Chitosan-polyethylene oxide nanofiber/polyacrylamide-co-acrylic acid hydrogel nanocomposite: A copper ion adsorbent of aqueous solutions

• Published in: Inorganic chemistry communications 2024-01, Vol.159, p.111682, Article 111682
• Main Authors: Azizi, Sama, Shaki, Hanieh, Shafeeyan, Mohammad Saleh, Khonakdar, Hossein Ali
• Format: Article
• Language: English
• Subjects: Adsorption; Langmuir and Freundlich isotherms; Nanofiber-hydrogel composite; Water pollutants
• ISSN: 1387-7003; 1879-0259
• DOI: 10.1016/j.inoche.2023.111682

[Display omitted] •Preparing a nanocomposite based on chitosan–polyethylene oxide /poly(acrylamide-co-acrylic acid)•Investigating the effect of temperature, concentration and dosage on absorption efficiency.•Copper ions were homogeneously adsorbed at sites with the same adsorption energy.•Perfect agreement between experiment and a pseudo-second-order kinetic model. This study investigates the efficacy of chitosan–polyethylene oxide nanofibers and polyacrylamide-co-acrylic acid hydrogel as adsorbents for removing copper ions (Cu2+) from aqueous solutions. The synthesized adsorbents were characterization by various analysis techniques. The optimal conditions for removal efficiency of Cu+2 by nanofibers are temperature of 25 °C, concentration of 100 mg/L of Cu+2 solution, dosage of 50 mg of adsorbent, and time interval of 120 min. Also, for hydrogel, the optimal conditions included temperature of 30 °C, concentration of 350 mg/L of Cu+2 solution, dosage of 0.1 g of adsorbent, and time interval of 240 min. The nanofiber and hydrogel exhibited 69 % and 79 % adsorption efficiencies, respectively. To enhance the adsorption efficiency, a new nanocomposite from both materials was prepared (with adsorption efficiency of 92 %). The adsorption mechanism of Cu+2 ions on the proposed adsorbents was studied by the different isotherm models, with the Langmuir model providing the most accurate fit. The kinetic parameters were determined using main kinetic models, so that the second-order kinetics showed a better agreement with the experimental data.