Metal-to-semiconductor transitions and optical properties of ReNiO3 superlattices: An integration of first-principles calculations and machine learning analysis

Abstract

Engineering the physical properties of rare-earth nickelates (ReNiO3) through superlattice engineering is a highly promising approach. This study focuses on the electronic configurations and optical properties of SrTiO3/ReNiO3 superlattices, with the integration of the first-principles calculations and machine learning analysis. Across the rare-earth elements from light to heavy, the SrTiO3/ReNiO3 superlattice displays a metal-to-semiconductor transition, with their band gaps diminishing as the thickness of the ReNiO3 layers increases. The machine learning analysis identify the thickness of the superlattice and the interface strain as key determinants of the band gaps. Additionally, the optical absorption is positive with the band gap and the in-plane lattice constants, whereas negative with the superlattice thickness. The optical reflectivity shows positive with the ReNiO3 lattice constants, and negative with the valence electrons number of rare earth elements. Our study may help to design and optimize SrTiO3/ReNiO3 superlattice materials with desired electronic and optical characteristics.