Synthesis, Characterization, and Modeling of Reduced Graphene Oxide Supported Adsorbent for Sorption of Pb(II) and Cr(VI) Ions from Binary Mixture

Abstract

Graphene and its derivatives as multifunctional catalysts are in high demand, owing to their exceptional potential. Here, we synthesized Cu/Ni@rGO nanocomposite by using reduced graphene oxide (rGO) as a support which provided large surface area. A mixture of Cu and Ni nanoparticles (NPs) was embedded on its surface for sorption of heavy metal ions, i.e., Pb²⁺ and Cr⁶⁺, from binary mixture. Synthesis process of nanocomposite was monitored by UV-visible spectroscopy. FTIR analysis was performed to confirm the functional groups involved in synthesis and stabilization of the nanocomposite. The average size of nanocomposite was 26 nm calculated by XRD spectroscopy. SEM analysis revealed the thread-like structure of nanocomposite, while EDX gave information about elemental composition. Synthesized material was used to remove cations (Pb²⁺ and Cr⁶⁺) from binary mixture under tungsten lamp and without tungsten lamp. Under tungsten lamp, at 5 ppm concentration of binary mixture of cations, after 40 min of interaction with 10 mg adsorbent dosage at 45 °C temperature, 94% of cations was removed very efficiently. Thermodynamics studies showed that reaction of cations with nanocatalyst was spontaneous and exothermic in nature. Kinetics models were employed on experimental values and regression coefficient (R²) was near to unity (0.99) for pseudo 2nd order, which was considered the best fitted method for adsorption. Among sorption isotherms, the best fitted model was Freundlich isotherm as its R² value (0.97) is near to unity. On these adsorption isotherms, error analysis was also applied to attain precision on results. Reusability of material was analyzed 5 times by desorption process which confirmed its stability and higher catalytic efficiency.

Graphical Abstract