Sorptive remediation of fluoride by ultra-sonicated iron-based polyaniline nano-composite: optimization and modelling using artificial neural network, kinetic and thermodynamic study

Abstract

The present research work approaches the removal of fluoride from contaminated water using an eco-friendly novel iron-based polyaniline nano-composite (PAn) in a batch mode method. The fluoride adsorption efficiency was studied with variation of parameters like initial fluoride concentration 10-20 mg L⁻¹, contact time 10-90 min, variation of adsorbent dose 0.1−1 g, temperature 25°, 30° and 40°C, pH 2-12 and presence of competing ions at 25°, 30° and 40°C and was optimised with artificial neural network model (ANN). The experimented adsorption data was best fitted to Langmuir adsorption isotherm with maximum adsorption capacity of 89.41 mg g⁻¹ at 40°C. The adsorption kinetics followed the pseudo second order reaction. The thermodynamics studies indicate that the adsorption process was spontaneous and endothermic in nature. The maximum fluoride removal was found to be 91% with good agreement to the results predicted by ANN model (structure 5-10-1). The PAn nano-composite can be used maximum of up to four cycles for defluoridation of drinking water. To determine the adhesion of fluoride on the PAn nano composite, the material was characterized using different instrumental analyses like SEM EDS, BET, XRD and FTIR. The FePAn nanocomposite can be used maximum up to four cycles for defluoridation of drinking water.