2024 : 4 : 21
Amir Azizi

Amir Azizi

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0003-2741-6797
Education: PhD.
ScopusId: 56318653900
Faculty: Science
Address: Arak University


Green synthesis of iron oxide/cellulose magnetic recyclable nanocomposite and its evaluation in ciprofoxacin removal from aqueous solutions
Green synthesis · Verbascum thapsus · Magnetic nanocomposite · Iron oxide/cellulose · Ciprofoxacin · Adsorption
Journal Journal of the Iranian Chemical Society
Researchers Amir Azizi


In this work, an eco-friendly, rapid, and simple approach using natural chemical components available in the aqueous extract of Verbascum thapsus plant was used for green synthesis of iron oxide nanoparticles and then iron oxide/cellulose magnetic nanocomposite, with good magnetic separation capability. The properties of the green synthesis nanocomposite were studied using diferent techniques, such as X-ray spectroscopy, dynamic light scattering, and magnetometry. Dynamic light scattering and magnetometry analyses showed that the average particle size of the nanocomposite prepared is at least 18.5 nm with a surface charge of 22 mV and 25 emu/g magnetic saturation. In the following, the adsorption ability of the synthesized nanocomposite was evaluated to remove ciprofoxacin from aquatic solutions. The efectiveness of four important parameters, including pH, initial concentration of ciprofoxacin, amount of nanocomposite, and contact time, in ciprofoxacin removal was optimized. Furthermore, several isotherms and kinetic models as well as thermodynamic adsorption process were examined to obtain the mechanism and kinetics of the adsorption. The removal efciency was 92.01%. at the determined optimum conditions: pH of 7, concentrations of 15 mg/L of ciprofoxacin, nanocomposite dosage of 20 mg/L, and contact time of 40 min. Langmuir isotherm with a maximum adsorption capacity of 168.03 mg/g, a pseudo-frst-order kinetic model with a constant rate of 1.21/min, and a correlation coefcient of 0.986 were the best models for ftting the experimental data.