Optimization and Experimental Design of the Pb(2+) Adsorption Process on a Nano-Fe(3)O(4)-Based Adsorbent Using the Response Surface Methodology

[Image: see text] Magnetic Fe(3)O(4) nanoparticles have been used as adsorbents for the removal of heavy-metal ions. In this study, optimization of the Pb(2+) adsorption process using Fe(3)O(4) has been investigated. The adsorbent was characterized by various techniques such as transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), and Brunauer–Emmett–Teller (BET) analysis. The influence of process variables on adsorption of Pb(2+) ions in accordance with p < 0.05 was investigated and analyzed by the Box–Behnken design (BBD) matrix with five variables (pH, adsorbent dose, initial Pb(2+) ion concentration, contact time, and temperature). The pH and temperature were observed to be the most significant parameters that affected the Pb(2+) ion adsorption capacity from the analysis of variance (ANOVA). Conduction of 46 experiments according to BBD and a subsequent analysis of variance (ANOVA) provide information in an empirical equation for the expected response. However, a quadratic correlation was established to calculate the optimum conditions, and it was found that the R(2) value (0.99) is in good agreement with adjusted R(2) (0.98). The optimum process value of variables obtained by numerical optimization corresponds to pH 6, an adsorbent dose of 10 mg, and an initial Pb(2+) ion concentration of 110 mg L(–1) in 40 min at 40 °C adsorption temperature. A maximum of 98.4% adsorption efficiency was achieved under optimum conditions. Furthermore, the presented model with an F value of 176.7 could adequately predict the response and give appropriate information to scale up the process.