Journal
JOURNAL OF MOLECULAR LIQUIDS
Volume 218, Issue -, Pages 354-362Publisher
ELSEVIER
DOI: 10.1016/j.molliq.2016.02.048
Keywords
Anionic dye MO; Adsorption isotherm; Random forest; Artificial neural network; Partial swarm optimization
Funding
- Yasouj University
- NRF South Africa
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The efficiency and performance of lead oxide nanoparticles loaded activated carbon were well investigated and elucidated for the removal of methyl orange dye. The influence of variables like; pH, contact time, MO concentration and mass of adsorbent was investigated and optimized by artificial neural network-partial swarm optimization (ANN-PSO). At optimal conditions predicted by ANN-P50, the coefficient of determination (R-2) and mean square error (MSE) correspond to test data were 0.97 and 0.00093, respectively. The maximum removal percentage (similar to 98%) was observed at conditions set at: 0.02 g of PbO-NP-AC, 15 mg L-1 of MO at pH 2.0 following mixing and stirring for 20 min. The experimental data were efficiently explained by the Langmuir isotherm model at all conditions with maximum adsorption capacity of 333.33 mg g(-1). Kinetic studies at various adsorbent mass and initial MO concentrations revealed that maximum MO removal was achieved within 15 min. The experimental data follow the pseudo-second-order rate equation. (c) 2016 Elsevier B.V. All rights reserved.
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