TY - JOUR
AU - Zhao, Yicheng
AU - Zhang, Jiyun
AU - Xu, Zhengwei
AU - Sun, Shijing
AU - Langner, Stefan
AU - Hartono, Noor Titan Putri
AU - Heumueller, Thomas
AU - Hou, Yi
AU - Elia, Jack
AU - Li, Ning
AU - Matt, Gebhard J.
AU - Du, Xiaoyan
AU - Meng, Wei
AU - Osvet, Andres
AU - Zhang, Kaicheng
AU - Stubhan, Tobias
AU - Feng, Yexin
AU - Hauch, Jens
AU - Sargent, Edward H.
AU - Buonassisi, Tonio
AU - Brabec, Christoph J.
TI - Discovery of temperature-induced stability reversal in perovskites using high-throughput robotic learning
JO - Nature Communications
VL - 12
IS - 1
SN - 2041-1723
CY - [London]
PB - Nature Publishing Group UK
M1 - FZJ-2021-02199
SP - 2191
PY - 2021
AB - 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.
LB - PUB:(DE-HGF)16
C6 - 33850155
UR - <Go to ISI:>//WOS:000640638000003
DO - DOI:10.1038/s41467-021-22472-x
UR - https://juser.fz-juelich.de/record/892610
ER -