Graphene-supported ordered mesoporous composites used for environmental remediation: A review

•Graphene-supported ordered mesoporous composites used in environmental remediation.•Review of recent developments in synthesis and characterization of the composites.•Summary on adsorption equilibrium isotherms, removal kinetics and thermodynamics.•Mainstream AI techniques are discussed for pollutants removal process optimization. Environmental pollutants have aroused extensive concerns worldwide, which mainly include heavy metals, nutrients and persistent organic pollutants. Therefore, it is highly essential that multifunctional composites as an adsorbent are developed for decontaminating these pollutants. Graphene is an allotrope of carbon consisting of a single layer of carbon atoms arranged in a hexagonal lattice, which is regarded as semimetal because its conduction and valence bands touch at the Dirac point (zero bandgap material). Ordered mesoporous materials have been applied in many areas due to their large specific surface area, uniform adjustable mesoporous diameter, uniform mass transfer and high adsorption capacity. As an attractive 2D material with remarkable physical and chemical properties, graphene oxide (GO) composites have been widely used in this field. Graphene oxide-ordered mesoporous silica materials showed a highly efficient adsorption of heavy metals from wastewater and the removal efficiencies for As, Cd, Cr, Hg, and Pb reached 97.7%, 96.9%, 96.0%, 98.5%, and 78.7%, respectively. Graphene-supported ordered mesoporous metal oxide composites have the properties of metal oxide and the characteristics of regular pore structure and high crystallinity, which have become a hotspot in the field of new materials. Equilibrium isotherms, removal kinetics and thermodynamics are critical for understanding the pollutants removal processes. The experimental design and mainstream artificial intelligence techniques (e.g. self-organizing mapping neural network, recurrent neural network and radial basis function neural networks) can contribute to modeling and optimization of the complex removal processes. In this paper, we overview the recent developments in synthesis, characterization and properties of ordered mesoporous materials with the emphasis on their applications in environmental remediation.