Dye adsorption from single and binary systems using NiO-MnO2 nanocomposite and artificial neural network modeling

作者：Mahmoodi Niyaz Mohammad; Hosseinabadi Farahani Zahra; Chamani Hooman

来源：Environmental Progress & Sustainable Energy, 2017, 36(1): 111-119.

DOI：10.1002/ep.12452

<jats:p>NiO‐MnO<jats:sub>2</jats:sub> nanocomposite was synthesized and its dye removal ability from single and binary systems was investigated. The characteristics of the synthesized nanocomposite were studied using scanning electron microscopy (SEM), X‐ray diffraction (XRD), and Fourier transform infrared (FTIR). Basic Blue 41 (BB41), Basic Red 18 (BR18), and Basic Red 46 (BR46) were used. Artificial neural network (ANN) as an intelligent system was used to model the dye removal process. The effect of operational parameters such as adsorbent dosage and initial dye concentration on dye removal was evaluated. It was found that adsorption of BB41, BR18, and BR46 on the nanocomposite followed the Langmuir, Freundlich, and Tempkin isotherms, respectively. The adsorption kinetics of dyes were found to conform to pseudo‐second‐order kinetics in both single and binary systems. The results showed that the predictions of the ANN models were in close agreement with experimental data.

• 出版日期2017-1