Adsorption of phenolic pollutants on graphene oxide: steric and energetic interpretations via advanced approach

A statistical physics-based approach was used to study the adsorption of phenol and 2,4-dichlorophenol (2,4-DCP) on graphene oxide (GO). A multilayer adsorption model developed by statistical physics was applied to elucidate the adsorption mechanism at the molecular scale, thereby indicating the limitations of classical models. The model was parameterized using experimental adsorption data collected at various temperatures, enabling the estimation of model parameters corresponding to different physicochemical properties such as the number of phenolic molecules adsorbed per active site, the density of active sites on the GO surface, the adsorption capacity, and the types of interactions involved in the process. Based on the modelling results, it was retrieved that the adsorption of phenol and 2,4-DCP on GO occurs via a multimolecular process governed by low degree of aggregation phenomena. The maximum adsorption capacities for phenol and 2,4-DCP were found to be 445.8 mg/g and 111.1 mg/g, respectively. The estimation of the adsorption energy highlights that the process is a physisorption. The explanation of positional entropy provided additional insights regarding the arrangement of phenol and 2,4-DCP molecules during adsorption on GO surface. Overall, this study provides an enhanced theoretical interpretation of the adsorption mechanisms at molecular level of two phenolic pollutants on GO surface, highlighting the superior ability of a statistical physics modeling in elucidating adsorption phenomena, compared to classical adsorption models.