Prediction of the freezing point of multicomponent liquid refrigerant solutions

Autores
Tello Alonso, Héctor Alfredo; Peralta, Juan Manuel; Rubiolo, Amelia Catalina; Zorrilla, Susana
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The freezing point is one of the most critical properties required to complete the mathematical formulation related to the transport phenomena involved in the immersion chilling and freezing (ICF) of foods. Unfortunately, data for ternary and higher order systems are scarce. The aim of this work was to verify the validity of an excess Gibbs energy model for predicting the freezing point of multicomponent mixtures of electrolytes and non-electrolytes, considering the processing conditions used in immersion chilling and freezing of foods. The extended UNIQUAC model was used. Data obtained from literature corresponding to freezing points of the ternary systems: NaCl–KCl–H2O, NaCl–CaCl2–H2O, NaCl– MgCl2–H2O and NaCl–EtOH–H2O, were compared with predicted values. The model accuracy was satisfactory, the highest absolute deviation being smaller than 1.71 ºC for the 378 data compared.
Fil: Tello Alonso, Héctor Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
Fil: Peralta, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
Fil: Rubiolo, Amelia Catalina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
Fil: Zorrilla, Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
Materia
Freezing Point
Multicomponent Solutions
Refrigerant Liquids
Extended Uniquac
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/13355
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Prediction of the freezing point of multicomponent liquid refrigerant solutionsTello Alonso, Héctor AlfredoPeralta, Juan ManuelRubiolo, Amelia CatalinaZorrilla, SusanaFreezing PointMulticomponent SolutionsRefrigerant LiquidsExtended Uniquachttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2The freezing point is one of the most critical properties required to complete the mathematical formulation related to the transport phenomena involved in the immersion chilling and freezing (ICF) of foods. Unfortunately, data for ternary and higher order systems are scarce. The aim of this work was to verify the validity of an excess Gibbs energy model for predicting the freezing point of multicomponent mixtures of electrolytes and non-electrolytes, considering the processing conditions used in immersion chilling and freezing of foods. The extended UNIQUAC model was used. Data obtained from literature corresponding to freezing points of the ternary systems: NaCl–KCl–H2O, NaCl–CaCl2–H2O, NaCl– MgCl2–H2O and NaCl–EtOH–H2O, were compared with predicted values. The model accuracy was satisfactory, the highest absolute deviation being smaller than 1.71 ºC for the 378 data compared.Fil: Tello Alonso, Héctor Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Peralta, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Rubiolo, Amelia Catalina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Zorrilla, Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaElsevier2011-05info: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/11336/13355Tello Alonso, Héctor Alfredo; Peralta, Juan Manuel; Rubiolo, Amelia Catalina; Zorrilla, Susana; Prediction of the freezing point of multicomponent liquid refrigerant solutions; Elsevier; Journal Of Food Engineering; 104; 1; 5-2011; 143-1480260-8774enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S026087741000587Xinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.jfoodeng.2010.12.006info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T12:00:06Zoai:ri.conicet.gov.ar:11336/13355instacron: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:34982025-10-22 12:00:07.118CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Prediction of the freezing point of multicomponent liquid refrigerant solutions
title Prediction of the freezing point of multicomponent liquid refrigerant solutions
spellingShingle Prediction of the freezing point of multicomponent liquid refrigerant solutions
Tello Alonso, Héctor Alfredo
Freezing Point
Multicomponent Solutions
Refrigerant Liquids
Extended Uniquac
title_short Prediction of the freezing point of multicomponent liquid refrigerant solutions
title_full Prediction of the freezing point of multicomponent liquid refrigerant solutions
title_fullStr Prediction of the freezing point of multicomponent liquid refrigerant solutions
title_full_unstemmed Prediction of the freezing point of multicomponent liquid refrigerant solutions
title_sort Prediction of the freezing point of multicomponent liquid refrigerant solutions
dc.creator.none.fl_str_mv Tello Alonso, Héctor Alfredo
Peralta, Juan Manuel
Rubiolo, Amelia Catalina
Zorrilla, Susana
author Tello Alonso, Héctor Alfredo
author_facet Tello Alonso, Héctor Alfredo
Peralta, Juan Manuel
Rubiolo, Amelia Catalina
Zorrilla, Susana
author_role author
author2 Peralta, Juan Manuel
Rubiolo, Amelia Catalina
Zorrilla, Susana
author2_role author
author
author
dc.subject.none.fl_str_mv Freezing Point
Multicomponent Solutions
Refrigerant Liquids
Extended Uniquac
topic Freezing Point
Multicomponent Solutions
Refrigerant Liquids
Extended Uniquac
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The freezing point is one of the most critical properties required to complete the mathematical formulation related to the transport phenomena involved in the immersion chilling and freezing (ICF) of foods. Unfortunately, data for ternary and higher order systems are scarce. The aim of this work was to verify the validity of an excess Gibbs energy model for predicting the freezing point of multicomponent mixtures of electrolytes and non-electrolytes, considering the processing conditions used in immersion chilling and freezing of foods. The extended UNIQUAC model was used. Data obtained from literature corresponding to freezing points of the ternary systems: NaCl–KCl–H2O, NaCl–CaCl2–H2O, NaCl– MgCl2–H2O and NaCl–EtOH–H2O, were compared with predicted values. The model accuracy was satisfactory, the highest absolute deviation being smaller than 1.71 ºC for the 378 data compared.
Fil: Tello Alonso, Héctor Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
Fil: Peralta, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
Fil: Rubiolo, Amelia Catalina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
Fil: Zorrilla, Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
description The freezing point is one of the most critical properties required to complete the mathematical formulation related to the transport phenomena involved in the immersion chilling and freezing (ICF) of foods. Unfortunately, data for ternary and higher order systems are scarce. The aim of this work was to verify the validity of an excess Gibbs energy model for predicting the freezing point of multicomponent mixtures of electrolytes and non-electrolytes, considering the processing conditions used in immersion chilling and freezing of foods. The extended UNIQUAC model was used. Data obtained from literature corresponding to freezing points of the ternary systems: NaCl–KCl–H2O, NaCl–CaCl2–H2O, NaCl– MgCl2–H2O and NaCl–EtOH–H2O, were compared with predicted values. The model accuracy was satisfactory, the highest absolute deviation being smaller than 1.71 ºC for the 378 data compared.
publishDate 2011
dc.date.none.fl_str_mv 2011-05
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/11336/13355
Tello Alonso, Héctor Alfredo; Peralta, Juan Manuel; Rubiolo, Amelia Catalina; Zorrilla, Susana; Prediction of the freezing point of multicomponent liquid refrigerant solutions; Elsevier; Journal Of Food Engineering; 104; 1; 5-2011; 143-148
0260-8774
url http://hdl.handle.net/11336/13355
identifier_str_mv Tello Alonso, Héctor Alfredo; Peralta, Juan Manuel; Rubiolo, Amelia Catalina; Zorrilla, Susana; Prediction of the freezing point of multicomponent liquid refrigerant solutions; Elsevier; Journal Of Food Engineering; 104; 1; 5-2011; 143-148
0260-8774
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/S026087741000587X
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jfoodeng.2010.12.006
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/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 12.982451

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