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KINETIC MODELLING OF METHYLENE BLUE DYE ADSORPTION ON CORN COBS IN STATIC AND DYNAMIC MODES

Authors: A. Aarfane*, S. Tahiri, A. Salhi, J. Hassoune, H. Aassila, E.K. Lhadi, M. El Krati;

KINETIC MODELLING OF METHYLENE BLUE DYE ADSORPTION ON CORN COBS IN STATIC AND DYNAMIC MODES

Abstract

The purpose of this work was to study the removal of methylene blue (MB) from aqueous solutions by adsorption on corn cobs in static and dynamic modes. This agricultural by-product was first characterized and then a series of experiments was conducted to highlight the effect of different operating conditions on the adsorption capacity. Batch experiments revealed that adsorption of MB on corn cobs is affected by too acidic medium. Equilibrium data were represented well by a Langmuir isotherm equation with maximum adsorption capacity of 40 mg/g. RL values obtained at different dye concentration indicate that the sorption of MB on corn cobs is favorable. The second-order kinetic model describes perfectly adsorption kinetic data and adsorption may be controlled by external mass transfer followed by intra-particle diffusion mass transfer. The effectiveness of corn cobs biomass in the removal of methylene blue (MB) dye from its aqueous solution was tested by a fixed-bed column adsorption study. The results of dynamic mode were then modelled using Thomas and Yoon-Nelson equations. The results demonstrated that corn cobs are suitable for removal of MB from water using batch as well as fixed bed sorption system.

Keywords

Adsorption; Methylene Blue (MB); Corn cobs; Static and dynamic modes; Modelling.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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