Separating microstructure-related from photo-induced degradation mechanisms in NFA based organic solar cells (Project 9)

• Applicant: Professor Dr. Christoph J. Brabec
• Subject Area: Synthesis and Properties of Functional Materials ; Experimental Condensed Matter Physics
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 461909888

Transition from fullerene based to non-fullerene-based acceptors (NFAs) has eliminated two major degradation processes in organic solar cells (OSCs): fullerene dimerization and fullerene diffusion. First experiments evidenced unprecedented device lifetime for selected NFA composites. P3HT:IDTBR solar cells were recently operated by our groups for over 25000 hrs continuously without obvious signs of degradation under 1 sun equivalent LED illumination and at temperatures below 40◦C. However, higher temperatures as well as UV / blue light are known to induce distinct degradation mechanisms in OSCs. Our recent investigations provided first in-sight into the mechanisms behind these degradation processes. We found a distinctly expressed wavelength dependence for photodegradation, which reached far into the 500 nm regime. More-over, we found that controlling the dimensionality and density of charge generating interfaces is a key parameter to enhanced thermal stability. Controlling the donor / NFA microstructure is of central importance to P9–Brabec/Li. Bulk heterojunction (BHJ) composites, bilayer (BL) as well as pseudo bilayer (PBL) solar cells will be made by conventional printing techniques, by layer transfer or by orthogonal solvent processing. This approach aims to control the active layer microstructure, giving us the ability to tune the device from a pure bilayer, through to an inter-diffused bilayer device and finally to an optimised bulk heterojunction in a controlled way. Thermal degradation as well as spectrally resolved photo induced degradation will be separately studied for these reference architectures and compared to the classical bulk heterojunction concept. Degradation of partially finished solar cell stacks will allow to investigate interactions between neighbouring layers and help identify the leading degradation mechanisms. Machine Learning Techniques will correlate the data from various characterization techniques as absorption, transient PL and electrical measurements to provide a predictive framework for organic photovoltaic (OPV) stability investigations. Based on the knowledge gained in this project, several strategies will be employed to mitigate thermal as well as photo-chemical degradation and to fabricate highly stable lab scale devices.

• DFG Programme: Research Units
• Subproject of: FOR 5387: Printed & Stable Organic Photovoltaics from Non-Fullerene Acceptors
• Co-Investigator: Dr. Ning Li