRlLCBkZWNsYXJhIHF1ZSBjdW1wcml1IHF1YWlzcXVlciBvYnJpZ2HDp8O1ZXMgZXhpZ2lkYXMgcGVsbyByZXNwZWN0aXZvIGNvbnRyYXRvIG91IGFjb3Jkby4KCkEgVW5pdmVyc2lkYWRlIEZlZGVyYWwgZG8gUmlvIEdyYW5kZSBkbyBOb3J0ZSBpZGVudGlmaWNhcsOhIGNsYXJhbWVudGUgbyhzKSBzZXUgKHMpIG5vbWUocykgY29tbyBvIChzKSBhdXRvciAoZXMpIG91IGRldGVudG9yIChlcykgZG9zIGRpcmVpdG9zIGRvIGRvY3VtZW50bwplbnRyZWd1ZSwgZSBuw6NvIGZhcsOhIHF1YWxxdWVyIGFsdGVyYcOnw6NvLCBwYXJhIGFsw6ltIGRhcyBwZXJtaXRpZGFzIHBvcgplc3RhwqBsaWNlbsOnYS4KRepositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2021-11-29T14:38:15Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false
dc.title.pt_BR.fl_str_mv Study of phenol removal by cloud point extraction: a process optimization using experimental design
title Study of phenol removal by cloud point extraction: a process optimization using experimental design
spellingShingle Study of phenol removal by cloud point extraction: a process optimization using experimental design
Silva, Wanessa Paulino Neves
Phenol
Surfactant
Triton X114
Cloud point extraction
title_short Study of phenol removal by cloud point extraction: a process optimization using experimental design
title_full Study of phenol removal by cloud point extraction: a process optimization using experimental design
title_fullStr Study of phenol removal by cloud point extraction: a process optimization using experimental design
title_full_unstemmed Study of phenol removal by cloud point extraction: a process optimization using experimental design
title_sort Study of phenol removal by cloud point extraction: a process optimization using experimental design
author Silva, Wanessa Paulino Neves
author_facet Silva, Wanessa Paulino Neves
Nascimento, André Ezequiel Gomes do
Moura, Maria Carlenise Paiva de Alencar
Oliveira, Humberto Neves Maia de
Barros Neto, Eduardo Lins de
author_role author
author2 Nascimento, André Ezequiel Gomes do
Moura, Maria Carlenise Paiva de Alencar
Oliveira, Humberto Neves Maia de
Barros Neto, Eduardo Lins de
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Silva, Wanessa Paulino Neves
Nascimento, André Ezequiel Gomes do
Moura, Maria Carlenise Paiva de Alencar
Oliveira, Humberto Neves Maia de
Barros Neto, Eduardo Lins de
dc.subject.por.fl_str_mv Phenol
Surfactant
Triton X114
Cloud point extraction
topic Phenol
Surfactant
Triton X114
Cloud point extraction
description The use of nonionic surfactants in liquid–liquid extraction consists of a two-phase process without the presence of an organic solvent. The present study aims to optimize the process of phenol removal from an aqueous solution by applying the cloud point extraction technique. A three-level factorial design and response surface methodology were employed to assess the effects of temperature and surfactant concentration on the extraction process. It was evaluated the effects of these factors on the following parameters: percentage of phenol extracted, ratio between phase volumes, and residual amounts of phenol and surfactant in the dilute phase after separation. Mathematical models were developed to predict the effect of each variable and their interactions with the extraction parameters. A comparison between predicted values using model equations and experimental values exhibited correlation coefficients (R2 ) greater than 0.98. The models were validated by analysis of variance, significance, and prediction, allowing the estimation of process variables. Response surface methodology allowed the optimization of process variables. The results showed phenol removal of up to 95%
publishDate 2015
dc.date.issued.fl_str_mv 2015-09-25
dc.date.accessioned.fl_str_mv 2021-11-29T14:21:17Z
dc.date.available.fl_str_mv 2021-11-29T14:21:17Z
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.citation.fl_str_mv SILVA, Wanessa Paulino Neves; NASCIMENTO, André Ezequiel Gomes do; MOURA, Maria Carlenise Paiva de Alencar ; OLIVEIRA, Humberto Neves Maia de; BARROS NETO, Eduardo Lins de. Study of phenol removal by cloud point extraction: a process optimization using experimental design. Separation and Purification Technology (Print), v. 152, p. 133-139, 2015. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S1383586615301428?via%3Dihub. Acesso em: 26 jul. 2021. DOI: https://doi.org/10.1016/j.seppur.2015.08.007.
dc.identifier.uri.fl_str_mv https://repositorio.ufrn.br/handle/123456789/45050
dc.identifier.issn.none.fl_str_mv 1383-5866
identifier_str_mv SILVA, Wanessa Paulino Neves; NASCIMENTO, André Ezequiel Gomes do; MOURA, Maria Carlenise Paiva de Alencar ; OLIVEIRA, Humberto Neves Maia de; BARROS NETO, Eduardo Lins de. Study of phenol removal by cloud point extraction: a process optimization using experimental design. Separation and Purification Technology (Print), v. 152, p. 133-139, 2015. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S1383586615301428?via%3Dihub. Acesso em: 26 jul. 2021. DOI: https://doi.org/10.1016/j.seppur.2015.08.007.
1383-5866
url https://repositorio.ufrn.br/handle/123456789/45050
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Attribution 3.0 Brazil
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 3.0 Brazil
https://creativecommons.org/licenses/by-nc-nd/3.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv ELSEVIER
publisher.none.fl_str_mv ELSEVIER
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFRN
instname:Universidade Federal do Rio Grande do Norte (UFRN)
instacron:UFRN
instname_str Universidade Federal do Rio Grande do Norte (UFRN)
instacron_str UFRN
institution UFRN
reponame_str Repositório Institucional da UFRN
collection Repositório Institucional da UFRN
bitstream.url.fl_str_mv https://repositorio.ufrn.br/bitstream/123456789/45050/1/StudyOfPhenolRemovalByCloudPointExtraction_BARROSNETO_2015.pdf
https://repositorio.ufrn.br/bitstream/123456789/45050/2/license_rdf
https://repositorio.ufrn.br/bitstream/123456789/45050/3/license.txt
bitstream.checksum.fl_str_mv 1fa82b2d91c3fdc906a6292de202bb8f
4d2950bda3d176f570a9f8b328dfbbef
6e6f57145bc87daf99079f06b081ff9f
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
repository.name.fl_str_mv Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)
repository.mail.fl_str_mv
_version_ 1802117857247494144