| People | Locations | Statistics |
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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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Berson, Solenn
CEA LITEN
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (9/9 displayed)
- 2021Impact of interfaces on perovskite solar cell’s stability
- 2021A machine vision tool for facilitating the optimization of large-area perovskite photovoltaics
- 2020A Comparison of the Structure and Properties of Opaque and Semi-Transparent NIP/PIN-Type Scalable Perovskite Solar Cellscitations
- 2020A Comparison of the Structure and Properties of Opaque and Semi-Transparent NIP/PIN-Type Scalable Perovskite Solar Cellscitations
- 2014Synthesis, optoelectronic and photovoltaic properties of conjugated alternating copolymers incorporating 2,1,3-benzothiadiazole or fluorenone units: a comparative studycitations
- 2013Anatase colloidal solutions suitable for inkjet printing: Enhancing lifetime of hybrid organic solar cellscitations
- 2010A New Supramolecular Route for Using Rod-Coil Block Copolymers in Photovoltaic Applicationscitations
- 2009Efficient formation, isolation and characterization of poly(3-alkylthiophene) nanofibres: probing order as a function of side-chain length
- 2007The synthesis of regio-regular poly(3-alkyl-2,5-thienylene vinylene) derivatives using lithium bis(trimethylsilyl)amide (LHMDS) in the dithiocarbamate precursorcitations
Places of action
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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.