4.7 Article

Investigate the ultrasound energy assisted adsorption mechanism of nickel(II) ions onto modified magnetic cobalt ferrite nanoparticles: Multivariate optimization

期刊

ULTRASONICS SONOCHEMISTRY
卷 37, 期 -, 页码 37-46

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ultsonch.2016.12.038

关键词

Multivariate optimization; Ultrasound energy; Adsorption; Ni2+ ions; Magnetic cobalt ferrite nanoparticles; Adsorption mechanism

资金

  1. Young Researchers and Elite Club, Gachsaran Branch, Islamic Azad University

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In present study, magnetic cobalt ferrite nanoparticles modified with (E)-N-(2-nitrobenzylidene)2-(2-(2-nitrophenyl)imidazolidine-1-yl) ethaneamine (CoFe2O4-NPs-NBNPIEA) was synthesized and applied as novel adsorbent for ultrasound energy assisted adsorption of nickel(II) ions (Ni2+) from aqueous solution. The prepared adsorbent characterized by Fourier transforms infrared spectroscopy (FT-IR), transmission electron microscope (TEM), vibrating sample magnetometer (VSM) and X-ray diffraction (XRD). The dependency of adsorption percentage to variables such as pH, initial Ni2+ ions concentration, adsorbent mass and ultrasound time were studied with response surface methodology (RSM) by considering the desirable functions. The quadratic model between the dependent and independent variables was built. The proposed method showed good agreement between the experimental data and predictive value, and it has been successfully employed to adsorption of NO2+ ions from aqueous solution. Subsequently, the experimental equilibrium data at different concentration of Ni2+ ions and 10 mg amount of adsorbent mass was fitted to conventional isotherm models like Langmuir, Freundlich, Tempkin, Dubinin-Radushkevich and it was revealed that the Langmuir is best model for explanation of behavior of experimental data. In addition, conventional kinetic models such as pseudo-first and second-order, Elovich and intraparticle diffusion were applied and it was seen that pseudo-second order equation is suitable to fit the experimental data. (C) 2016 Elsevier B.V. All rights reserved.

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