Machine learning lattice constants from ionic radii and electronegativities for cubic perovskite $$A_{2}XY_{6}$$ compounds
Sign Up to like & getrecommendations! Published in 2020 at "Physics and Chemistry of Minerals"
DOI: 10.1007/s00269-020-01108-4
Abstract: Metal halide perovskites have attracted great attention in the past decade due to unique and tunable optical and electrical properties, which are promising candidates for various applications such as solar cells, light-emitting diodes, and laser… read more here.
Keywords: perovskite compounds; radii electronegativities; lattice constants; ionic radii ... See more keywords
Probing the physical properties of M2LiCeF6 (M = Rb and Cs) double perovskite compounds for prospective high-energy applications employing the DFT framework
Sign Up to like & getrecommendations! Published in 2023 at "RSC Advances"
DOI: 10.1039/d3ra01451g
Abstract: Herein, the optoelectronic, structural, thermoelectric, and elastic characteristics of M2LiCeF6 (M = Rb and Cs) double perovskite compounds were investigated using ab initio modeling in the DFT framework. The Birch–Murnaghan fitting curve used for the… read more here.
Keywords: properties m2licef6; dft framework; energy; perovskite compounds ... See more keywords
Predictions of new AB O 3 perovskite compounds by combining machine learning and density functional theory
Sign Up to like & getrecommendations! Published in 2018 at "Physical Review Materials"
DOI: 10.1103/physrevmaterials.2.043802
Abstract: We apply machine learning (ML) methods to a database of 390 experimentally reported $AB{\mathrm{O}}_{3}$ compounds to construct two statistical models that predict possible new perovskite materials and possible new cubic perovskites. The first ML model… read more here.
Keywords: density functional; machine learning; perovskite compounds; functional theory ... See more keywords