Adsorption is a cost effective and green technology for the removal of hazardous chemicals from aqueous media. In current work, remediation of cadmium ions from aqueous media is performed by employing chemically modified Saccharum arundinaceum. Sorbent was pretreated with acid and base, separately, to check the effect of these chemicals on its adsorption potential and base treated sorbent was selected for further analysis, due to its higher sorption potential (97.5%) for Cd2+. Characterization of sorbent was carried out by recording FTIR spectra for determination of functional groups and SEM for evaluation of surface morphology. FTIR spectra reflect suitability of sorbent material for removal of Cd2+ due to presence of abundant –OH groups on sorbent surface, which may develop strong binding with sorbate. SEM results exhibited presence of cylindrical cavities on sorbent surface, endorsing viability of sorbent for the removal of Cd2+. 24 full factorial design (FFD) was employed to optimize the experimental conditions. Experimental results of adsorption process were compared with the predicted results; obtained by first-order model of FFD and Artificial Neural Network (ANN). In FFD, all the possible combinations were used and predicted model was generated for application on experimental setup. Similarly, ANN was used to obtain predicted response by multi-layer perceptron (MLP) method. Predictive analysis, carried out by both the modeling techniques, yielded comparable results, i.e. FFD (0.9852) and ANN (0.9788); revealing good prediction ability of both the modeling techniques.

Fozia Batool, Shahid Iqbal, Jamshed Akbar and Sobia Noreen