Thermodynamic stability descriptor of A2BX6-type perovskite materials

The toxicity issue and unsatisfactory thermodynamic stability of Pb-based perovskites pose the most critical challenge for practical commercialization. Among the remaining alternatives, A(2)BX(6)-type vacancy ordered double perovskites have attracted significant attention. With the success achieved by A(2)BX(6)-type materials, the design of stable and non-toxic A(2)BX(6)-type materials has consistently remained a prominent concern. The incorporation of stability descriptors has played a crucial role in the design and exploration of conventional single and double perovskites. However, due to the significantly more relaxed arrangement exhibited by the octahedral structure of A(2)BX(6) compared to that of ABX(3) and A(2)B(1)B(3)X(6), traditional descriptors have proven ineffective in establishing a structure-stability relationship for A(2)BX(6). An explicit descriptor for the stability of A(2)BX(6)-type perovskite materials in this study has been developed through the utilization of symbolic regression algorithm. The accuracy of similar to 90 %, which is significantly higher than traditional stability descriptors, and also comparable to that of black-box machine learning models. The utilization of this efficient descriptor facilitates the design stable vacancy ordered double perovskite materials.