Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches

Autores
Goodarzi, Mohammad; Duchowicz, Pablo Román; Freitas, Matheus P.; Fernández, Francisco Marcelo
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The Hildebrand solubility parameter (ý) provides a numerical estimate of the degree of interaction between materials, and can be a good indication of solubility. In this work, a small number of physicochemical variables were appropriately selected from a pool of Dragon descriptors and correlated with the Hildebrand thermodynamic parameter of compounds previously studied as organic solvents of buckminsterfullerene (C60), using multiple linear regression and support vector machines. Models were validated using an external set of compounds and the statistical parameters obtained revealed the high prediction performance of all models, especially the one based on nonlinear regression. These findings provide useful information about which solvent and corresponding characteristics are important for solubility studies of e.g. this increasingly useful carbon allotrope.
Fil: Goodarzi, Mohammad. Islamic Azad University; Irán
Fil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina
Fil: Freitas, Matheus P.. Universidad Federal de Lavras; Brasil
Fil: Fernández, Francisco Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina
Materia
QSPR
Artificial Neural Networks
Hildebrand parameter
fullerene
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:11336/247638
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approachesGoodarzi, MohammadDuchowicz, Pablo RománFreitas, Matheus P.Fernández, Francisco MarceloQSPRArtificial Neural NetworksHildebrand parameterfullerenehttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1The Hildebrand solubility parameter (ý) provides a numerical estimate of the degree of interaction between materials, and can be a good indication of solubility. In this work, a small number of physicochemical variables were appropriately selected from a pool of Dragon descriptors and correlated with the Hildebrand thermodynamic parameter of compounds previously studied as organic solvents of buckminsterfullerene (C60), using multiple linear regression and support vector machines. Models were validated using an external set of compounds and the statistical parameters obtained revealed the high prediction performance of all models, especially the one based on nonlinear regression. These findings provide useful information about which solvent and corresponding characteristics are important for solubility studies of e.g. this increasingly useful carbon allotrope.Fil: Goodarzi, Mohammad. Islamic Azad University; IránFil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Freitas, Matheus P.. Universidad Federal de Lavras; BrasilFil: Fernández, Francisco Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaElsevier Science2010-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/247638Goodarzi, Mohammad; Duchowicz, Pablo Román; Freitas, Matheus P.; Fernández, Francisco Marcelo; Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches; Elsevier Science; Fluid Phase Equilibria; 293; 2; 6-2010; 130-1360378-3812CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378381210001007info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fluid.2010.02.025info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:49:25Zoai:ri.conicet.gov.ar:11336/247638instacron: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 09:49:25.872CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches
title Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches
spellingShingle Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches
Goodarzi, Mohammad
QSPR
Artificial Neural Networks
Hildebrand parameter
fullerene
title_short Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches
title_full Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches
title_fullStr Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches
title_full_unstemmed Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches
title_sort Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches
dc.creator.none.fl_str_mv Goodarzi, Mohammad
Duchowicz, Pablo Román
Freitas, Matheus P.
Fernández, Francisco Marcelo
author Goodarzi, Mohammad
author_facet Goodarzi, Mohammad
Duchowicz, Pablo Román
Freitas, Matheus P.
Fernández, Francisco Marcelo
author_role author
author2 Duchowicz, Pablo Román
Freitas, Matheus P.
Fernández, Francisco Marcelo
author2_role author
author
author
dc.subject.none.fl_str_mv QSPR
Artificial Neural Networks
Hildebrand parameter
fullerene
topic QSPR
Artificial Neural Networks
Hildebrand parameter
fullerene
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The Hildebrand solubility parameter (ý) provides a numerical estimate of the degree of interaction between materials, and can be a good indication of solubility. In this work, a small number of physicochemical variables were appropriately selected from a pool of Dragon descriptors and correlated with the Hildebrand thermodynamic parameter of compounds previously studied as organic solvents of buckminsterfullerene (C60), using multiple linear regression and support vector machines. Models were validated using an external set of compounds and the statistical parameters obtained revealed the high prediction performance of all models, especially the one based on nonlinear regression. These findings provide useful information about which solvent and corresponding characteristics are important for solubility studies of e.g. this increasingly useful carbon allotrope.
Fil: Goodarzi, Mohammad. Islamic Azad University; Irán
Fil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina
Fil: Freitas, Matheus P.. Universidad Federal de Lavras; Brasil
Fil: Fernández, Francisco Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina
description The Hildebrand solubility parameter (ý) provides a numerical estimate of the degree of interaction between materials, and can be a good indication of solubility. In this work, a small number of physicochemical variables were appropriately selected from a pool of Dragon descriptors and correlated with the Hildebrand thermodynamic parameter of compounds previously studied as organic solvents of buckminsterfullerene (C60), using multiple linear regression and support vector machines. Models were validated using an external set of compounds and the statistical parameters obtained revealed the high prediction performance of all models, especially the one based on nonlinear regression. These findings provide useful information about which solvent and corresponding characteristics are important for solubility studies of e.g. this increasingly useful carbon allotrope.
publishDate 2010
dc.date.none.fl_str_mv 2010-06
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/11336/247638
Goodarzi, Mohammad; Duchowicz, Pablo Román; Freitas, Matheus P.; Fernández, Francisco Marcelo; Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches; Elsevier Science; Fluid Phase Equilibria; 293; 2; 6-2010; 130-136
0378-3812
CONICET Digital
CONICET
url http://hdl.handle.net/11336/247638
identifier_str_mv Goodarzi, Mohammad; Duchowicz, Pablo Román; Freitas, Matheus P.; Fernández, Francisco Marcelo; Prediction of the Hildebrand parameter of various solvents using linear and nonlinear approaches; Elsevier Science; Fluid Phase Equilibria; 293; 2; 6-2010; 130-136
0378-3812
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378381210001007
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fluid.2010.02.025
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
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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