Aspects of estimating parameter dependencies in a detailed chromatography model based on frontal experiments

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Bibtex

@article{bf0018f6de604b3aa0eeea0c9c669f64,
title = "Aspects of estimating parameter dependencies in a detailed chromatography model based on frontal experiments",
abstract = "A methodology for estimation of the dependency on flow rate and bead size of the axial dispersion coefficient and the film mass transfer coefficient in a detailed model for chromatographic processes is proposed. The model describes the concentration of the solute in the mobile phase and considers external/internal mass transfer resistance. The flow rate dependency of the mixing effect in the external volume is also considered. The unknown model parameters estimated are the bed void, the axial dispersion coefficient, the liquid film mass transfer coefficient, the effective diffusion coefficient and the apparent bead porosity. All the parameters in the model and the parameter dependencies were subsequently determined in three classes of experiments, i.e. the external mixing behaviour, the mobile phase behaviour and the stationary phase behaviour. The estimates are based on the sum of the least squares of the residuals between the experimental breakthrough curves and the model response. The methodology is exemplified by frontal experiments with blue dextran and bovine serum albumin in a well-defined column set-up. The results show that it is possible to estimate the unknown physical parameters in the detailed model, and their dependencies on flow rate and bead size, using the proposed methodology. (c) 2006 Elsevier Ltd. All rights reserved.",
keywords = "mass transfer resistance, computer simulation, chromatography modelling, parameter estimation, parameter dependencies",
author = "P Persson and Per-Erik Gustavsson and Guido Zacchi and Bernt Nilsson",
year = "2006",
doi = "10.1016/j.procbio.2006.03.030",
language = "English",
volume = "41",
pages = "1812--1821",
journal = "Process Biochemistry",
issn = "0032-9592",
publisher = "Elsevier",
number = "8",

}