title: Synthesis of magnetic γ-Fe2O3-based nanomaterial for ultrasonic assisted dyes adsorption: Modeling and optimization.
abstract: γ-Fe2O3 nanoparticles were synthesized and loaded on activated carbon. The prepared nanomaterial was characterized by field emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDX), Fourier transforms infrared spectroscopy (FT-IR) and X-ray diffraction (XRD). The γ-Fe2O3 nanoparticle-loaded activated carbon (γ-Fe2O3-NPs-AC) was used as novel adsorbent for the ultrasonic-assisted removal of methylene blue (MB) and malachite green (MG). Response surface methodology and artificial neural network were applied to model and optimize the adsorption of the MB and MG in their individual and binary solutions followed by the investigation on adsorption isotherm and kinetics. The individual effects of parameters such as pH, mass of adsorbent, ultrasonication time as well as MB and MG concentrations in addition to the effects of their possible interactions on the adsorption process were investigated. The numerical optimization revealed that the optimum adsorption (>99.5% for each dye) is obtained at 0.02g, 15mgL(-1), 4min and 7.0 corresponding to the adsorbent mass, each dye concentration, sonication time and pH, respectively. The Freundlich, Langmuir, Temkin and Dubinin-Radushkevich isotherms were studied. The Langmuir was found to be most applicable isotherm which predicted maximum monolayer adsorption capacities of 195.55 and 207.04mgg(-1) for the adsorption of MB and MG, respectively. The pseudo-second order model was found to be applicable for the adsorption kinetics. Blank experiments (without any adsorbent) were run to investigate the possible degradation of the dyes studied in presence of ultrasonication. No dyes degradation was observed.
authors.affiliation: Chemistry Department, Yasouj University, Yasouj 75918-74831, Iran.
authors.forename: Arash
authors.initials: A
authors.lastname: Asfaram
authors.affiliation: Chemistry Department, Yasouj University, Yasouj 75918-74831, Iran. Electronic address: m_ghaedi@mail.yu.ac.ir.
authors.forename: Mehrorang
authors.initials: M
authors.lastname: Ghaedi
authors.affiliation: Department of Physics, Yasouj University, Yasouj 75918-74831, Iran. Electronic address: hajati@mail.yu.ac.ir.
authors.forename: Shaaker
authors.initials: S
authors.lastname: Hajati
authors.affiliation: Department of Polymer Engineering, Golestan University, Gorgan 49188-88369, Iran.
authors.forename: Alireza
authors.initials: A
authors.lastname: Goudarzi
keywords: Artificial neural network; Binary components; Derivative spectrophotometry; Response surface methodology; Ultrasound-assisted adsorption; γ-Fe(2)O(3)-NPs-AC