Journal of Solid State Chemistry

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 cooling devices. The lattice constant , a, as the only variable parameter among the six parameters in the crystal structure, has a significant impact on the structural stability , bandgap structure, and thus materials performance. In this work, the Gaussian process regression (GPR) model is developed to elucidate the statistical relationship between ionic radii and lattice constants for cubic perovskite A 2 X Y 6 compounds. A total of 79 samples with lattice constants ranging from 8.109 Å to 11.790 Å are explored. The modeling approach demonstrates a high degree of accuracy and stability, contributing to efficient and low-cost estimations of lattice constants.

Machine learning lattice constants for cubic perovskite A2XY6 compounds