Unlocking the Potential of Mg-Doped Rare Earth Manganites: Machine Learning-Guided Synthesis and Insights into Structural and Optical Properties

Abstract

By leveraging machine learning insights from prior perovskite studies and employing the sol–gel method, we successfully synthesized two novel perovskite nanoceramics—M0.5 Ca0.25Mg0.25MnO3 (M = La, Pr)—as multifunctional nanomaterials. X-ray diffraction (XRD) confirmed their orthorhombic Pnma crystal structure. The Williamson–Hall method estimated average particle sizes of 59.5 nm for PCMMO and 21.8 nm for LCMMO, while the Scherrer method provided corresponding values of 32.59 nm and 20.43 nm. SEM, UV-Vis, and FTIR analyses validated the chemical composition, homogeneity, and optical properties of the synthesized compounds, revealing band gaps of 3.25 eV (LCMMO) and 3.71 eV (PCMMO) with Urbach energies of 0.29 eV and 0.26 eV, respectively. These findings provide valuable insights into the structural and optical properties of LCMMO and PCMMO, highlighting their potential as multifunctional materials for advanced device applications.