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Artificial neural network approach for modelling of methyl violet 2B dye adsorption using pomelo skin

Journal of Environment & Biotechnology Research, Vol. 6, No. 3, Pages 238-247, July 2017

Muhammad Khairud Dahri, Muhammad Raziq Rahimi Kooh, Linda Biaw Leng Lim


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ABSTRACT

This study investigates pomelo peel (PP) as a low-cost adsorbent for removal of methyl violet 2B (MV) by batch adsorption study. The adsorbent was characterised using Fourier-transform infrared spectroscopy. The experiments included the effects of pH, ionic strength, temperature, initial dye concentration and contact time. Modelling of the adsorption process with a three-layer artificial neural network were in good agreement with the experimental data with high correlation coefficient (R=0.9978) and low error (root mean square error =0.01) for 3 neurons in the hidden layer. The data on the investigation of ionic strength (62% dye removal at 0.8 mol/L KNO3) showed that hydrophobic-hydrophobic interaction may be the dominant force of attraction between the adsorbent and adsorbate, as the electrostatic interaction was suppressed at high salt concentration. The pseudo second model best described the adsorption kinetics as the adsorption followed a second order rate law with respect to availability of adsorption sites. The Weber-Morris intraparticle diffusion model indicated that the rate-limiting step was not intraparticle diffusion. Thermodynamics study revealed that PP-MV adsorption system was spontaneous and exothermic in nature. Lastly, the Langmuir model best represented the adsorption process and predicted a superior qmax value of 1.2 mmol/g (468.3 mg/g).
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Journal of Environment and Biotechnology Research
Volume 6, Number 3, 2017, pp. 238-247
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