Modelling of adsorbate-size dependent explicit isotherms using a segregated approach to account for surface heterogeneities

Open Access
Authors
  • S. Sharma
  • M.S. Rigutto
  • R. Baur
  • U. Agarwal
Publication date 2023
Journal Molecular Physics
Article number e2183721
Volume | Issue number 121 | 19-20
Number of pages 18
Organisations
  • Faculty of Science (FNWI) - Van 't Hoff Institute for Molecular Sciences (HIMS)
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.

Document type Article
Note In special issue: Thermodynamics 2022 Conference.
Language English
Related dataset Sample simulation input file and data sets for the article: "Modelling of adsorbate-size dependent explicit isotherms using a segregated approach to account for surface heterogeneities."
Published at https://doi.org/10.1080/00268976.2023.2183721
Other links https://www.scopus.com/pages/publications/85150786079
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