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Synthesis, Characterization and Performance of NiO/CNT Nanocomposite for Arsenic Removal from Aqueous Media

[ Vol. 13 , Issue. 6 ]

Author(s):

Reza Moradi* and Fatemeh Faraji Rokni   Pages 579 - 585 ( 7 )

Abstract:


Background: Arsenic considered as one of the most frequent and most toxic heavy metals. The WHO guideline value for arsenic in drinking water was lowered to 10 ppm. But nevertheless, surface water with arsenic concentrations 200 ppm has also been reported. The presence of arsenic in water resources causes various diseases including cancer, blood pressure, symptoms of skin and etc… several methods have been considered for remove the heavy metals from aqueous media such as: ion exchange, coagulation, adsorption on active alumina and using of iron salts and sulphide as arsenic adsorbent.

Method: In this study, evaluate attempt to remove of arsenic from water resources. To limit the spread of the arsenic within water sources, NiO/CNT nanocomposite adsorbents were synthesized and characterized with the aim of removal of one of the aggressive arsenic ions. Affinity and efficiency adsorption parameters of NiO/CNT nanocomposite, such as; contact time, mass of adsorbent, initial concentration of arsenic ions, sizes of existing NiO nanoparticle at adsorbent and adsorption isotherm behaviors were studied.

Results: the efficiency of arsenic adsorption enhanced with increasing of contact time, mass of adsorbent and sizes of existing NiO nanoparticle on the surface of CNTs. With increasing the initial concentration up to 5 ppm, the removal efficiency is reduced and it reaches to 90%. Then, with further increase at initial concentration, removal efficiency enhanced and reaches to about 94% at 20 ppm. Thus, the optimal concentration of removal efficiency was not observed. The value of RL for both Freundlich and Langmuir models are between zero and one, so adsorption isotherm of these two models are desirable for adsorption of arsenic on NiO/CNT nanocomposite. Due to the higher regression coefficient (R2) of Freundlich model, the fit is better with Freundlich model than with Langmuir model.

Conclusion: The present study shows that NiO-nanoparticles prepared by polyol method is a good adsorbent for removal of As ions from aqueous media and smaller nanoparticle have more activity than larger own. The adsorption process is a function of the adsorbent mass and concentrations and contact time. Optimal adsorptions were for 0.2 g adsorbent and 30 min contact time. Freundlich model is found to be in a good agreement with experimental data on adaptive behavior of As ions on NiO/CNT. NiO/CNT nanocomposite is then considered as a useful catalyst for the treatment of arsenic contaminated water.

Keywords:

NiO nanoparticles, carbon nanotubes, nanocomposites, absorbent, removal efficiency, adsorption isotherm, Langmuir and Freundlich model.

Affiliation:

Department of Physics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Department of Physics, Sari Branch, Islamic Azad University, Sari

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