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2021 Nat. Commun., Stability Reversal in Perovskites! German Research about Temperature Using Robotic Learning

Top-Notch Due to It’s Precision!

  Nature Communications (IF 14.919) publishes a study from the University of Erlangen-Nuremberg, Germany. The research team discovered temperature-induced stability reversal in perovskites through high-throughput robotic learning.

  Perovskite materials have opened up new avenues for high-performance optoelectronic devices, among which FAPbI3-based polycation perovskites have attracted much attention due to their excellent optoelectronic properties. In this study, the research team used high-throughput techniques coupled with robotic learning to analyze the stability of multi-cations perovskites. After analysis, the research team found that the effect of the organic: inorganic cation ratio was reversed when the aging temperature was lowered below 100 °C. Specifically, organic cations (e.g. MA) are actually stability enhancers, while inorganic cations (e.g. Cs/Rb) are stability killers below 100 °C. The authors define this phenomenon as stability reversal in perovskites, which is further translated to device stability.

Workflow of the high-throughput robotic system

  The research team used a high-throughput robot (HTRobot) combined with machine learning to evaluate the photothermal stability of mixed-cation perovskites under different aging conditions. In the figure below, (a) is the crystal structure of ABX3 perovskite, where A represents a monovalent cation, B represents lead, and X represents a halide. In this study, FAPbI3 was used as the host material, followed by methylammonium (MA), cesium (Cs), rubidium (Rb), and potassium (K) as combined cations. As shown in Figure (b) below, the HTRobot system starts with a small amount of mother liquor, which was automatically mixed to form the desired precursor before stability testing. The detailed workflow was shown in Figure (c) below. HTRobot automatically synthesized materials, and in total, more than 1,000 samples were manufactured.

Perovskite Stability Reversal high-throughput robotic system

  The research team used a solar simulator, a quantum efficiency measurement system of Enlitech and other instruments for analysis. The results showed that at high aging temperatures, increasing organic cations (such as methylammonium) or decreasing inorganic cations (such as cesium) in multi-cation perovskites adversely affects light/thermal stability; but below 100°C, the effect was reversed. The research team further confirmed that combining at least 10 mol.% MA and up to 5 mol.% Cs/Rb maximized device stability at device operating temperatures (<100°C). Under illumination at 30°C, methylammonium-containing perovskite solar cells show negligible loss in efficiency compared to the initial efficiency after 1800 hours of operation.

  In addition to the EQE (External Quantum Efficiency) spectral analysis of solar cells, the Quantum Efficiency Measurement System of Enlitech also provides a Jsc (short-circuit current density) comparison for the short-circuit current of solar cells under a solar simulator to prove the authenticity of the experiment.

Perovskite EQE External quantum efficiency Stability Reversal robotic learning

(a) External quantum efficiency (EQE) of CsxMA0.15-xFA0.85PbI3 perovskite solar cells.

Perovskite J-V PCE robotic learning Solar Cells
(b) Current density-voltage (J-V) curves of FAPbI3 and CsxMA0.15-xFA0.85PbI3 (x = 0, 5, 10, and 15%) perovskite solar cells.

Recommended Instruments: QE-R Quantum Efficiency Measurement System

Keywords: Perovskite, stability reversal, high-throughput robotic learning, Quantum Efficiency

Article link: https://www.nature.com/articles/s41467-021-22472-x

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Perovskite Stability Reversal Temperature Robotic Learning EQE

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