Calculation of solid-liquid equilibrium and crystallization paths for melt crystallization processes

Slaughter, D. W.; Doherty, Michael F.

doi:10.1016/0009-2509(95)00010-3

Cited by 48 publications

(28 citation statements)

References 46 publications

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“…(24) and (25) assumes that the activity coefficients of both components are equal to one. The assumption that ortho-and para-dichlorobenzene results in an ideal mixture was verified by comparing the experimental eutectic temperature reported in the International Critical Tables with the calculated eutectic temperature.…”

Section: Solid-layer Growth From Melt Crystallization 583mentioning

confidence: 99%

A Combined Analytic and Numerical Method for Predicting the Solid-Layer Growth From Melt Crystallization

Dai

Fen

Nassar

et al. 2003

Numerical Heat Transfer, Part A: Applications

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The kinetics of crystallization limit the rate in which crystal growth can occur without incorporation of undesired impurity. If the rate of heat transfer exceeds the mass transfer rate of the impurity, the impurity can solidify, contaminating the product. One would like to specify a rate of crystallization and determine the temperature profile of the crystallizer wall that would achieve this result. This is an inverse problem that has not been solved in the previous crystallizer models. A combined analytic and numerical method for solving the inverse problem is given in this article. The method is illustrated by an example.

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Section: Solid-layer Growth From Melt Crystallization 583mentioning

confidence: 99%

A Combined Analytic and Numerical Method for Predicting the Solid-Layer Growth From Melt Crystallization

Dai

Fen

Nassar

et al. 2003

Numerical Heat Transfer, Part A: Applications

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“…There are mainly three solid-liquid equilibrium models that have been used in the current literature for fatty mixtures: Bragg-Williams approximation [23], Slaughter and Doherty model [24] and Margules-isomorphism correlations [15,19]. The Bragg-Williams approximation assumes non-ideal mixing in both liquid and solid phases and attributes the non-ideality of mixing to the enthalpy term of the free energy of mixing, supposing that the entropy term is like in the ideal mixing.…”

Section: Background On Fat Thermodynamic Equilibrium Modelingmentioning

confidence: 99%

“…SFC computation until 1990 was mainly empirical, partially based on curve fitting [15]. After 1990, the literature mostly published experimental studies [16][17][18] and some equilibrium modeling issues [19][20][21][22]. Won [20] used iterative methods to compute softening and clear points with no considerations about computing activity coefficients on solid and liquid phases and applied it to cocoa butter.…”

Section: Background On Fat Thermodynamic Equilibrium Modelingmentioning

confidence: 99%

Phase Equilibrium and Optimization Tools: Application for Enhanced Structured Lipids for Foods

Santos

Roux

Gerbaud

2010

J Americ Oil Chem Soc

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Solid-liquid phase equilibrium modeling of triacylglycerol mixtures is essential for lipids design. Considering the a polymorphism and liquid phase as ideal, the Margules 2-suffix excess Gibbs energy model with predictive binary parameter correlations describes the non ideal b and b 0 solid polymorphs. Solving by direct optimization of the Gibbs free energy enables one to predict from a bulk mixture composition the phases composition at a given temperature and thus the SFC curve, the melting profile and the Differential Scanning Calorimetry (DSC) curve that are related to end-user lipid properties. Phase diagram, SFC and DSC curve experimental data are qualitatively and quantitatively well predicted for the binary mixture 1,3-dipalmitoyl-2-oleoyl-sn-glycerol (POP) and 1,2,3-tripalmitoyl-sn-glycerol (PPP), the ternary mixture 1,3-dimyristoyl-2-palmitoyl-snglycerol (MPM), 1,2-distearoyl-3-oleoyl-sn-glycerol (SSO) and 1,2,3-trioleoyl-sn-glycerol (OOO), for palm oil and cocoa butter. Then, addition to palm oil of Medium-LongMedium type structured lipids is evaluated, using caprylic acid as medium chain and long chain fatty acids (EPAeicosapentaenoic acid, DHA-docosahexaenoic acid, c-linolenic-octadecatrienoic acid and AA-arachidonic acid), as sn-2 substitutes. EPA, DHA and AA increase the melting range on both the fusion and crystallization side. c-linolenic shifts the melting range upwards. This predictive tool is useful for the pre-screening of lipids matching desired properties set a priori.

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“…The solute and the solvent are fully miscible only in the liquid phase above the transition temperature, while F 8 H 16 separates at lower temperatures, and does not interact with the liquid solvent [26]. For this reason we can approximate x s 1 c s 1 % 1, and therefore [27]:…”

Section: Activity Coefficientsmentioning

confidence: 99%

Gels from a semifluorinated n-alkane in fluorinated solvents as a probe for intermolecular interactions

Tattini

Nostro

Scalise

et al. 2009

Journal of Colloid and Interface Science

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Calculation of solid-liquid equilibrium and crystallization paths for melt crystallization processes

Cited by 48 publications

References 46 publications

A Combined Analytic and Numerical Method for Predicting the Solid-Layer Growth From Melt Crystallization

A Combined Analytic and Numerical Method for Predicting the Solid-Layer Growth From Melt Crystallization

Phase Equilibrium and Optimization Tools: Application for Enhanced Structured Lipids for Foods

Gels from a semifluorinated n-alkane in fluorinated solvents as a probe for intermolecular interactions

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