MWCNT-Fe3O4 as a superior adsorbent for microcystins LR removal: Investigation on the magnetic adsorption separation, artificial neural network modeling, and genetic algorithm optimization

Dobaradaran, Sina and Baziar, Mansour and Azari, Ali and Karimaei, Mostafa and Gupta, Vinod Kumar and Agarwal, Shilpi and Sharafi, Kiomars and Maroosi, Mohammad and Shariatifar, Nabi (2017) MWCNT-Fe3O4 as a superior adsorbent for microcystins LR removal: Investigation on the magnetic adsorption separation, artificial neural network modeling, and genetic algorithm optimization. Journal of Molecular Liquids, 241. pp. 102-113.

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Abstract

Magnetic multi-wall carbon nanotube (MMWCNT) was prepared by simple protocol and its structural features were characterized using SEM, TEM, and XRD analysis. The association between removal (%) and variables such as pH (3 − 11), adsorbent amounts (0.005, 0.1, 0.25, 0.5, 0.75, and 1 g/L), reaction time (5–180 min), and concentration of microcystins-LR (10, 25, 50, 75, and 125 μg/L) was investigated and optimized. The results of the isotherm study indicated that Langmuir offered high determination coefficients (R2 = 0.993, 0.996, and 0.998, for the three different working temperatures of 20 °C, 35 °C, and 50 °C respectively) and was the optimum isotherm to anticipate adsorption of MC-LR (microcystins-LR) by magnetic MWCNT adsorbent. The kinetic study revealed that the adsorption kinetics of MC-LR could be better defined using the pseudo-second-order model. A three-layer model of an artificial neural network was applied to forecast the MC-LR removal efficiency by magnetic MWCNTs over 66 runs. To forecast the MC-LR removal efficiency, the minimum mean squared error of 0.0011 and determination coefficient (R2) of 0.9813 were obtained. The use of the artificial neural network model achieved a good level of compatibility between the acquired and anticipated data.

Item Type: Article
Subjects: WA Public Health
Divisions: Faculty of Public Health
Depositing User: محسن زارعی
Date Deposited: 31 Dec 2018 08:31
Last Modified: 31 Dec 2018 08:31
URI: http://eprints.bpums.ac.ir/id/eprint/7348

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