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dc.contributor.authorKhattab, IS
dc.contributor.authorBandarkar, F
dc.contributor.authorFakhree, MAA
dc.contributor.authorJouyban, A
dc.date.accessioned2018-08-26T08:05:01Z
dc.date.available2018-08-26T08:05:01Z
dc.date.issued2012
dc.identifier.urihttp://dspace.tbzmed.ac.ir:8080/xmlui/handle/123456789/49722
dc.description.abstractDensity, viscosity, and surface tension of liquids are important physicochemical properties which affect mass and heat transfer in solutions. The density, viscosity, and surface tension of binary mixture of water+ethanol at 293, 298, 303, 308, 313, 318, and 323 K are reported and compared with the available literature data. The findings of these comparisons show how the measured data are reproducible from different laboratories. The molar volume of water+ethanol mixtures are also calculated using measured density values. The Jouyban-Acree model was used for mathematical correlation of the data. The relative deviation (RD) was used as an error criterion and the RD values for correlation of density, viscosity, surface tension and molar volume data at investigated temperatures are 0.1 +/- 0.1%, 10.4 +/- 9.5%, 4.2 +/- 3.6%, and 0.3 +/- 0.3%, respectively. The corresponding RDs for the predicted properties after training using the experimental data at 298 K are 0.2 +/- 0.2%, 14.1 +/- 15.8%, 5.4 +/- 4.6% and 0.4 +/- 0.3%, respectively, for density, viscosity, surface tension, and molar volume data. This study shows that the Jouyban-Acree model can correlate/predict physicochemical properties of the mixtures of solvents at different temperatures with acceptable error in calculation.
dc.language.isoEnglish
dc.relation.ispartofKOREAN JOURNAL OF CHEMICAL ENGINEERING
dc.subjectDensity
dc.subjectViscosity
dc.subjectSurface Tension
dc.subjectWater plus Ethanol
dc.subjectBinary Mixture
dc.subjectJouyban-Acree Model
dc.titleDensity, viscosity, and surface tension of water plus ethanol mixtures from 293 to 323 K
dc.typeArticle
dc.citation.volume29
dc.citation.issue6
dc.citation.spage812
dc.citation.epage817
dc.citation.indexWeb of science
dc.identifier.DOIhttps://doi.org/10.1007/s11814-011-0239-6


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