Ecofriendly Synthesis of Magnetic Composites Loaded on Rice Husks for Acid Blue 25 Decontamination: Adsorption Kinetics, Thermodynamics, and Isotherms

Abstract

Addressing the growing need for methods for ecofriendly dye removal from aqueous media, this study explores the potential of rice husks coated with iron oxide (Fe2O3@RH composites) for efficient Acid Blue 25 decontamination. The adsorption potential of Acid Blue 25 is analyzed using raw rice husks and Fe2O3 nanoparticles in the literature, but their enhanced removal capacity by means of Fe2O3@RH composites is reported for the first time in this study. Fe2O3@RH composites were analyzed by using analytical techniques such as TGA, SEM, FTIR, BET, and the point of zero charge (pH(PZC)). The Acid Blue 25 adsorption experiment using Fe2O3@RH composites showed maximum adsorption at an initial concentration of Acid Blue 25 of 80 ppm, a contact time of 50 min, a temperature of 313 K, 0.25 g of Fe2O3@RH composites, and a pH of 2. The maximum percentage removal of Acid Blue 25 was found to be 91%. Various linear and nonlinear kinetic and isothermal models were used in this study to emphasize the importance and necessity of the adsorption process. Adsorption isotherms such as the Freundlich, Temkin, Langmuir, and Dubinin–Radushkevich (D–R) models were applied. The results showed that all the isotherms were best fitted on the data, except the linear form of the D–R isotherm. Adsorption kinetics such as the intraparticle kinetic model, the Elovich kinetic model, and the pseudo-first-order and pseudo-second-order models were applied. All the kinetic models were found to be best fitted on the data, except the PSO model (types II, III, and IV). Thermodynamic parameters such as ΔG° (KJ/mol), ΔH° (KJ/mol), and ΔS° (J/K*mol) were studied, and the reaction was found to be exothermic in nature with an increase in the entropy of the system, which supported the adsorption phenomenon. The current study contributes to a comprehensive understanding of the adsorption process and its underlying mechanisms through characterization, the optimization of the conditions, and the application of various models. The findings of the present study suggest practical applications of this method in wastewater treatment and environmental remediation.