Development of Novel Imaging Techniques for Quality Control in Organic Solar Cell Manufacturing Using Artificially Introduced Defects.
André Karl a, Andres Osvet a, Ning Li a b, Christoph J. Brabec a b
a Institute of Materials for Electronics and Energy Technology (i-MEET), Friedrich-Alexander Universität Erlangen-Nürnberg,Germany, Martensstraße, 7, Erlangen, Germany
b Helmholtz-Institute Erlangen-Nürnberg for Renewable Energy (IEK-11), Egerlandstr. 3, Erlangen, 91058, Germany
Materials for Sustainable Development Conference (MATSUS)
Proceedings of nanoGe Fall Meeting19 (NFM19)
#OPV19. Organic Photovoltaics: recent breakthroughs, advanced characterization and modelling
Berlin, Germany, 2019 November 3rd - 8th
Organizers: Jörg Ackermann and Uli Würfel
Poster, André Karl, 359
Publication date: 18th July 2019

Organic photovoltaics (OPV) have recently made great strides in terms of efficiency with reports of increased PCEs of over 15 %. Such high efficiencies in combination with other attractive properties, for example the possibility for flexible substrates, semi-transparent devices or solution processability, make OPV increasingly attractive for larger scale industrial production, especially when considering specialized applications like building-integrated photovoltaics. However, in order to efficiently produce OPV cells or modules on a larger scale, quick and reliable quality control measures are crucial. One of the most widely used means for quality control is imaging of the radiative or non-radiative recombination of solar cells, namely (lock in) thermography (LIT) and luminescence imaging. These methods are limited in some respects. For example a determination of the lateral position of a defect is easily possible, while the exact resolution of the nature of a defect, e.g. in which layer of a thin film stack a defect is located, is challenging. Our approach to overcome this difficulty is the introduction of well-defined artificial defects into certain layers of an OPV stack and subsequent imaging analysis of the defected cells. The unique response gained from cells with artificial defects can then be transferred to the imaging of cells or modules with naturally occurring manufacturing defects.

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