Zhao Y, Hauch J, Zhang J, Xu Z, Sun S, Langner S, Hartono NTP, Heumüller T, Hou Y, Elia J, Li N, Matt G, Du X, Meng W, Osvet A, Zhang K, Stubhan T, Feng Y, Sargent EH, Buonassisi T, Brabec C (2021)
Publication Type: Journal article
Publication year: 2021
Book Volume: 12
Article Number: 2191
Journal Issue: 1
DOI: 10.1038/s41467-021-22472-x
Stability 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.
APA:
Zhao, Y., Hauch, J., Zhang, J., Xu, Z., Sun, S., Langner, S.,... Brabec, C. (2021). Discovery of temperature-induced stability reversal in perovskites using high-throughput robotic learning. Nature Communications, 12(1). https://doi.org/10.1038/s41467-021-22472-x
MLA:
Zhao, Yicheng, et al. "Discovery of temperature-induced stability reversal in perovskites using high-throughput robotic learning." Nature Communications 12.1 (2021).
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