Efficient removal of methylene blue dye using mangosteen peel waste: kinetics, isotherms and artificial neural network (ANN) modelling

Abstract

a b s t r ac tIn this work, mangosteen peel (MP) waste was used as a new biosorbent for removal of methylene blue (MB) dye from aqueous solution. Surface area, surface functional groups, surface charge and surface morphology were analyzed through Brunauer Emmett Teller, Fourier transform infrared, pH zpc and field emission scanning electron microscopy/energy dispersive X-ray spectroscopy techniques, respectively. The major functional groups were -CO, -COO and -OH. Batch adsorption experiments were conducted with varying MP dose (0.01-0.08 g), pH (2-12), contact time (10-60 min), temperature (25°C-45°C) and concentration of MB solution (50-150 mg/L). The study examined the implementation of artificial neural network for the prediction of MB adsorption from aqueous solution by MP, based on 30 experimental sets of batch adsorption study. Optimum number of neurons determined was 4 for LevenbergMarquardt training algorithm; at which the highest value of R 2 and lowest mean square error were found to be 0.997 and 2.972, respectively. Among the various kinetic models applied, the pseudo-second-order kinetic model was identified to be the most suitable to represent the adsorption of MB on the surface of MP. Langmuir, Freundlich, Temkin and Harkins-Jura isotherm models were employed to study the adsorption equilibrium. Langmuir isotherm model was identified as the most suitable. The calculated values of thermodynamic factors, ∆S°, ∆G°, S*, E a and ∆H°, showed that the adsorption phenomenon is spontaneous, feasible and endothermic in nature.

Micro-Bubble Flotation for Removing Cadmium Ions from Aqueous Solution: Artificial Neural Network Modeling and Kinetic of Flotation

“…the potential toxicity of residuals amounts of collector in the effluent and cost [23], also this figure confirms that the ANN model could be effectively predicting the experimental results. To theoretically examine, if the amount of SDS represent the optimum value for highly removal efficiency, ANN model was used at different concentrations of SDS was varied around the best value (15,18,20,22,25,28,30 and 35 mg/L) as shown in Fig. 10.…”

“…Numerous studies have been conducted in which ANNs were used in different wastewater processes such as flotation [17], advanced oxidation process [18] power generation by microbial fuel cell [19], adsorption [20] , and sorptive flotation [21]. The scope of this study was to investigate the effect of micro-bubbles in the removal efficiency of Cd(II) ions from aqueous solution at different parameters , ionic strength , flotation kinetic and use the artificial neural network (ANN) to describe this behavior.…”

Removal of anthracene in water by MIL-88(Fe), NH2-MIL-88(Fe), and mixed-MIL-88(Fe) metal–organic frameworks

“…Adsorption is considered one of the most prosperous and environmental friendly technique for wastewater remediations. [18][19][20][21] The use of biomass, [22][23][24][25] activated carbon [26][27][28][29] and clay minerals 30,31 as adsorbents for organic contaminants remediation has been fully studied.…”

Preparation of Nano-Particles and Their Applications in Adsorption

“…A range of effective, low-cost and environment friendly nano-materials with outstanding properties have been developed for prospective applications in decontamination of industrial effluents, surface, ground and drinking water. Literature also revealed that nanoparticles behave as an ideal adsorbent as they are environmentally benign, selective, efficient, recyclable, high surface area and maximum adsorption capacity even at a very low concentration [24][25][26].…”