Kinetic Monte Carlo Model of an Organic Solar Cell Calibrated by Experiments
Sebastian Wilken a, Tanvi Upreti a, Staffan Dahlström b, Gustav Persson c, Martijn Kemerink a
a Linköping University, Sweden, SE-581 83, Linköping, Sweden
b Åbo Akademi University, Finland, Porthaninkatu, 3, Turku, Finland
c Chalmers University of Technology, Sweden, Fysikgränd, 3, Gothenburg, Sweden
nanoGe Fall Meeting
Proceedings of nanoGe Fall Meeting19 (NGFM19)
#CharDy19. Charge Carrier Dynamics
Berlin, Germany, 2019 November 3rd - 8th
Organizers: Marcus Scheele and Maksym Yarema
Poster, Sebastian Wilken, 425
Publication date: 18th July 2019

Kinetic Monte Carlo (kMC) simulations have been proven to be a valuable tool to model transient extraction and mobility measurements on organic photovoltaics (OPVs) [1]. However, it is much more difficult and computationally demanding to model the key characteristic of any OPV device, its current-voltage (IV) curve under illumination. To describe a complete IV curve, the kMC model must also accurately describe the situation close to open-circuit conditions, i.e., when charge recombination and charge injection become significant. Here, we present a kMC model of a disordered OPV device that is thoroughly calibrated by independent experimental techniques. We find that it is crucial to make realistic assumptions on the morphology in the active layer, most notably the aggregation behavior, which is determined using transmission electron microscopy (TEM) and three-dimensional tomography. Another important parameter is the injection barrier height at the contacts. The injection barriers determine the background charge density in the device and, thus, the number of possible reaction partners available for nongeminate recombination. We combine charge extraction by linearly increasing voltage (CELIV) and bias-assisted charge extraction (BACE) experiments with a drift-diffusion simulator to calibrate the barrier height, which is then plugged into the kMC model. Notably, our model coherently describes transient absorption and IV measurements with the same set of input parameters. This allows us to make predictions of macroscopic device performance parameters like the open-circuit voltage and the fill factor based on microscopic material properties.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 799801.

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