Organic photovoltaic (OPV) devices are considered to be a promising alternative technology to inorganic solar cells because they offer the possibility to be fabricated on large scales at a low production cost. Especially the concept of an intermixed Bulk-Heterojunction (BHJ) between organic donor and acceptor materials forms the basis for devices with high power conversion efficiencies (PCE) [1] because it allows to handle the separation of photo-generated excitons efficiently. Since it is a challenging task to investigate the morphology and the internal processes experimentally [2], simulations on different scales can be viable tools to guide the optimization of BHJ cells. One way to model organic solar cells is to solve the Drift-Diffusion (DD) equations. They offer an approach at a macroscopic continuum level, low computational effort, and with good agreement to experimental data [3]. A common approximation of DD simulations is the effective medium approach (EMA) [4], i.e. the lack of incorporation of the real blend morphology. In the EMA, donor and acceptor material are treated as one effective material. The donor/acceptor interfaces to split excitons into polaronic charges are assumed to be everywhere across the photoactive layer and no real exciton dynamics is considered. For this purpose, kinetic Monte Carlo (kMC) simulations offer a suitable tool to implement the desired morphology [5,6]. We have developed a fully functional kMC simulator for organic BHJ devices [7] that is able to generate intermixed morphologies after a spin-exchange algorithm and includes exciton and charge dynamics. Despite good reproduction of experimental measurements, the kMC method comes at very high computational cost and is not suitable to simulate large device structures or long virtual time periods. The morphology generated for the kMC simulations gives the possibility to be passed to the DD simulations to overcome the EMA and to establish a common basis for both simulations (Fig. 1). This allows to adequately compare the two methods and test how much of an approximation is made with the EMA.
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