Fuzzy logic modeling of Pb (II) sorption onto mesoporous NiO/ZnCl2-Rosa Canina-L seeds activated carbon nanocomposite prepared by ultrasound-assisted co-precipitation technique

Abstract

In this study, NiO/Rosa Canina-L seeds activated carbon nanocomposite (NiO/ACNC) was prepared by adding dropwise NaOH solution (2 mol/L) to raise the suspension pH to around 9 at room temperature under ultrasonic irradiation (200 W) as an efficient method and characterized by FE-SEM, FTIR and N2 adsorption-desorption isotherm. The effect of different parameters such as contact time (0–120 min), initial metal ion concentration (25–200 mg/L), temperature (298, 318 and 333 K), amount of adsorbent (0.002–0.007 g) and the solution's initial pH (1–7) on the adsorption of Pb (II) was investigated in batch-scale experiments. The equilibrium data were well fitted by Langmuir model type 1 (R2 > 0.99). The maximum monolayer adsorption capacity (qm) of NiO/ACNC was 1428.57 mg/L. Thermodynamic parameters (¿G°, ¿H° and ¿S°) were also calculated. The results showed that the adsorption of Pb (II) onto NiO/ACNC was feasible, spontaneous and exothermic under studied conditions. In addition, a fuzzy-logic-based model including multiple inputs and one output was developed to predict the removal efficiency of Pb (II) from aqueous solution. Four input variables including pH, contact time (min), dosage (g) and initial concentration of Pb (II) were fuzzified using an artificial intelligence-based approach. The fuzzy subsets consisted of triangular membership functions with eight levels and a total of 26 rules in the IF-THEN approach which was implemented on a Mamdani-type of fuzzy inference system. Fuzzy data exhibited small deviation with satisfactory coefficient of determination (R2 > 0.98) that clearly proved very good performance of fuzzy-logic-based model in prediction of removal efficiency of Pb (II). It was confirmed that NiO/ACNC had a great potential as a novel adsorbent to remove Pb (II) from aqueous solution.