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  5. Flash‐Lamp Processing of Charge Extraction Layers for Polymer Solar Cells

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Article
en
2022

Flash‐Lamp Processing of Charge Extraction Layers for Polymer Solar Cells

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en
2022
Vol 9 (28)
Vol. 9
DOI: 10.1002/admi.202201150

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Ulrich Sigmar Schubert
Ulrich Sigmar Schubert

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Aurelien Sokeng Djoumessi
Jose Prince Madalaimuthu
Shahidul Alam
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Abstract

Abstract Thermal annealing (TA) is one of the most used processing techniques for the fabrication of polymer solar cells. The method is not only used to dry solution‐processed films but also for improving the electrical conductivity and the optical absorption of the materials after coating as films. Its use is questionable in combination with high throughput manufacturing techniques such as roll‐to‐roll large‐scale production since annealing times of several minutes already put up high demands on oven lengths. Furthermore, the commonly used flexible substrates are not compatible with high processing temperatures. Therefore, there is a need for more rapid treatment techniques, which do not negatively affect the plastic substrate. Herein, it is successfully demonstrated that flash lamp annealing (FLA) can be a valid alternative to TA. The FLA technique is applied at various pulse durations and thus energy doses to PEDOT:PSS and SnO 2 films used as charge extraction layers in conventional and inverted solar cells architectures. In combination with PM6:Y6 photoactive layer, the obtained device's performances are comparable or even better than the devices treated with the classical TA on a hotplate. In terms of energy efficiency, the FLA is clearly more efficient than the TA, even at the size of prototypes.

How to cite this publication

Aurelien Sokeng Djoumessi, Jose Prince Madalaimuthu, Shahidul Alam, Aman Anand, Anastasia Sichwardt, Peter Fischer, Roland Rösch, Ulrich Sigmar Schubert, Harald Hoppe (2022). Flash‐Lamp Processing of Charge Extraction Layers for Polymer Solar Cells. , 9(28), DOI: https://doi.org/10.1002/admi.202201150.

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Publication Details

Type

Article

Year

2022

Authors

9

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/admi.202201150

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