Parvindar M. Sah;Smita G. Gite;Harshala S. Naik;Ratnamala Sonawane;Julia Nadrowska;Patrycja Golińska;Rajesh W. Raut;Aniket K. Gade
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Ag-Doped ZnO Nanoparticles: A Versatile Multifunctional Nanomaterial for Anticancer, Antibacterial, and Recyclable Photocatalyst
Silver doping into zinc oxide nanoparticles (Ag-ZnO NPs) were prepared via the co-precipitation method. The XRD analysis revealed the hexagonal structure characteristic of ZnO nanoparticles. The diminishing intensity of the peaks in Ag-ZnO NPs’ XRD pattern indicated the successful incorporation of Ag metal within the ZnO lattice. Elemental composition validation was performed through energy-dispersive X-ray spectroscopy (EDX), while FTIR spectroscopy elucidated the functional groups present in both ZnO and Ag nanoparticles. A judicious approach of 3% silver doping was employed to overcome silver’s toxicity potential at higher concentrations. Remarkably, the Ag-ZnO NPs exhibited exceptional, reusable photocatalytic prowess over four cycles in the degradation of methylene blue. Furthermore, the Ag-ZnO NPs showcased potent antibacterial efficacy against select pathogens, including Escherichia coli ATCC 27853, Salmonella typhi CT18, Staphylococcus aureus NCTC8325, and Bacillus subtilis QST 713. Notably, these nanoparticles also exhibited significant anticancer activity against Hep-G2, a human hepatoma cell line. Silver-doped zinc oxide emerges as a promising asset against wastewater dye pollution and holds promising applications in liver cancer.
期刊介绍:
The IEEE Transactions on NanoBioscience reports on original, innovative and interdisciplinary work on all aspects of molecular systems, cellular systems, and tissues (including molecular electronics). Topics covered in the journal focus on a broad spectrum of aspects, both on foundations and on applications. Specifically, methods and techniques, experimental aspects, design and implementation, instrumentation and laboratory equipment, clinical aspects, hardware and software data acquisition and analysis and computer based modelling are covered (based on traditional or high performance computing - parallel computers or computer networks).