Modeling defluoridation of real-life groundwater by a green adsorbent aluminum/olivine composite: Isotherm, kinetics, thermodynamics and novel framework based on artificial neural network and support vector machine. (15th January 2022)

• Record Type: Journal Article
• Authors: Sahu, Saswata; Yadav, Manoj Kumar; Gupta, Ashok Kumar; Uddameri, Venkatesh; Toppo, Ashish Navneet; Maheedhar, Bellum; Ghosal, Partha Sarathi
• Is Part Of: Journal of environmental management. Volume 302:Part A(2022)
• Publication Date: 2022-01-15
• Subjects: Fluoride adsorption -- Real-life groundwater -- Prediction model -- Artificial neural network -- Support vector machine; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2021.113965
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: The kinetic, isotherm, and thermodynamics of adsorptive removal of fluoride from the real-life groundwater was evaluated to assess the applicability of a green adsorbent, aluminum/olivine composite (AOC). The isotherm and kinetics were demonstrated by the Freundlich and Elovich model indicating significant surface heterogeneity of AOC in favouring the fluoride sorption. The fluoride removal efficiency of AOC was achieved as 87.5% after 240 min of contact time. The diffusion kinetic model exhibited that both the intra-particle and film diffusion together control the rate-limiting step of fluoride adsorption. A negative value of ΔG 0 (−19.919 kJ/mol) at 303 K confirmed the spontaneous adsorption reaction of fluoride, and its endothermic nature was supported by the negative value of ΔH 0 (39.504 kJ/mol). A novel framework for a predictive model by artificial neural network (ANN), and support vector machine (SVM) considering the real and synthetic fluoride-containing water was developed to assess the efficiency of adsorbent under different scenarios. ANN model was observed to be statistically significant (RMSE: 1.0955 and R 2 : 0.9982) and the proposed method may be instrumental in a similar area for benchmarking the synthetic and real-life samples. The low desorption potential of the spent adsorbent exhibited safe disposal of sludge and the secondary-pollutant-free treated water by the efficient and green adsorbent AOC enhanced the field-scale applicability of the green technology. Graphical abstract: Image 1 Highlights: AOC can efficiently remove fluoride from real-life groundwater up to 87.5%. Freundlich and Elovich models demonstrated adsorption isotherm and kinetics. Adsorption thermodynamic reflects spontaneous, endothermic, physisorption reaction. Benchmarking sorption process of synthetic and real-life water for field simulation. Neural network performed as better prediction model than support vector machine.