Predictability of chromatographic protein separations

Athalye, A.M.; Gibbs, S. Julian; Lightfoot, E. N.

doi:10.1016/0021-9673(92)80007-h

Cited by 55 publications

(3 citation statements)

References 49 publications

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“…While X-ray-computed tomography has been used to monitor displacements in rock (Vinegar, 19861, no detailed studies concerning fingering have been performed with this method. On the other hand, magnetic resonance imaging (MRI) has been used to visualize viscous fingering in solutions (Pearl et al, 1993), Hele-Shaw cells (Davies et al, 1992), and in conventional packed columns (Athalye et al, 1991;Plante et al, 1994). Recent magnetic-resonance imaging measurements in packed columns have also provided the three-dimensional visualization of viscous fingering in porous media for the first time (Fernandez et al, 1995).…”

Section: Aiche Journalmentioning

confidence: 98%

Chemical imaging of multicomponent viscous fingering in chromatography

1997

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Section: Aiche Journalmentioning

confidence: 98%

Chemical imaging of multicomponent viscous fingering in chromatography

1997

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“…Other methods to evaluate tortuosity in a direct manner are based on the determination of the ratio of the value of the diffusion coefficient of a probe in bulk to its apparent value in the porous network ( D eff = ε D 0 /τ). The diffusion coefficients may be derived from direct transport data (for example, by analyzing the shape of chromatographic peaks, by diffusivity measurements with Wicke Kallenbach cells), or from NMR applied to various probes …”

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confidence: 99%

Tortuosity of Porous Particles

2007

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Tortuosity is often used as an adjustable parameter in models of transfer properties through porous media. This parameter, not reducible to classical measured microstructural parameters like specific surface area, porosity, or pore size distribution, reflects the efficiency of percolation paths, which is linked to the topology of the material. The measurement of the effective conductivity of a bed of particles saturated with an electrolyte is a simple way to evaluate tortuosity. Nevertheless, it received only little attention because of the real difficulties in both getting reliable results and interpreting data. Notably, the discrimination between the contribution of interparticle and intraparticle porosities to the tortuosity is not resolved. To our knowledge, there is no model able to fit the experimental data of the tortuosity of a suspension, and a fortiori of a particle bed, in the whole porosity range. Only empirical expressions have been proposed, but they do not allow deriving intratortuosity of a porous particle. For a dilute system, Maxwell's equation predicts the effective conductivity of suspensions of spherical particles as a function of the bulk electrolyte conductivity and of particle conductivity. The intraparticle tortuosity can be derived from the particle conductivity obtained from the Maxwell equation applied to data at infinite dilution of particles. Then, by assuming that the Maxwell equation is a first-order approximation of the conductivity as a function of porosity, we propose an explicit relation of the tortuosity tau of a suspension of porous particles, obtained by conductivity measurement, as tau = tau(epsilon, epsilon(p), tau(p)), where epsilon is the total porosity of the suspension, tau(p) is the intraparticle tortuosity, and epsilon(p) is the particle porosity. This relationship fits the experimental data in the whole porosity range and can be used to determine tau(p) from an experiment at only one porosity. Finally, the obtained values of tau(p) for a set of porous particles used in chromatography are discussed and compared to the data available in the literature.

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“…Since the CI values are lower than the parameter values reported in Table , the parameter identification can be considered accurate given the excellent fit indices. The coefficients for external film mass transfer and axial dispersion could be estimated with a different correlation than the one used, for example, by Athalye et al, Delgado, and Valdés-Solís et al to improve the agreement between measurements and predictions. Despite this discrepancy, the estimated coefficients reported in Table for different gas flow rates are in line with the magnitudes commonly reported in the literature. , Water vapor molecules are adsorbed in the pores (meso and macro) by forming hydrogen bonds between the adsorbed molecules and the adsorbent surface.…”

Section: Results and Discussionmentioning

confidence: 99%

Modeling of Water Vapor Adsorption and Desorption in an Industrial Medical Air Dryer

Cardenas

Farrusseng

Daniel

2023

Ind. Eng. Chem. Res.

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This study presents the development of a dynamic multiscale model to simulate the adsorption and desorption processes in a fixed bed for medical air drying. The model includes equations of mass balance, thermodynamics, hydrodynamics, and adsorption/desorption kinetics. The temperature-dependent Toth–Aranovich–Donohue equation is used to approximate the equilibrium relationship between water vapor and activated alumina (hopcalite). Measurements of the breakthrough curve at different water vapor concentrations and gas flow rates can be used to determine kinetic resistances such as axial dispersion, external film mass transfer, pore diffusion, and internal mass transfer and thus to determine the limiting resistance of the process. The model predictions agree well with the experimental results, which are supported by performance indices and confirmed by additional breakthrough curves for validation. The validated model proves effective in predicting water vapor adsorption and desorption breakthrough curves on adsorbents considering concentration, flow rate, and temperature and serves as a valuable tool for the development and optimization of commercial PSA columns with multiple adsorption layers.

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Predictability of chromatographic protein separations

Cited by 55 publications

References 49 publications

Chemical imaging of multicomponent viscous fingering in chromatography

Chemical imaging of multicomponent viscous fingering in chromatography

Tortuosity of Porous Particles

Modeling of Water Vapor Adsorption and Desorption in an Industrial Medical Air Dryer

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