Home /Research /Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells (Adv. Energy Mater. 48/2023)
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Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells (Adv. Energy Mater. 48/2023)

Jiyun Zhang, Bowen Liu, Ziyi Liu, Jianchang Wu, Simon Arnold, Hongyang Shi, Tobias Osterrieder, Jens Hauch, Zhenni Wu, Junsheng Luo, Jerrit Wagner, Christian Berger, Tobias Stubhan, F. Schmitt, Kaicheng Zhang, Mykhailo Sytnyk, Thomas Heumueller, Carolin M. Sutter‐Fella, Ian Marius Peters, Yicheng Zhao

Year
2023
Citations
4
Access
Open access

Abstract

Solution-Processed Perovskite Thin Films In article number 2302594, Jiyun Zhang, Yicheng Zhao, Christoph J. Brabec and co-workers develop a machine-learning-guided automated platform, the SPINBOT, to optimize solution-processed perovskite thin films. The platform efficiently explores an intricate multi-dimensional parameter space to produce high-quality and reproducible films. As a result, the optimized film achieves an impressive 21.6% PCE in solar cells under ambient conditions, along with excellent long-term stability.

Keywords

Perovskite (structure)Materials scienceThin filmStability (learning theory)Energy (signal processing)Parameter spaceArtificial intelligenceZhàngNanotechnologyOptoelectronics

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