Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/43496
Title: | Ultrasonic spray coating for the scalable fabrication of Perovskite-on-Chalcogenide monolithic tandem Devices: Approaching the 20% efficiency | Authors: | SILVANO, Joao BIRANT, Gizem ORIS, Tim D'HAEN, Jan DEFERME, Wim VERMANG, Bart |
Issue Date: | 2024 | Publisher: | PERGAMON-ELSEVIER SCIENCE LTD | Source: | SOLAR ENERGY, 277 (Art N° 112738) | Abstract: | The combination of perovskite and chalcogenide solar cells allows for the monolithic fabrication of all-thin-film tandem with compositional tunability, facilitating optimal band gap alignment for an efficient absorption of the sunlight spectrum, while empowering flexible photovoltaic applications. However, this combination is yet to reach the levels of efficiency and production scalability seen in perovskite/silicon tandems, mostly due to the challenging fabrication of perovskite cells on top of the irregular chalcogenide cell surface. Herein, we propose to enhance the scalability of the technology by developing the ultrasonic spray coating of perovskite on top of Cu(In,Ga)S(Se) (CIGS) cells for the fabrication of monolithic tandem devices. The capability of the technique to deposit conformal perovskite coatings, aligned with interlayer optimization, results in the successful integration of perovskite and chalcogenide cells. The resulting monolithic tandem devices exhibit efficiencies close to 20%, a significant improvement on the efficiency of the single junction perovskite and CIGS reference cells. These results offer a promising pathway towards the upscaling of perovskite/CIGS device fabrication. | Notes: | Birant, G; Vermang, B (corresponding author), Imec Partner Solliance, Kapeldreef 75, B-3000 Leuven, Belgium. gizem.birant@imec.be; bart.vermang@uhasselt.be |
Document URI: | http://hdl.handle.net/1942/43496 | ISSN: | 0038-092X | e-ISSN: | 1471-1257 | DOI: | 10.1016/j.solener.2024.112738 | ISI #: | 001270607800001 | Rights: | 2024 International Solar Energy Society. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
ee.pdf Restricted Access | Published version | 0 B | Adobe PDF | View/Open Request a copy |
ACFr.pdf Until 2025-01-15 | Peer-reviewed author version | 2.15 MB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.