Distribution models for nitrophenols in a liquid-liquid system
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/37038 |
Resumo: | The formation of nitrophenols by-products is still of major concern for the economics and environmental impact of the industrial process of benzene (Bz) nitration to mononitrobenzene (MNB) with mixed acid (sulphuric and nitric acids). The knowledge of nitrophenol (NP) distribution ratios in the liquid-liquid mixture (Dj,j={NP}) is desirable for process optimization and for understanding the reaction mechanisms behind nitrophenols formation. In this study, a data-driven approach was implemented to provide prediction models for Dj of 2,4-dinitrophenol (DNP) and of 2,4,6-trinitrophenol (TNP) in a biphasic liquid system with a composition representative of the industrial processes. In the first step, screening tests were performed to identify the main variables influencing the experimental equilibrium weight fractions of nitrophenols in the aqueous phase wj,eA. Subsequently two independent data sets were built for development and external validation of prediction multivariate linear regression (MLR) models, at 30°C. The fitting results (R2 and Rad2⩾0.90) and the prediction results (Rpred,DNP2=0.931,Rpred,TNP2=0.908) confirmed the quality of the wj,eA models. Statistical significant predictive MLR models were also developed for Dj (which is related with wj,eA), at 30°C, with DNP evidencing a higher affinity for the organic phase (i.e. DDNP≈2DTNP). |
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Distribution models for nitrophenols in a liquid-liquid systemBenzene nitrationDistribution ratioMultivariate linear regressionNitrophenolsPredictive modelsThe formation of nitrophenols by-products is still of major concern for the economics and environmental impact of the industrial process of benzene (Bz) nitration to mononitrobenzene (MNB) with mixed acid (sulphuric and nitric acids). The knowledge of nitrophenol (NP) distribution ratios in the liquid-liquid mixture (Dj,j={NP}) is desirable for process optimization and for understanding the reaction mechanisms behind nitrophenols formation. In this study, a data-driven approach was implemented to provide prediction models for Dj of 2,4-dinitrophenol (DNP) and of 2,4,6-trinitrophenol (TNP) in a biphasic liquid system with a composition representative of the industrial processes. In the first step, screening tests were performed to identify the main variables influencing the experimental equilibrium weight fractions of nitrophenols in the aqueous phase wj,eA. Subsequently two independent data sets were built for development and external validation of prediction multivariate linear regression (MLR) models, at 30°C. The fitting results (R2 and Rad2⩾0.90) and the prediction results (Rpred,DNP2=0.931,Rpred,TNP2=0.908) confirmed the quality of the wj,eA models. Statistical significant predictive MLR models were also developed for Dj (which is related with wj,eA), at 30°C, with DNP evidencing a higher affinity for the organic phase (i.e. DDNP≈2DTNP).Elsevier2023-04-14T10:57:12Z2018-11-02T00:00:00Z2018-11-02info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/37038eng0009-250910.1016/j.ces.2018.04.056Lopes, A.L.C.V.Ribeiro, A.F.G.Reis, M.P.S.Silva, D.C.M.Portugal, I.Baptista, C.M.S.G.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T12:11:24Zoai:ria.ua.pt:10773/37038Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:07:41.757298Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Distribution models for nitrophenols in a liquid-liquid system |
title |
Distribution models for nitrophenols in a liquid-liquid system |
spellingShingle |
Distribution models for nitrophenols in a liquid-liquid system Lopes, A.L.C.V. Benzene nitration Distribution ratio Multivariate linear regression Nitrophenols Predictive models |
title_short |
Distribution models for nitrophenols in a liquid-liquid system |
title_full |
Distribution models for nitrophenols in a liquid-liquid system |
title_fullStr |
Distribution models for nitrophenols in a liquid-liquid system |
title_full_unstemmed |
Distribution models for nitrophenols in a liquid-liquid system |
title_sort |
Distribution models for nitrophenols in a liquid-liquid system |
author |
Lopes, A.L.C.V. |
author_facet |
Lopes, A.L.C.V. Ribeiro, A.F.G. Reis, M.P.S. Silva, D.C.M. Portugal, I. Baptista, C.M.S.G. |
author_role |
author |
author2 |
Ribeiro, A.F.G. Reis, M.P.S. Silva, D.C.M. Portugal, I. Baptista, C.M.S.G. |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Lopes, A.L.C.V. Ribeiro, A.F.G. Reis, M.P.S. Silva, D.C.M. Portugal, I. Baptista, C.M.S.G. |
dc.subject.por.fl_str_mv |
Benzene nitration Distribution ratio Multivariate linear regression Nitrophenols Predictive models |
topic |
Benzene nitration Distribution ratio Multivariate linear regression Nitrophenols Predictive models |
description |
The formation of nitrophenols by-products is still of major concern for the economics and environmental impact of the industrial process of benzene (Bz) nitration to mononitrobenzene (MNB) with mixed acid (sulphuric and nitric acids). The knowledge of nitrophenol (NP) distribution ratios in the liquid-liquid mixture (Dj,j={NP}) is desirable for process optimization and for understanding the reaction mechanisms behind nitrophenols formation. In this study, a data-driven approach was implemented to provide prediction models for Dj of 2,4-dinitrophenol (DNP) and of 2,4,6-trinitrophenol (TNP) in a biphasic liquid system with a composition representative of the industrial processes. In the first step, screening tests were performed to identify the main variables influencing the experimental equilibrium weight fractions of nitrophenols in the aqueous phase wj,eA. Subsequently two independent data sets were built for development and external validation of prediction multivariate linear regression (MLR) models, at 30°C. The fitting results (R2 and Rad2⩾0.90) and the prediction results (Rpred,DNP2=0.931,Rpred,TNP2=0.908) confirmed the quality of the wj,eA models. Statistical significant predictive MLR models were also developed for Dj (which is related with wj,eA), at 30°C, with DNP evidencing a higher affinity for the organic phase (i.e. DDNP≈2DTNP). |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-11-02T00:00:00Z 2018-11-02 2023-04-14T10:57:12Z |
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://hdl.handle.net/10773/37038 |
url |
http://hdl.handle.net/10773/37038 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0009-2509 10.1016/j.ces.2018.04.056 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799137731217981440 |