Objective
Organic photovoltaics (OPVs) have gained a lot of attention as versatile and cheap alternatives to their inorganic counterparts. Great improvement has been made by tuning the electronic properties of donor, D, and acceptor, A, molecules. Equally important for high efficiency devices, is the morphology and orientation of D and A molecules in the active layer because: (1) excitons created upon absorption have a finite migration length (5-20 nm), D and A domains therefore have to be small and (2) both domains have to fully percolate the active layer in order to achieve efficient charge transport and collection at the electrodes. So far, the D-A morphology has mainly been optimized by altering processing methods, such as spin-casting, (organic) vapor phase deposition and vacuum thermal evaporation, and by post-deposition annealing (e.g. using solvent vapor and / or temperature).
Here we propose to encode the morphology directly into the chemical structure of the D and A molecules by using self-assembly. This way, molecular recognition between the molecules determines the morphology of the active layer. To this end, pyrene derivatives with enhanced π-π stacking have been reported, as well as molecules incorporating hydrogen-bonding motifs coupled to electronically active segments. These types of self-assembled devices had enhanced efficiency compared to their non-assembled analogues, and clearly show that self-assembly provides a new level of control over morphology.
In this project, we will use self-assembling D molecules bearing large π-π stacking motifs together with hydrogen bonding arrays to hierarchically organize both D and A molecules and creating a high interfacial area, while maintaining percolation. This way exciton diffusion and splitting will be facilitated, hole mobility will be enhanced by improved interconnection of D molecules and recombination will decrease, leading to higher power conversion efficiency.
Fields of science
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Topic(s)
Call for proposal
FP7-PEOPLE-2013-IEF
See other projects for this call
Funding Scheme
MC-IEF - Intra-European Fellowships (IEF)Coordinator
67081 Strasbourg
France