Abstract
A novel mathematical method for parameter estimation is proposed and used to estimate in the Laplace transform domain the values of the parameters that characterize the mechanisms of intraparticle diffusion and convection in spherical perfusive or purely diffusive adsorbent particles with a monodisperse or with a bidisperse porous structure when the adsorbent particles are packed in a column. The parameter estimation method in the Laplace transform domain presented in this work is significantly simpler, easier to use and dramatically faster than the conventional parameter estimation procedure in the time domain, which requires the repeated numerical solution of the partial differential equations that describe the dynamic behaviour of the adsorption of an adsorbate in a column. Furthermore, since the value(s) of the parameter(s) that characterize the diffusional mass transfer mechanism(s) in the porous adsorbent particles is independent of the mode of operation, then the value(s) of the effective pore diffusion coefficient(s) determined by the mathematical method presented in this work could be used to describe the diffusional mass transfer rate of the adsorbate in operational modes other (finite bath (batch) operation, periodic countercurrent column operation, fluidized bed operation) than fixed-bed column operation.
Recommended Citation
G. A. Heeter and A. I. Liapis, "Affinity Adsorption of Adsorbates into Spherical Monodisperse and Bidisperse Porous Perfusive and Purely Diffusive Adsorbent Particles Packed in a Column. Parameter Estimation in the Laplace Transform Domain," Journal of Chromatography A, vol. 760, no. 1, pp. 55 - 69, Elsevier, Jan 1997.
The definitive version is available at https://doi.org/10.1016/S0021-9673(96)00704-2
Department(s)
Chemical and Biochemical Engineering
Keywords and Phrases
adsorbents; adsorption; affinity adsorbents; Laplace transform domain; mathematical models; simulation
International Standard Serial Number (ISSN)
0021-9673
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Elsevier, All rights reserved.
Publication Date
24 Jan 1997
