Removal of Bisphenol-A by NaP Zeolite/Hydroxyapatite Composite: Adsorption Experiments and Modeling by Artificial Neural Networks

In this paper, we have reported removal of Bisphenol A (BPA) by Hydroxyapatite/NaP zeolite (HAp: Zeolite ) nanocomposite which synthesized in previous our work and characterized by using different methods such as X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscope, Energy Dispersive X-ray analysis, surface area, and thermogravimetric analysis. To investigate the purification performance for removal BPA batch experiments were used. The results showed that the removal capacity could reach an equilibrium value of 11.125 mg/g in the initial BPA concentration of 50 mg/L. Some parameters such as initial concentration, pH, contact time, adsorbent dosage, and the temperature were studied that result shows this nanocomposite have high capacity for adsorption of BPA. The kinetic study presented that it agreed well with the pseudo-second-order model (R2= 0.994). Furthermore, thermodynamics studies were carried out, and result showed an exothermic condition for adsorption process. An artificial neural networks (ANNs) model was developed to predict the performance removal process based on experimental information which shows an association between the predicted results of the designed ANN model and experimental data. Results showed that the neural network model predicted values are found in close agreement with the batch experiment result with a correlation coefficient (R2) about 0.99051 and mean squared error 0.005938.