Silver nanoparticles embedded on magnetite-coated UiO-66 microspheres for enhanced nitroarene reduction

This study explores the synthesis and catalytic properties of silver nanoparticles (AgNPs) embedded on magnetite-coated UiO-66 microspheres (Fe3O4/UiO-66(Zr)/Ag) for efficiently converting 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). The inclusion of hollow Fe3O4 microspheres in the composite serves a dual purpose: enhancing catalytic activity and facilitating easy magnetic recovery. Concurrently, UiO66(Zr), with its high surface area, aids in the effective adsorption and loading of AgNPs, which act as the primary catalyst for the conversion of 4-NP to 4-AP. The combination of AgNPs, the Fe3O4 microstructure, and UiO-66 properties aims to enhance catalytic performance. The investigation into the effect of various experimental parameters revealed optimal conditions for maximum catalytic activity at an initial Ag+ concentration of 7.5 mM, a catalyst mass of 3 mg, pH 5, and a reaction temperature of 30 degrees C. Fe3O4/UiO-66/Ag exhibited superior performance with a reaction rate constant of 0.284 min(-1), surpassing Fe3O4/Ag, Fe3O4/UiO-66, and Fe3O4 by 2.3-fold, 83.5-fold, and 91.6-fold, respectively. The reduction mechanism involves sequential steps of adsorption, electron transfer, and synergistic interactions among catalytic components (Fe3O4, UiO-66, AgNPs). Crucially, AgNPs played a pivotal role in accelerating the electron transfer process, facilitating the reduction of 4-NP to 4-AP. Remarkably, the catalyst demonstrated not only excellent stability but also impressive recyclability, maintaining a conversion rate exceeding 92 % over five consecutive reuses. Metal leaching concentrations remained well within established safety thresholds for drinking water. Overall, Fe3O4/UiO-66/Ag emerges as a highly efficient and recyclable catalyst with promising applications in environmental remediation. (c) 2024 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights are reserved, including those for text and data mining, AI training, and similar technologies.