Chemical Synthesis And Characterization Of Lanthanum Oxide Nanoparticle Extended By Machine Learning Prediction

Abstract

Low-cost co-precipitation method has used to synthesis the La₂O₃ nanoparticles at room temperature. The regression-based prediction model for estimating the optimal crystal size and respective strain has also presented. Energy Dispersive X-ray Spectroscopy (EDS), Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR) spectroscopy, and X-ray diffraction (XRD) were used to characterize the nanoparticles. With a particle size of 7.13nm and 7.92nm, a hexagonal structure has been formed, confirmed by XRD analysis. FTIR spectroscopy verified the existence of La-O stretching modes. The SEM images revealed the annealing effect on grain size and their agglomeration. The elemental composition of nanoparticles was determined by EDS analysis. The resulting nanoparticles morphology and properties were significantly influenced by the annealing temperature. Proposed method offersR²value of 0.9836 justifying the effectiveness of prediction.