ABSTRACT
This study involves the application of Fe-TiO2 nanocomposite for the degradation of the pharmaceutical drug ofloxacin. The novel fixed bed composite made up of foundry sand, fly ash, and clay has been applied with the coating of TiO2 for the hybrid process to take place. Further, the applications of machine learning along with optimization analysis have been carried out. The artificial neural network (ANN), a type of model for machine learning, has a wide potential in the high-speed processing of data and its implementation in the research in various fields. Due to its non-linearity, self-learning, and adaptive nature, ANN has been applied for modeling the data of the dual process of photocatalysis and photo-Fenton. For the modeling of data, ANN was employed and for the optimization of the process Box Behnken design (BBD) was used. The interactions between the various input parameters have also been evaluated. The optimization analysis showed 91% degradation at the treatment time of 94 min with H2O2 dose of 354 mg/L and the number of beads as 110. With the decrement in the time for the degradation of ofloxacin and an increase in the value of the rate constant, the in-situ dual effect has proven to be effective among the individual processes.
