Effect of surface roughness on partition of ionic liquids in nanopores by a perturbed-chain SAFT density functional theory.

Abstract

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.