Enhancing antioxidant properties of CeO 2 nanoparticles with Nd 3+ doping: structural, biological, and machine learning insights

The antioxidant capabilities of nanoparticles are contingent upon various factors, including their shape, size, and chemical composition. Herein, novel Nd-doped CeO nanoparticles were synthesized and the neodymium content was varied to investigate the synergistic impact on the antioxidant properties...

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Bibliographic Details
Published in:Biomaterials science 2024-04, Vol.12 (8), p.2108-2120
Main Authors: Ceballos-Sanchez, Oscar, Navarro-López, Diego E, Mejía-Méndez, Jorge L, Sanchez-Ante, Gildardo, Rodríguez-González, Vicente, Sánchez-López, Angélica Lizeth, Sanchez-Martinez, Araceli, Duron-Torres, Sergio M, Juarez-Moreno, Karla, Tiwari, Naveen, López-Mena, Edgar R
Format: Article
Language:English
Subjects:
Anti-Bacterial Agents - chemistry
Anti-Bacterial Agents - pharmacology
Antioxidants - chemistry
Antioxidants - pharmacology
Nanoparticles - chemistry
Nanostructures
Neodymium
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Summary:The antioxidant capabilities of nanoparticles are contingent upon various factors, including their shape, size, and chemical composition. Herein, novel Nd-doped CeO nanoparticles were synthesized and the neodymium content was varied to investigate the synergistic impact on the antioxidant properties of CeO nanoparticles. Incorporating Nd induced changes in lattice parameters and significantly altered the morphology from nanoparticles to nanorods. The biological activity of Nd-doped CeO was examined against pathogenic bacterial strains, breast cancer cell lines, and antioxidant models. The antibacterial and anticancer activities of nanoparticles were not observed, which could be associated with the Ce /Ce ratio. Notably, the incorporation of neodymium improved the antioxidant capacity of CeO . Machine learning techniques were employed to forecast the antioxidant activity to enhance understanding and predictive capabilities. Among these models, the random forest model exhibited the highest accuracy at 96.35%, establishing it as a robust computational tool for elucidating the biological behavior of Nd-doped CeO nanoparticles. This study presents the first exploration of the influence of Nd on the structural, optical, and biological attributes of CeO , contributing valuable insights and extending the application of machine learning in predicting the therapeutic efficacy of inorganic nanomaterials.
ISSN:2047-4830
2047-4849
DOI:10.1039/D3BM02107F