Effect of surface roughness on partition of ionic liquids in nanopores by a perturbed-chain SAFT density functional theoryShow others and affiliations
2022 (English)In: Journal of Chemical Physics, ISSN 0021-9606, E-ISSN 1089-7690, Vol. 157, no 1, article id 014701Article in journal (Refereed) Published
Abstract [en]
In this work, the distribution and partition behavior of ionic liquids (ILs) in nanopores with rough surfaces are investigated by a two-dimensional (2D) classical density functional theory model. The model is consistent with the equation of state that combines the perturbed-chain statistical associating fluid theory and the mean spherical approximation theory for bulk fluids. Its performance is verified by comparing the theoretical predictions with the results from molecular simulations. The fast Fourier transform and a hybrid iteration method of Picard iteration and Anderson mixing are used to efficiently obtain the solution of density profile for the sizable 2D system. The molecular parameters for IL-ions are obtained by fitting model predictions to experimental densities of bulk ILs. The model is applied to study the structure and partition of the ILs in nanopores. The results show that the peak of the density profile of counterions near a rough surface is much higher than that near a smooth surface. The adsorption of counterions and removal of co-ions are enhanced by surface roughness. Thus, the nanopore with a rough surface can store more charge. At low absolute surface potential, the partition coefficient for ions on rough surfaces is lower than that on smooth surfaces. At high absolute surface potential, increasing surface roughness leads to an increase in the partition coefficient for counterions and a decrease in the partition coefficient for co-ions.
Place, publisher, year, edition, pages
American Institute of Physics (AIP), 2022. Vol. 157, no 1, article id 014701
Keywords [en]
Ionic liquid, rough surface, classical density functional theory, PC-SAFT, electrical double layer
National Category
Energy Engineering
Research subject
Energy Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-91783DOI: 10.1063/5.0098924ISI: 000866542900019PubMedID: 35803823Scopus ID: 2-s2.0-85133534057OAI: oai:DiVA.org:ltu-91783DiVA, id: diva2:1674620
Note
Validerad;2022;Nivå 2;2022-07-14 (joosat);
Funder: National Natural Science Foundation of China (grant no. 21606096)
2022-06-222022-06-222022-12-02Bibliographically approved