Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model

Autores
Peralta, Juan Manuel; Rubiolo, Amelia Catalina; Zorrilla, Susana
Año de publicación
2007
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Immersion chilling and freezing (ICF) of foods use aqueous solutions at low temperature that are considered secondary refrigerants. These solutions contain solutes such as NaCl, CaCl2, KCl, ethanol, glucose, etc. The ICF processes have several advantages over the conventional food chilling and freezing methods. The aim of this work was to study the behavior of an excess Gibbs energy model for predicting thermodynamic properties of mixtures of electrolytes and non-electrolytes, considering the physical conditions used in immersion chilling and freezing of foods. The extended UNIQUAC model was used. Data obtained from literature for heat capacity, density and freezing point for binary aqueous solutions of NaCl, CaCl2, KCl and ethanol were compared with predicted values. Additional parameters for the density estimation were included into the model. In general, the model accuracy was satisfactory.
Fil: Peralta, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Rubiolo, Amelia Catalina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Zorrilla, Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Materia
Refrigerant Liquids;
Foods
Prediction
Properties
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:11336/25938
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy modelPeralta, Juan ManuelRubiolo, Amelia CatalinaZorrilla, SusanaRefrigerant Liquids;FoodsPredictionPropertieshttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2Immersion chilling and freezing (ICF) of foods use aqueous solutions at low temperature that are considered secondary refrigerants. These solutions contain solutes such as NaCl, CaCl2, KCl, ethanol, glucose, etc. The ICF processes have several advantages over the conventional food chilling and freezing methods. The aim of this work was to study the behavior of an excess Gibbs energy model for predicting thermodynamic properties of mixtures of electrolytes and non-electrolytes, considering the physical conditions used in immersion chilling and freezing of foods. The extended UNIQUAC model was used. Data obtained from literature for heat capacity, density and freezing point for binary aqueous solutions of NaCl, CaCl2, KCl and ethanol were compared with predicted values. Additional parameters for the density estimation were included into the model. In general, the model accuracy was satisfactory.Fil: Peralta, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Rubiolo, Amelia Catalina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Zorrilla, Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaElsevier2007-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/25938Peralta, Juan Manuel; Rubiolo, Amelia Catalina; Zorrilla, Susana; Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model; Elsevier; Journal of Food Engineering; 82; 4; 12-2007; 548-5580260-8774CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0260877407001823info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jfoodeng.2007.03.010info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:08:48Zoai:ri.conicet.gov.ar:11336/25938instacron: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 10:08:49.086CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model
title Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model
spellingShingle Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model
Peralta, Juan Manuel
Refrigerant Liquids;
Foods
Prediction
Properties
title_short Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model
title_full Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model
title_fullStr Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model
title_full_unstemmed Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model
title_sort Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model
dc.creator.none.fl_str_mv Peralta, Juan Manuel
Rubiolo, Amelia Catalina
Zorrilla, Susana
author Peralta, Juan Manuel
author_facet Peralta, Juan Manuel
Rubiolo, Amelia Catalina
Zorrilla, Susana
author_role author
author2 Rubiolo, Amelia Catalina
Zorrilla, Susana
author2_role author
author
dc.subject.none.fl_str_mv Refrigerant Liquids;
Foods
Prediction
Properties
topic Refrigerant Liquids;
Foods
Prediction
Properties
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Immersion chilling and freezing (ICF) of foods use aqueous solutions at low temperature that are considered secondary refrigerants. These solutions contain solutes such as NaCl, CaCl2, KCl, ethanol, glucose, etc. The ICF processes have several advantages over the conventional food chilling and freezing methods. The aim of this work was to study the behavior of an excess Gibbs energy model for predicting thermodynamic properties of mixtures of electrolytes and non-electrolytes, considering the physical conditions used in immersion chilling and freezing of foods. The extended UNIQUAC model was used. Data obtained from literature for heat capacity, density and freezing point for binary aqueous solutions of NaCl, CaCl2, KCl and ethanol were compared with predicted values. Additional parameters for the density estimation were included into the model. In general, the model accuracy was satisfactory.
Fil: Peralta, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Rubiolo, Amelia Catalina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Zorrilla, Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
description Immersion chilling and freezing (ICF) of foods use aqueous solutions at low temperature that are considered secondary refrigerants. These solutions contain solutes such as NaCl, CaCl2, KCl, ethanol, glucose, etc. The ICF processes have several advantages over the conventional food chilling and freezing methods. The aim of this work was to study the behavior of an excess Gibbs energy model for predicting thermodynamic properties of mixtures of electrolytes and non-electrolytes, considering the physical conditions used in immersion chilling and freezing of foods. The extended UNIQUAC model was used. Data obtained from literature for heat capacity, density and freezing point for binary aqueous solutions of NaCl, CaCl2, KCl and ethanol were compared with predicted values. Additional parameters for the density estimation were included into the model. In general, the model accuracy was satisfactory.
publishDate 2007
dc.date.none.fl_str_mv 2007-12
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/11336/25938
Peralta, Juan Manuel; Rubiolo, Amelia Catalina; Zorrilla, Susana; Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model; Elsevier; Journal of Food Engineering; 82; 4; 12-2007; 548-558
0260-8774
CONICET Digital
CONICET
url http://hdl.handle.net/11336/25938
identifier_str_mv Peralta, Juan Manuel; Rubiolo, Amelia Catalina; Zorrilla, Susana; Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model; Elsevier; Journal of Food Engineering; 82; 4; 12-2007; 548-558
0260-8774
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0260877407001823
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jfoodeng.2007.03.010
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
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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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