Long Photocarrier Lifetimes in CsPbBr3 Films Deposited by Machine-learning-assisted IR-Laser Molecular Beam Epitaxy

Abstract

We investigated a machine-learning-assisted IR-laser molecular beam epitaxy (IR-MBE) process to extend the photocarrier lifetime of halide perovskite CsPbBr₃ films. In this method, the raw material powder placed in a vacuum is heated by pulsed IR laser irradiation, thereby depositing thin-film crystals on the heated substrate. A machine-learning approach was employed to explore the growth window that enhances the crystallinity of IR-MBE-grown CsPbBr₃ films and maximizes their functional properties. A closed-loop operation based on Bayesian optimization was performed to explore the growth window by autonomously tune three synthesis parameters: substrate temperature, nitrogen pressure, and deposition rate. Twenty trial depositions led to the detection of a growth window that drastically improved the crystallinity of the CsPbBr₃ film. When the CsPbBr₃ film was deposited under optimum conditions, the optical absorption rate of the excitons increased, and the photoluminiscence emission efficiency improved. Furthermore, time-resolved microwave photoconductivity measurements revealed a long photocarrier lifetime of 40.4 μs, which was comparable to that of bulk CsPbBr₃ single crystals, even though the CsPbBr₃ film was polycrystalline, revealing that the generation of defects that promote nonradiative recombination was suppressed. The IR-MBE method assisted by Bayesian optimization is a powerful synthetic process that improves the quality of halide perovskite films and maximizes their functional properties of the material itself.