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The Innovation Materials > 2026 Vol. 4 > No. 3 > 100226
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AI-guided stability design for perovskite photovoltaics

  • 1.

    Forschungszentrum Jülich, Helmholtz-Institute Erlangen-Nürnberg (HI ERN), Department of High-Throughput Methods in Photovoltaics, Erlangen 91058, Germany

  • 2.

    Institute of Materials Data Science and Informatics (IMD-3), Forschungszentrum Jülich, Erlangen 91058, Germany

  • 3.

    Institute of Materials for Electronics and Energy Technology (i-MEET), Department of Materials Science and Engineering, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen 91058, Germany

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  • Corresponding author: jiyun.zhang@fau.de
  • Received Date:  May 28, 2026
    Accepted Date:  July 10, 2026
    Published Online:  July 16, 2026
The Innovation Materials  4(3),  https://doi.org/10.59717/j.xinn-mater.2026.100226  |  Cite this article
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    • REFERENCES
  • [1] Guo J., Li B., Zhang Z., et al. (2026). AI-guided design of efficient perovskite solar cells operationally stable at 100°C. Science 392:724−728. DOI:10.1126/science.aef1620

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    [2] Gao D., Lu S., Zhang C., et al. (2026). Autonomous closed-loop framework for reproducible perovskite solar cells. Nature 653:707−714. DOI:10.1038/s41586-026-10482-y

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    [4] Zhang J., Hauch J. A. and Brabec C. J. (2024). Toward self-driven autonomous material and device acceleration platforms (AMADAP) for emerging photovoltaics technologies. Acc. Chem. Res. 57:1434−1445. DOI:10.1021/acs.accounts.4c00095

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  • Cite this article:

    Zhang J. (2026). AI-guided stability design for perovskite photovoltaics. The Innovation Materials 4:100226. https://doi.org/10.59717/j.xinn-mater.2026.100226
    Zhang J. (2026). AI-guided stability design for perovskite photovoltaics. The Innovation Materials 4:100226. https://doi.org/10.59717/j.xinn-mater.2026.100226

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