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 (2mol/L) to raise the suspension pH to around 9 at room temperature under ultrasonic irradiation (200W) as an efficient method and characterized by FE-SEM, FTIR and N adsorption-desorption isotherm. The effect of different parameters such as contact time (0-120min), initial metal ion concentration (25-200mg/L), temperature (298, 318 and 333K), amount of adsorbent (0.002-0.007g) 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 (R>0.99). The maximum monolayer adsorption capacity (q) of NiO/ACNC was 1428.57mg/L. Thermodynamic parameters (ΔG°, ΔH° and ΔS°) 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 (R>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.

Modelling of the adsorption of urea herbicides by tropical soils with an Adaptive‐Neural‐based Fuzzy Inference System

“…Amiri et al 26 applied ANFIS to model Pb (II) adsorption from aqueous solution by ostrich bone ash. Javadian et al 27 also carried out a FIS modelling of Pb II sorption onto mesoporous NiO/ZnCl 2 ‐ Rosa Canina‐L seeds activated carbon nanocomposite. Tanhaei et al 28 reported a neuro‐fuzzy modelling of methyl orange removal by magnetic chitosan nanocomposite.…”

Adaptive neuro‐fuzzy inference system modeling of 2,4‐dichlorophenol adsorption on wood‐based activated carbon

“…Adsorption is considered one of the most competitive techniques, which saves processing power, provides economic benefits, and is a feasible system that is a simple, nontoxic, and low‐cost . Because of the lack of sufficient surface‐active areas and/or diffusion limitation, most adsorbents are ineffective and can present problems such as high cost, difficulty in separation from water, and formation of secondary waste . Considering such disadvantages, recently, wood‐based activated carbon (WbAC), which has unique properties such as size and morphology, has been found to have high adsorption efficiency for micro‐pollutant removal .…”

Introduction of explicit equations for the estimation of surface tension, specific weight, and kinematic viscosity of water as a function of temperature

“…Modelling not only helps develop a comprehensive understanding of a process, but also has the potential to predict and solve problems in specific processes. 8 Mathematical modelling and computer simulation are also valuable and powerful tools for describing and evaluating their performance under both dynamic and steady-state conditions. On the other hand, there are few systematic articles on the implementation of forecasting models that can be used directly for both design and educational purposes.…”