Artificial intelligence and regression analysis for Cd(II) ion biosorption from aqueous solution by Gossypium barbadense waste (original) (raw)

2018, Environmental science and pollution research international

In this study, batch biosorption experiments were conducted to determine the removal efficiency of Cd(II) ion from aqueous solutions by Gossypium barbadense waste. The biosorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) connected with energy dispersive X-ray (EDX). The sorption mechanism was described by complexation/chelation of Cd with the functional groups of O-H, C=O, -COO-, and C-O, as well as, cation-exchange with Mg and K. At initial Cd(II) ion concentration (C ), 50 mg/L, the adsorption equilibrium of 89.2% was achieved after 15 min under the optimum experimental factors of pH 6.0, biosorbent dosage 10 g/L, and particle diameter 0.125-0.25 mm. Both Langmuir and Freundlich models fitted well to the sorption data, suggesting the co-existence of monolayer coverage along with heterogenous surface biosorption. Artificial neural network (ANN) with a structure of 5-10-1 was performed to predict the Cd(II) ion removal...