Colloidal Synthesis of Air-Stable CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> Quantum Dots by Gaining Chemical Insight into the Solvent Effects

Feng Zhang, Sheng Huang, Peng Wang, Xiaomei Chen, Suling Zhao, Yuping Dong, Haizheng Zhong

Chemistry of Materials · 2017 · 231 citations · 51 references

Concepts

Abstract

Because of the superior optical properties and potential applications in display technology, colloidal synthesis of halide perovskite quantum dots has been intensively studied. Although great successes have been made in the fabrication of green emissive CH 3 NH 3 PbBr 3 quantum dots, the fabrication of stable iodide-based CH 3 NH 3 PbI 3 quantum dots remains a great challenge because of their sensitivity to moisture in the open air. Even in a glovebox, the colloidal CH 3 NH 3 PbI 3 quantum dots obtained from N, N -dimethylformamide suffer from instability caused by fast degradation within days to weeks. In this work, we investigated the interactions between perovskite precursors and various polar solvents as well as their influence on the crystallization of CH 3 NH 3 PbI 3 in reprecipitation synthesis. By gaining chemical insight into the coordination effects, we can explain the degradation of CH 3 NH 3 PbI 3 to the defective crystals with coordinated solvents on the surface and/or intrinsic inner iodine vacancies. On the basis of this understanding, we fabricated air-stable CH 3 NH 3 PbI 3 quantum dots with a tunable size from 6.6 to 13.3 nm by selecting noncoordinated acetonitrile as a good solvent through ligand-assisted precipitation synthesis. The fabrication can be processed under ambient conditions, and the resulting CH 3 NH 3 PbI 3 quantum dots exhibit tunable emission with high photoluminescence quantum yields (maximum of ∼46%) as well as good stability. Moreover, the quantum confinement effects in CH 3 NH 3 PbI 3 quantum dots were discussed by correlating the size-dependent photoluminescence properties with theoretical calculations, which can be described by the infinite quantum well approximation model.

References

51