Response surface modeling of lead (׀׀) removal by graphene oxide-Fe3O4 nanocomposite using central composite design.

Background: Magnetic graphene oxide (Fe3O4@SiO2-GO) nanocomposite was fabricated through a facile process and its application as an excellent adsorbent for lead (II) removal was also demonstrated by applying response surface methodology (RSM).
Methods: Fe3O4@SiO2-GO nanocomposite was synthesized and characterized properly. The effects of four independent variables, initial pH of solution (3.5-8.5), nanocomposite dosage (1-60 mg L(-1)), contact time (2-30 min), and initial lead (II) ion concentration (0.5-5 mg L(-1)) on the lead (II) removal efficiency were investigated and the process was optimized using RSM. Using central composite design (CCD), 44 experiments were carried out and the process response was modeled using a quadratic equation as function of the variables.
Results: The optimum values of the variables were found to be 6.9, 30.5 mg L(-1), 16 min, and 2.49 mg L(-1) for pH, adsorbent dosage, contact time, and lead (II) initial concentration, respectively. The amount of adsorbed lead (II) after 16 min was recorded as high as 505.81 mg g(-1) for 90 mg L(-1) initial lead (II) ion concentration. The Sips isotherm was found to provide a good fit with the adsorption data (KS = 256 L mg(-1), nS = 0.57, qm = 598.4 mg g(-1), and R(2) = 0.984). The mean free energy Eads was 9.901 kJ/mol which confirmed the chemisorption mechanism. The kinetic study determined an appropriate compliance of experimental data with the double exponential kinetic model (R(2) = 0.982).
Conclusions: Quadratic and reduced models were examined to correlate the variables with the removal efficiency of Fe3O4@SiO2-GO. According to the analysis of variance, the most influential factors were identified as pH and contact time. At the optimum condition, the adsorption yield was achieved up to nearly 100 %.