Lattice Constant Prediction of Complex Cubic Peroveskite A2BCO6 using Extreme Learning Machine

Abstract

Double perovskite oxides have received a lot of interest in the last ten years because of their distinctive and adaptable material properties. Among the six parameters in the cubic structure, the lattice constant is the sole changeable parameter, which plays an important role in developing materials for particular technological applications and distinctively identifies the crystal structure of the material. In this paper, the extreme learning machine (ELM) is used to correlate the lattice constant of $A_2^{ + 2}BC{O_6}$ cubic perovskite compounds, such as their ionic radii, electronegativity, oxidation state, and lattice constant. We investigated 147 compounds with lattice constants between 7.700 and 8.890Å. The prediction method has a high level of accuracy and stability and provides accurate estimates of lattice constants.