A model for dynamic extraction using a supercritical fluid

Bartle, Keith D.; Clifford, Anthony A.; Hawthorne, Steven B.; Langenfeld, John J.; Miller, David J.; Robinson, Robert E.

doi:10.1016/0896-8446(90)90039-o

Cited by 192 publications

(76 citation statements)

References 7 publications

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“…Their advantage is their simplicity, but these models are not adequate for scaling up. Other authors have proposed models based on analogies to heat and mass transfer (Bartle et al, 1990;Reverchon et al, 1993;Esquivel et al, 1999;Barroso et al, 2011). The single sphere model assumes that the solute is extracted from a particulate bed composed of porous and inert spheres having the same size; the model showed that intraparticle mass transfer was the controlling factor for the process and that mass transfer resistance on the fluid is zero.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling of supercritical fluid extraction of oil from canola and sesame seeds

Honarvar¹,

Sajadian

Khorram

et al. 2013

Braz. J. Chem. Eng.

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-Mathematical modeling of supercritical fluid extraction of oil from canola and sesame seeds with a two-phase model was performed in this work. A model based on differential mass balance was used to correlate the experimental data. Different adsorption isotherm models (Henry, Freundlich and Brunauer, Emmet and Teller (BET)) were used to describe the equilibrium state. Three model parameters such as effective diffusivity (D eff ), mass transfer coefficient (K f ) and axial dispersion coefficient (D ax ) of the bed were used as fitting parameters. The experimental data for yields were obtained at pressures of 10-20 MPa, temperatures of 313-333 K and solvent flow rates of 2-4 g/min. From the results, a nonlinear adsorption isotherm exhibited better agreement with experimental data of yield than a linear model in the range of studied conditions.

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Section: Introductionmentioning

confidence: 99%

Mathematical modeling of supercritical fluid extraction of oil from canola and sesame seeds

Honarvar¹,

Sajadian

Khorram

et al. 2013

Braz. J. Chem. Eng.

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“…The HBM (Eq. 3) [31] and the DLT (Eqs. 4-5) [32] which both considers the diffusivity inside a particle, were also estimated as single calibration models.…”

Section: Single Calibration Modelsmentioning

confidence: 99%

Method development in inverse modeling applied to supercritical fluid extraction of lipids

Abrahamsson

Andersson

Nilsson

et al. 2016

The Journal of Supercritical Fluids

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Modeling of the supercritical fluid extraction of solid materials is an important aspect in order to understand and predict the process. A comparison of two empirical models, two semi-empirical models and two mechanistic models is performed using calibration of single experiments. It is concluded that the best fit is obtained using a simple empirical expression. Furthermore, single calibrations did not generate reliable parameters with physical meaning and a methodology is proposed for inverse modeling with complete calibration using several experiments. The experimental dataset contained 29 extractions of lipids from crushed linseeds with varying temperatures, pressures and flow rates.A general rate model and a proposed extension of the hot ball model were evaluated for this purpose. The methodology includes data acquisition, model structure estimation, model calibration and a cross-validation. In general, it was found that the solubility model of Sovová outperformed the other evaluated correlations, and for the general rate model the Toth partition isotherm was also found in the top model structures. However, no generalization could be made regarding the correlations describing the Nernst diffusion layer and diffusivity. AbbreviationsBPR, back-pressure regulator; CV, cross-validation; DLT, diffusion-layer theory; DOE, design of experiments; EHBM, extended hot ball model; ELSD, evaporative light scattering detector; GA, genetic algorithm; GRM, general rate model; HBM, hot ball model; LHS, Latin hypercube sampling; ODE, ordinary differential equation; PSO, particle swarm optimization; RMSE, root mean square error; RMSEC, root mean square error of calibration; RMSECV, root mean square error of cross-validation; scCO2, supercritical carbon dioxide; SFE, supercritical fluid extraction

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“…This gives way to a transition region in which the removal of lipid becomes rate limiting, followed by an asymptotic approach to the final lipid content with passage of the extraction fluid (SC-CO2). Such extraction curves have been modelled by several investigators and generalized in a "hot ball" kinetic model by Bartle et al (1990).…”

Section: Principles For the Analytical Sfe Of Lipidsmentioning

confidence: 99%

Supercritical fluid extraction: Present status and prospects

King¹

2002

Grasas y Aceites

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A model for dynamic extraction using a supercritical fluid

Cited by 192 publications

References 7 publications

Mathematical modeling of supercritical fluid extraction of oil from canola and sesame seeds

Mathematical modeling of supercritical fluid extraction of oil from canola and sesame seeds

Method development in inverse modeling applied to supercritical fluid extraction of lipids

Supercritical fluid extraction: Present status and prospects

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