Machine-Learning-Assisted Investigation on Benign Ion Migration in Metal Halide Perovskites

Abstract

Defect-assisted ion migration is one of the important issues that results in instability and non-radiative losses in hybrid organic–inorganic metal halide perovskite solar cells. In this work, based on the deep potential (DP) model, a long-time-scale molecular dynamics (MD) simulation has been employed to capture the interstitial-assisted iodine migration process. The results indicate that, when interstitial iodine (I_i) begins to migrate, the serious structural distortion becomes mild, weakening the electron–vibration interaction. The deep trap state induced by the iodine trimer undergoes a “deep–shallow–deep” dynamic process, which ultimately leads to an improvement of the carrier lifetime during the interstitial-assisted iodine migration process. Our work confirms that different dynamic processes are strongly correlated in halide perovskites and demonstrates that ion migration, considered to be detrimental, can become benign in a particular case. The reported results provide new fundamental insight to improve the efficiency of CH₃NH₃PbI₃ perovskite solar cells.