Preparation of nanomaterials for the ultrasound-enhanced removal of Pb2+ ions and malachite green dye: Chemometric optimization and modeling

Abstract

Copper oxide nanoparticle-loaded activated carbon (CuO-NP-AC) was synthesized and characterized using different techniques such as FE-SEM, XRD and FT-IR. It was successfully applied for the ultrasound-assisted simultaneous removal of Pb2+ ions and malachite green (MG) dye in binary system from aqueous solution. The effect of important parameters was modeled and optimized by artificial neural network (ANN) and response surface methodology (RSM). Maximum simultaneous removal percentages (>99.0%) were found at 25mgL−1, 20mgL−1, 0.02g, 5min and 6.0 corresponding to initial Pb2+ concentration, initial MG concentration, CuO-NP-AC amount, ultrasonication time and pH, respectively. The precision of the equation obtained by RSM was confirmed by the analysis of variance and calculation of correlation coefficient relating the predicted and the experimental values of ultrasound-assisted simultaneous removal of the analytes. A good agreement between experimental and predicted values was observed. A feed-forward neural network with a topology optimized by response surface methodology was successfully applied for the prediction of ultrasound-assisted simultaneous removal of Pb2+ ions and MG dye in binary system by CuO-NPs-AC. The number of hidden neurons, MSE, R2, number of epochs and error histogram were chosen for ANN modeling. Then, Langmuir, Freundlich, Temkin and D–R isothermal models were applied for fitting the experimental data. It was found that the Langmuir model well describes the isotherm data with a maximum adsorption capacity of 98.328 and 87.719mgg−1 for Pb2+ and MG, respectively. Kinetic studies at optimum condition showed that maximum Pb2+ and MG adsorption is achieved within 5min of the start of most experiments. The combination of pseudo-second-order rate equation and intraparticle diffusion model was applicable to explain the experimental data of ultrasound-assisted simultaneous removal of Pb2+ and MG at optimum condition obtained from RSM.