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Fractal-Like Kinetics of Adsorption Applied to the Solid/Solution Interface.


ABSTRACT: In this paper, the fractal-like multiexponential (f-mexp) equation was modified by introducing the fractional fractal exponent to each stage of the adsorption process. The new equation was used for the analysis of kinetic adsorption of copper onto treated attapulgite. The modeling results show that the modified f-mexp equation fits properly the kinetic data in comparison with the classical and fractal-like kinetic models tested. The effect of varying the initial concentration of the adsorbate on the kinetic parameters was analyzed. Artificial neural networks were applied for the prediction of adsorption efficiency. Outcomes indicate that the multilayer perceptron neural network can predict the removal of copper from aqueous solutions more accurately under different experimental conditions than the single-layer feedforward neural network. Single-site and multisite occupancy adsorption models were used for the analysis of experimental adsorption equilibrium data of copper onto treated attapulgite. The modeling results show that there is no multisite occupancy effect and that the equilibrium data fit well the Langmuir-Freundlich isotherm.

SUBMITTER: El Bardiji N 

PROVIDER: S-EPMC7081449 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Fractal-Like Kinetics of Adsorption Applied to the Solid/Solution Interface.

El Bardiji Naoual N   Ziat Khadija K   Naji Ahmed A   Saidi Mohamed M  

ACS omega 20200306 10


In this paper, the fractal-like multiexponential (f-mexp) equation was modified by introducing the fractional fractal exponent to each stage of the adsorption process. The new equation was used for the analysis of kinetic adsorption of copper onto treated attapulgite. The modeling results show that the modified f-mexp equation fits properly the kinetic data in comparison with the classical and fractal-like kinetic models tested. The effect of varying the initial concentration of the adsorbate on  ...[more]

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