Emerging iron-based mesoporous materials for adsorptive removal of pollutants: Mechanism, optimization, challenges, and future perspective

Abstract

Iron-based materials (IBMs) have shown promise as adsorbents due to their unique physicochemical properties. This review provides an overview of the different types of IBMs, their synthesis methods, and their properties. Results found in the adsorption of emerging contaminants to a wide range of IBMs are discussed. The IBMs used were evaluated in terms of their maximum uptake capacity, with special consideration given to environmental conditions such as contact time, solution pH, initial pollutant concentration, etc. The adsorption mechanisms of pollutants are discussed taking into account the results of kinetic, isotherm, thermodynamic studies, surface complexation modelling (SCM), and available spectroscopic data. A current overview of molecular modeling and simulation studies related to density functional theory (DFT), surface response methodology (RSM), and artificial neural network (ANN) is presented. In addition, the reusability and suitability of IBMs in real wastewater treatment is shown. The review concludes with the strengths and weaknesses of current research and suggests ideas for future research that will improve our ability to remove contaminants from real wastewater streams.

Keywords: Adsorption; Artificial neural network; Density functional theory; Emerging contaminants; Environment; Iron oxide; Pollutants; Response surface methodology; Wastewater.