Enhanced Adsorption of Hexavalent Chromium onto Magnetic Calcium Ferrite Nanoparticles: Kinetic, Isotherm, and Neural Network Modeling

Abstract

Calcium ferrite nanoparticles with super-paramagnetic behavior were synthesized via simple chemical precipitation method for effective removal of hexavalent chromium from aqueous media. The properties of synthesized nanoparticles were studied by X-ray diffraction (XRD), field emission scanning electron microscope (FESEM), Fourier transform infrared (FTIR) spectroscopy, Brunauer-Emmett-Teller (BET), and vibrating sample magnetometer (VSM) measurements. The ferrite nanoparticles have shown polycrystalline nature and high BET specific surface area (229.83 m2/g) with active functional groups on the surface. The adsorption process follows second-order kinetics with the involvement of intra-particle diffusion and adsorption capacity as much as 124.11 mg/g was determined from the Langmuir isotherm. The thermodynamic analysis revealed that the adsorption process was feasible, spontaneous, and exothermic in nature. A three-layer feed-forward back-propagation artificial neural network (ANN) model was employed to predict the removal (%) of Cr(VI) ions as output. Optimal ANN network (4:8:1) shows the minimum mean squared error (MSE) of 0.00161 and maximum coefficient of determination (R2) of 0.984. The adsorption process is mostly influenced by solution pH and followed by adsorbent dosage, initial Cr(VI) concentration, and contact time as illustrated by sensitivity analysis. With small size and high surface area, biocompatibility, ecofriendly nature, easy magnetic separation, and enhanced adsorption capacity towards Cr(VI), calcium ferrite nanoparticles will find its potential application in wastewater remediation.