Artificial neural network modelling of Cr(VI) surface adsorption with NiO nanoparticles using the results obtained from optimization of response surface methodology
In this study, the nanoparticles of sol–gel-synthesized NiO were used as effective adsorbents for removing Cr(VI) from aqueous solutions. To do so, the effect of four initial parameters including Cr(VI) concentration, the amount of NiO adsorbent, contact time, and pH on removing Cr(VI) with sol–gel-synthesized NiO was studied. Using the results of designing the experiment, the process of surface adsorption by ANN was modelled. For modelling the results of Cr(VI) removal process with NiO nanoparticles, a three-layered ANN of feed-forward back-propagation having 4:10:1 topology was used. The findings indicated that the results obtained from ANN correspond well with the data obtained from response surface methodology and experimental data.
KeywordsAdsorption Cr(VI) NiO nanoparticles Sol–gel method Artificial neural network (ANN)
The authors gratefully acknowledge their appreciation to the Islamic Azad University, Maragheh, for providing facilities.
Compliance with ethical standards
Conflict of interest
The authors have no conflict of interest.
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