Removing silver ions from aqueous solution through a modified graphene oxide adsorbent: Mechanism and machine learning

Abstract

In this work, silver ions were removed using modified graphene oxide (GO) with Gallic Acid (GA). Properties of GO/GA composites were characterized using Fourier transform infrared spectroscopy (FT-IR), Scanning electron microscope (SEM), X-ray diffraction (XRD), and Thermal Gravity Analysis (TGA). The effects of experimental parameters such as pH, adsorbent dosage, contact time, and initial concentrations of silver on the adsorption treatment of Ag (I) ions were investigated. Results indicated the optimum condition (98.35 % adsorption) was achieved at pH = 7, 25 mg of adsorbent, a time of 60 min, and an initial concentration of 50 ppm at 25 °C. Langmuir and Dubinin-Radushkevich isotherm models could reasonably interpret the adsorption data. In addition, the pseudo-second-order model appropriately described the kinetics of the adsorption process. Moreover, suggested mechanisms of modified adsorbent and the process were introduced. Finally, this work was compared with others, and all experimental data at different conditions were forecasted through machine learning.