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 2 nanoparticles were synthesized and the neodymium content was varied to investigate the synergistic impact on the antioxidant properties of CeO 2 nanoparticles. Incorporating Nd 3+ induced changes in lattice parameters and significantly altered the morphology from nanoparticles to nanorods. The biological activity of Nd-doped CeO 2 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 3+ /Ce 4+ ratio. Notably, the incorporation of neodymium improved the antioxidant capacity of CeO 2 . 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 2 nanoparticles. This study presents the first exploration of the influence of Nd 3+ on the structural, optical, and biological attributes of CeO 2 , contributing valuable insights and extending the application of machine learning in predicting the therapeutic efficacy of inorganic nanomaterials.