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Intragrain impurity annihilation for highly efficient and stable perovskite solar cells

  • Songhua Cai*
  • , Zhipeng Li
  • , Yalan Zhang
  • , Tanghao Liu
  • , Peng Wang
  • , Ming-Gang Ju*
  • , Shuping Pang*
  • , Shu Ping Lau
  • , Xiao Cheng Zeng
  • , Yuanyuan Zhou*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

31 Downloads (CityUHK Scholars)

Abstract

Intragrain impurities can impart detrimental effects on the efficiency and stability of perovskite solar cells, but they are indiscernible to conventional characterizations and thus remain unexplored. Using in situ scanning transmission electron microscopy, we reveal that intragrain impurity nano-clusters inherited from either the solution synthesis or post-synthesis storage can revert to perovskites upon irradiation stimuli, leading to the counterintuitive amendment of crystalline grains. In conjunction with computational modelling, we atomically resolve crystallographic transformation modes for the annihilation of intragrain impurity nano-clusters and probe their impacts on optoelectronic properties. Such critical fundamental findings are translated for the device advancement. Adopting a scanning laser stimulus proven to heal intragrain impurity nano-clusters, we simultaneously boost the efficiency and stability of formamidinium-cesium perovskite solar cells, by virtual of improved optoelectronic properties and relaxed intra-crystal strain, respectively. This device engineering, inspired and guided by atomic-scale in situ microscopic imaging, presents a new prototype for solar cell advancement. © The Author(s) 2024.

Original languageEnglish
Article number2329
JournalNature Communications
Volume15
Online published14 Mar 2024
DOIs
Publication statusPublished - 2024

Funding

Y.Z. acknowledges the Excellent Young Scientists Funds (No. 52222318) from the National Natural Science Foundation of China (NSFC) and the Early Career Scheme (No. 22300221) & General Research Fund (No. 12302822) from the Hong Kong Research Grants Council (RGC). Y.Z. also acknowledge the startup grant of the Hong Kong University of Science and Technology. S.C. acknowledges the startup grants from the Department of Applied Physics, the Hong Kong Polytechnic University (1-BD96, 1-BDCM), the General Research Fund (No. 15306122) & the Early Career Scheme (No. 25305023) from the Hong Kong RGC. M-G.J. acknowledges the General Program of NSFC (No. 22173019) and the Fundamental Research Funds for the Central Universities (No. 2242022R40072). Part of this TEM characterization was performed on the Hong Kong RGC-supported STEM facilities (No. C5029-18E). We acknowledge Z. Shao, C. Gao and W. Wang for the experimental assistance and Prof. Y. Xiang from HKUST for the valuable discussion on the theoretical calculations. We acknowlege the National Supercomputing Center of Tianjin and the Big Data Computing Center of Southeast University for providing the facility support on the materials computation. Y.Z. acknowledges the Excellent Young Scientists Funds (No. 52222318) from the National Natural Science Foundation of China (NSFC) and the Early Career Scheme (No. 22300221) & General Research Fund (No. 12302822) from the Hong Kong Research Grants Council (RGC). Y.Z. also acknowledge the startup grant of the Hong Kong University of Science and Technology. S.C. acknowledges the startup grants from the Department of Applied Physics, the Hong Kong Polytechnic University (1-BD96, 1-BDCM), the General Research Fund (No. 15306122) & the Early Career Scheme (No. 25305023) from the Hong Kong RGC. M-G.J. acknowledges the General Program of NSFC (No. 22173019) and the Fundamental Research Funds for the Central Universities (No. 2242022R40072). Part of this TEM characterization was performed on the Hong Kong RGC-supported STEM facilities (No. C5029-18E). We acknowledge Z. Shao, C. Gao and W. Wang for the experimental assistance and Prof. Y. Xiang from HKUST for the valuable discussion on the theoretical calculations. We acknowlege the National Supercomputing Center of Tianjin and the Big Data Computing Center of Southeast University for providing the facility support on the materials computation.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

RGC Funding Information

  • RGC-funded

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