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申博渊教授课题组在Nat. Commun.上发表论文
发布时间:2023-11-21 点击:10

题目:

In situ Imaging of the Atomic Phase Transition Dynamics in Metal Halide Perovskites

作者:

Mengmeng Ma1,2, Xuliang Zhang1,2, Xiao Chen3, Hao Xiong3, Liang Xu1,2, Tao Cheng1,2, Jianyu Yuan1,2, Fei Wei3, Boyuan Shen1,2*

单位:

1Institute of Functional Nano & Soft Materials (FUNSOM), Soochow University, Suzhou, 215123, Jiangsu, PR China.

2Jiangsu Key Laboratory of Advanced Negative Carbon Technologies, Soochow University, Suzhou, 215123, Jiangsu, PR China.

3Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, PR China.

摘要:

Phase transition dynamics are an important concern in the wide applications of metal halide perovskites, which fundamentally determine the optoelectronic properties and stabilities of perovskite materials and devices. However, a more in-depth understanding of such a phase transition process with real atomic resolution is still limited by the immature low-dose electron microscopy and in situ imaging studies to date. Here, we apply an emergent low-dose imaging technique to identify different phase structures (α, β and γ) in CsPbI3 nanocrystals during an in-situ heating process. The rotation angles of PbI6 octahedrons can be measured in these images to quantitatively describe the thermal-induced phase distribution and phase transition. Then, the dynamics of such a phase transition are studied at a macro time scale by continuously imaging the phase distribution in a single nanocrystal. The structural evolution process of CsPbI3 nanocrystals at the particle level, including the changes in morphology and composition, is also visualized with increasing temperature. These results provide atomic insights into the transition dynamics of perovskite phases, indicating a long-time transition process with obvious intermediate states and spatial distribution that should be generally considered in the further study of structure-property relations and device performance.

影响因子:

17.694

分区情况:

一区

链接:

https://doi.org/10.1038/s41467-023-42999-5




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