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Erschienen in: Arabian Journal for Science and Engineering 12/2019

15.07.2019 | Research Article - Chemical Engineering

Removal of Congo Red from Aqueous Solution Using ‘Perna viridis’: Kinetic Study and Modeling Using Artificial Neural Network

verfasst von: Adarsh Ajith Naik, Vishnuprasad Selvaraj, Haribabu Krishnan

Erschienen in: Arabian Journal for Science and Engineering | Ausgabe 12/2019

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Abstract

In this work, the removal of Congo red dye from its aqueous solution by a low-cost adsorbent obtained from Perna viridis sea shell, an aquacultural solid waste, was studied. Maximum removal of 98% of the dye was obtained with adsorbent dosage 22 g L−1, pH of 5.5, contact time of 30 min and temperature of 308.5 K. Various adsorption reaction models were investigated and found that the pseudo-second-order model best described the reaction kinetics. Further, the mechanism of adsorption was studied using the intra-particle diffusion model, and it was confirmed that the intra-particle diffusion and boundary layer diffusion were the rate-controlling factors. Artificial neural network model was developed for the prediction of the percentage removal of the dye from its aqueous solution, and the prediction was in agreement with the experimental results obtained. It was inferred that the adsorbent prepared from P. viridis having high thermal stability (600 °C), a surface area of 13.746 m2 g−1 and mean pore diameter 7.0625 nm should be an excellent alternative for the conventional adsorbent used for the removal of the carcinogenic dye such as Congo red from its aqueous solution at any operating condition.

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Metadaten
Titel
Removal of Congo Red from Aqueous Solution Using ‘Perna viridis’: Kinetic Study and Modeling Using Artificial Neural Network
verfasst von
Adarsh Ajith Naik
Vishnuprasad Selvaraj
Haribabu Krishnan
Publikationsdatum
15.07.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Arabian Journal for Science and Engineering / Ausgabe 12/2019
Print ISSN: 2193-567X
Elektronische ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-019-03993-6

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