期刊
JOURNAL OF MOLECULAR LIQUIDS
卷 218, 期 -, 页码 354-362出版社
ELSEVIER
DOI: 10.1016/j.molliq.2016.02.048
关键词
Anionic dye MO; Adsorption isotherm; Random forest; Artificial neural network; Partial swarm optimization
资金
- Yasouj University
- NRF South Africa
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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