Synthesis and characterization of g-CN/rGO photocatalyst for waste water Ciprofloxacin; Generalized Regression Neural Network and Surface Response Methodology study

In this study, a nanocomposite photocatalyst called graphitic carbon nitride-reduced graphene oxide (g-CN/rGO) was synthesized, characterized and applied for the photocatalytic degradation of ciprofloxacin (CP), which serves as a representative contaminant, under visible light illumination [1]. The experiment considered different conditions such as initial CP concentration, irradiation time, photocatalyst dose, and pH [2]. The obtained results were then modeled using response surface methodology (RSM) and generalized regression neural network (GRNN) approaches to provide a more accurate description of the process behavior. To verify the main active species, free radical trapping experiments were conducted. Additionally, the LC-Mass technique was utilized to detect the intermediates formed during the photodegradation process. When comparing the photocatalytic performance of g-CN/rGO with other recently developed counterparts, it becomes evident that it holds promise as an alternative for remediating these types of pollutants in water bodies. The excellent performance of the g-CN/rGO photocatalyst suggests its potential for large-scale photodegradation of persistent organic pollutants in wastewater treatment plants [3].