摘要
Based on 489 known perovskite-type complex oxides and a number of other type complex oxides, the pattern recognition-atomic parameter method is adopted to find regularities of the formation and the lattice distortion of the perovskite structure. It has been found that the restriction on Goldschmidt’s t factor constitutes only a necessary but not a sufficient condition to form perovskite-type compounds. A more effective mathematical model, which can precisely sum up the regularities of the formation, the lattice distortion, and the cell constants of known perovskite-type compounds and reliably make corresponding predictions on unknown compounds, can be set up by integrating multiple atomic parameters such as ionic radii, ionic valency, and Basanov’s electronegativity of constituent elements. Based on it, an intelligent database has been implemented. Its prediction accuracy is tested by eight newly discovered perovskite-type compounds such as Eu(Mn0.5 Ni0.5)O3, etc. (they are not included in the database
Based on 489 known perovskite-type complex oxides and a number of other type complex oxides, the pattern recognition-atomic parameter method is adopted to find regularities of the formation and the lattice distortion of the perovskite structure. It has been found that the restriction on Goldschmidt’s t factor constitutes only a necessary but not a sufficient condition to form perovskite-type compounds. A more effective mathematical model, which can precisely sum up the regularities of the formation, the lattice distortion, and the cell constants of known perovskite-type compounds and reliably make corresponding predictions on unknown compounds, can be set up by integrating multiple atomic parameters such as ionic radii, ionic valency, and Basanov’s electronegativity of constituent elements. Based on it, an intelligent database has been implemented. Its prediction accuracy is tested by eight newly discovered perovskite-type compounds such as Eu(Mn0.5 Ni0.5)O3, etc. (they are not included in the database during the test). The prediction results are in agreement with experimental facts.
基金
This work was supported by the "863" Program (Grant No. 863-511-945-005).