Graphene oxide for the treatment of ranitidine containing solution: Optimum sorption kinetics by linear and non linear methods and simulation using artificial neural network

• Graphene oxide was synthesized using ultrasonication power and used for removal of ranitidine.
• The equilibrium kinetics was analyzed using pseudo-second order kinetic and ANN simulation techniques.
• Pseudo second order Kinetic parameters were analyzed using linear and non-linear models.
• Non-linear model better represent the experimental data than linear kinetic models.
• The ANN simulation process shows satisfactory agreement with the experimental results.

In this present study, Graphene oxide nanoplateletes were synthesized and used as nano-adsorbent for the treatment of ranitidine present in synthetic wastewater. 99% ranitidine was removed using synthesized Graphene oxide. Comparative analysis was performed between linear and non-linear kinetic model for estimating the kinetic parameters. Four linear pseudo-second-order kinetic models were analyzed with non-linear kinetic model. Error analysis between non-linear and linear model were studied for determining the best-fitting model. It was observed that non-linear method proved to be a better alternative than the linear kinetic model for obtaining the important kinetic parameters which can be used further to determine the mechanism of the adsorption study. In addition, the treatment procedure was simulated using artificial neural network analysis to estimate the maximum percentage of ranitidine removal from wastewater in terms of various operational parameters.