Modelling of adsorbate-size dependent explicit isotherms using a segregated approach to account for surface heterogeneities
S. Sharma (TU Delft - Engineering Thermodynamics)
Marcello Rigutto (Shell Global Solutions International B.V.)
Richard Baur (Shell Global Solutions International B.V.)
Umang Agarwal (Shell Global Solutions International B.V.)
Erik Zuidema (Shell Global Solutions International B.V.)
Salvador R.G. Balestra (University Pablo de Olavide)
Sofia Calero (Eindhoven University of Technology)
David Dubbeldam (Universiteit van Amsterdam)
T.J.H. Vlugt (TU Delft - Engineering Thermodynamics)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Ideal Adsorbed Solution Theory (IAST) is a common method for modelling mixture adsorption isotherms based on pure component isotherms. When the adsorbent has distinct adsorption sites, the segregated version of IAST (SIAST) provides improved adsorbed loadings compared to IAST. We have adopted the concept of SIAST and applied it to an explicit isotherm model which takes into account the different sizes of the adsorbates: the so called Segregated Explicit Isotherm (SEI). The purpose of SEI is to have an explicit adsorption model that can consider both size-effects of the co-adsorbed molecules and surface heterogeneities. In sharp contrast to IAST and SIAST, no iterative scheme is required in case of SEI, which leads to much faster simulations. A comparative study has been performed to analyse the adsorption isotherms calculated using these three methods. The adsorbed loadings predicted by SEI and SIAST are in excellent agreement with the Grand-Canonical Monte Carlo (GCMC) simulation data. The loadings estimated by IAST show considerable deviations from the GCMC data at high pressures. Breakthrough curve modelling is used to compare the effects of these three models at dynamic conditions. The explicit model (SEI) leads to the fastest simulation run time, followed by SIAST.
help_outline