Background &Objectives: Aniline is a substance used in chemical industries and in various processes such as pesticide production, chemical bleaching, textile dyes, etc. In spite of the negative effects of aniline on the environment due the difficult decomposition of this substance, various methods have been investigated to remove this substance from water resources. The aim of this study was to investigate the efficiency of magnetized carbon nanotubes in the removal of aniline from aqueous solutions.
Methods: Fe3O4-CNT magnetic nanoparticles were prepared by co-precipitation method. The morphology of the adsorbent surface, shape and size of CNT-Fe3O4 magnetic nanoparticles was investigated by scanning electron microscopy (SEM) and transfer electron microscopy (TEM). BET analysis was also used to determine the physical properties of the adsorbent such as surface area, size and volume of the cavities and their distribution on the adsorbent. An X-ray diffraction device (XRD) was used to determine the pattern and the purity of the Fe3O4 particles. The synthetic adsorbent properties were analyzed by FTIR technique. In order to optimize the adsorption conditions and determine the optimal values of each of the factors affecting the adsorption process (pH, contact time, adsorbent value, initial aniline error and temperature), adsorption experiments were performed and aniline concentration was determined by spectrophotometric method.
Results: SEM and TEM analyzes showed that the magnetic carbon nanotubes were almost uniform and had an average diameter of 5 nanometers and an average length of 100 nanometers. XRD analysis also showed the stabilization of Fe3O4 on carbon nanotubes. FTIR analysis for the absorption of aniline contaminants on the magnetic carbon nanotubes adsorbent indicated that the aniline contaminant bond has appeared on the adsorbent.
Conclusion: The results of the study showed that magnetic MWCNT adsorbent was able to effectively remove aniline contaminants from aquatic environments. Statistical analysis showed that pH parameters, adsorption concentration, pollutant concentration, temperature and contact time were effective on pollutant removal efficiency.