Heavy metals are one of the most important environmental pollutants. One of the methods of absorbing heavy metals from industrial wastewater is the use of synthesized nanosorbents. The high cost and low efficiency of some common industrial wastewater treatment processes have created limitations. One of the interesting methods is the absorption process by carbon nanotubes as a new method. The present research aims to investigate the application of Al nanoparticles coated with polyaniline and functionalized modified multi-walled carbon nanotubes (MWCNT) for removal of Ni2+ and Zn2+ from a simulated industrial effluent. In the present study, the effect of absorption process time, pH, nickel and zinc ion dose, adsorbent dose and temperature on the efficiency of heavy metal absorption was investigated. The concentration of metal ions was measured using the ICP model ES-710. FTIR spectra for modified MWCNT nanotubes and polyaniline-coated alumina nanoparticles were recorded before and after adsorption using a PerkinElmer Spectrum One FTIR vacuum oven. X-ray diffraction patterns were obtained by XRD Rigaku Ultima IV, Japan, and SEM and TEM micrograph analysis were performed by FESEM TESCAN MIRA 3 and PHILIPS CM300, respectively.The maximum removal efficiency of nickel and zinc cations using nano alumina coated with polyaniline was obtained at pH 10 and 8, respectively. The maximum removal percentage of these two metal ions using functionalized MWCNTs can also be obtained at pH 7 and 8. The optimal concentration of metal ions for the highest removal efficiency of studied cations using surface modified alumina nanoparticles and functionalized MWCNT was obtained at 800 mg/L and 100 mg/L, respectively. In addition, the adsorption efficiency decreased with increasing process temperature. The obtained results showed that surface MWCNT with carbonyl, carboxyl and hydroxyl functional groups together with alumina nanoparticles modified by polyaniline can be considered as a potential adsorbent for absorbing nickel and zinc cations from simulated industrial effluents.
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