Metal-oxide coated Graphene oxide nano-composite for the treatment of pharmaceutical compound in photocatalytic reactor: Batch, Kinetics and Mathematical Modeling using Response Surface Methodology and Artificial Neural Network

Bhaṭṭācārya, Sandīpana; Das, Papita; Bhowal, Avijit; Majumder, Subrata Kumar

Metal-oxide coated Graphene oxide nano-composite for the treatment of pharmaceutical compound in photocatalytic reactor: Batch, Kinetics and Mathematical Modeling using Response Surface Methodology and Artificial Neural Network

2022

Bhaṭṭācārya, Sandīpana | Das, Papita | Bhowal, Avijit | Majumder, Subrata Kumar

Titanium dioxide (TiO₂) photocatalyst has gained constant interest in the treatment of wastewater because of its greater stability, lower cost, low-toxicity, high efficiency, and more reactivity under UV radiation. On the other hand, Graphene oxide (GO) possesses high electron mobility, and therefore when GO is combined with TiO₂, the photocatalytic activity of TiO₂ is increased. In this study, nano-composite was synthesized in a hydrothermal reactor using two types of TiO₂ nanoparticles (TiO₂ consisting of a mixture of rutile and anatase phase (Type 1) and bioreduced TiO₂ (Type 2)) and the efficiency of both the TiO₂-GO nanocomposite to remove the drug Carbamazepine (CBZ) was investigated. The TiO₂-GO nanocomposite with the Type 1 TiO₂ exhibited greater efficiency hence further studies were conducted with that composite. The efficiency of TiO₂-GO nanocomposite for the purpose of removing CBZ were investigated in presence of different types of incident radiation like Solar radiation, white light and three type of Ultraviolet radiation (A, B, C). The removal of the drug by TiO₂-GO composite has been optimized using response surface methodology and artificial neural network. From this study, the maximum reduction was observed was 91.2% and whereas in case of the RSM optimization study the maximum removal that was observed was 91.7%. The validation of the RSM model was done using the mathematical analysis of the model equation of RSM. Different kinetics models was also analyzed using the experimental data and it was observed that it followed pseudo-second-order kinetics. The optimization using ANN also showed a close interaction with the experimental results.

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