Discovery of temperature-induced stability reversal in perovskites using high-throughput robotic learning
Name
s41467-021-22472-x.pdf
Description
Published version
Size
2.56 MB
Format
Adobe PDF
Checksum (MD5)
40446dc2835861a21198547aa137093b
Author(s)
Zhao, Yicheng
Zhang, Jiyun
Xu, Zhengwei
Sun, Shijing
Langner, Stefan
Hartono, Noor Titan Putri
Heumueller, Thomas
Hou, Yi
Elia, Jack
Li, Ning
Date Issued
2021
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Citation
Zhao, Yicheng, Zhang, Jiyun, Xu, Zhengwei, Sun, Shijing, Langner, Stefan et al. 2021. "Discovery of temperature-induced stability reversal in perovskites using high-throughput robotic learning." Nature Communications, 12 (1).
Version
Final published version
Abstract
AbstractStability of perovskite-based photovoltaics remains a topic requiring further attention. Cation engineering influences perovskite stability, with the present-day understanding of the impact of cations based on accelerated ageing tests at higher-than-operating temperatures (e.g. 140°C). By coupling high-throughput experimentation with machine learning, we discover a weak correlation between high/low-temperature stability with a stability-reversal behavior. At high ageing temperatures, increasing organic cation (e.g. methylammonium) or decreasing inorganic cation (e.g. cesium) in multi-cation perovskites has detrimental impact on photo/thermal-stability; but below 100°C, the impact is reversed. The underlying mechanism is revealed by calculating the kinetic activation energy in perovskite decomposition. We further identify that incorporating at least 10 mol.% MA and up to 5 mol.% Cs/Rb to maximize the device stability at device-operating temperature (<100°C). We close by demonstrating the methylammonium-containing perovskite solar cells showing negligible efficiency loss compared to its initial efficiency after 1800 hours of working under illumination at 30°C.
MIT Department
Massachusetts Institute of Technology. Photovoltaic Research Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/S41467-021-22472-X
