Predicting Perovskite Thin-Film Photovoltaic Performance from Photoluminescence Videos
info
Photovoltaics are a key technology to decarbonize the generation of energy. While perovskite thin-films are a promising option to build powerful next generation photovoltaics demonstrating high power conversion efficiencies, their manufacturing process remains unstable. We build a model that directly predicts the solar cell performance based on a video capturing the perovskite layer formation prior to finalizing the solar cell. This helps to uncover process insights that lead to a better scalable and more reliable production and facilitates experimentation, which may lead to overcoming the current commercialization hurdles faster.
Publication
4725570
Perovskite
1
https://helmholtz-imaging.de/apa-bold-title.csl
50
date
desc
1571
https://helmholtz-imaging.de/wp-content/plugins/zotpress/
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Klein, L., Ziegler, S., Laufer, F., Debus, C., Götz, M., Maier‐Hein, K., Paetzold, U. W., Isensee, F., & Jäger, P. F. (2023). Discovering Process Dynamics for Scalable Perovskite Solar Cell Manufacturing with Explainable AI. Advanced Materials, 2307160. https://doi.org/10.1002/adma.202307160
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