Integral approach of treatment of phenolic wastewater using nano-metal coated graphene oxide in combination with advanced oxidation

Abstract Wastewater treatment is one of the highlighted environmental concerns today due to depletion in the underground water table and its serious impact on aquatic life. High organic loading, antibacterial, and phytotoxicity of phenolic compounds in wastewater make them resistant to biological degradation. Therefore, the main aim of the research is to investigate the degradation of phenol by photocatalysis, through a series of Graphene Oxide (GO) coated nanocomposites such as GO-TiO2 (GOT) and Graphene-Iron (GOI). The performance of hybrid composite was investigated in a batch system under different loading conditions such as pH, adsorbent dose, and phenol concentration. Photocatalytic degradation results in complete declination of pollutants into harmless end products. The phenol adsorption by GOT was best and was pH dependant. The optimum condition for 97.78% removal by GOT was achieved at an adsorbent dose of (0.210 g /L), pH (5.5), phenol concentration (10 mg/L), and contact time 2 h. But the major drawback of GOT is recovery and separation, to overcome this GOI was synthesized. GOI represents lesser adsorption capability of (53.89%) because of the loading of iron on GO sheet. Langmuir and Freundlich both isotherm models represented well fit for the phenol adsorption batch data. However, the Langmuir isotherm (R2=0.999) shows a better fit over the Freundlich model (R2=0.964). Further in the study, the photocatalytic degradation by GOT were optimized using response surface methodology (RSM) and Artificial Neural Network (ANN) analysis.