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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Cros, Stéphane
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (7/7 displayed)
- 2023ALD-grown tin oxide as an electron selective layer for perovskite/silicon tandem cellscitations
- 2023Elucidating Interfacial Limitations Induced by Tin Oxide Electron Selective Layer Grown by Atomic Layer Deposition in N−I−P Perovskite-Based Solar Cellscitations
- 2022Nanocomposite coatings based on polyvinyl alcohol and montmorillonite for high-barrier food packagingcitations
- 2021A machine vision tool for facilitating the optimization of large-area perovskite photovoltaics
- 2014Interlaboratory indoor ageing of roll-to-roll and spin coated organic photovoltaic devices: Testing the ISOS testscitations
- 2014Structural properties of ultraviolet cured polysilazane gas barrier layers on polymer substratescitations
- 2012Optimization of PVA clay nanocomposite for ultra-barrier multilayer encapsulation of organic solar cells.
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article
A machine vision tool for facilitating the optimization of large-area perovskite photovoltaics
Abstract
e report a fast, reliable and non-destructive method for quantifying the homogeneity of perovskite thin films over large areas using machine vision. We adapt existing machine vision algorithms to spatially quantify multiple perovskite film properties (substrate coverage, film thickness, defect density) with pixel resolution from pictures of 25 cm 2 samples. Our machine vision tool—called PerovskiteVision—can be combined with an optical model to predict photovoltaic cell and module current density from the perovskite film thickness. We use the measured film properties and predicted device current density to identify a posteriori the process conditions that simultaneously maximize the device performance and the manufacturing throughput for large-area perovskite deposition using gas-knife assisted slot-die coating. PerovskiteVision thus facilitates the transfer of a new deposition process to large-scale photovoltaic module manufacturing. This work shows how machine vision can accelerate slow characterization steps essential for the multi-objective optimization of thin film deposition processes.