Random surface statistical associating fluid theory: Adsorption of n-alkanes on rough surface

Adsorption properties of chain fluids are of interest from both fundamental and industrial points of view. Density Functional Theory (DFT) based models are among the most appropriate techniques allowing to describe surface phenomena. At the same time, Statistical Associating Fluid Theory (SAFT) successfully describes bulk pressure-volume-temperature properties of chain-fluids. In this study, we have developed a novel version of the SAFT-DFT approach entitled Random Surface (RS)-SAFT which is capable of describing adsorption of short hydrocarbons on geometrically rough surfaces. A major advantage of our theory is the application to adsorption on natural rough surfaces with normal and lateral heterogeneity. For this reason, we have proposed a workflow where the surface of a real solid sample is analyzed using a theoretical approach developed in our previous work [T. Aslyamov and A. Khlyupin, J. Chem. Phys. 147, 154703 (2017)] and experimentally by means of low temperature adsorption isotherm measurements for simple fluids. As a result, RS-SAFT can predict adsorption properties of chain fluids taking into account the geometry of the surface sample under consideration. In order to test our workflow, we have investigated hexane adsorption on carbon black with the initially unknown geometry. Theoretical predictions for hexane adsorption at 303 K and 293 K fit corresponding experimental data well. Published under license by AIP Publishing.