Fig. 4 shows more detailed simulation results for the conhguration of Fig. 3A. 

Fig. 5 shows site dependent simulation results for the conhguration of Fig. 3A. 

Fig. 6 shows location dependent simulation results for the conhguration of Fig. 3A. 

Fig. 7 is a comparison between local and non-local modeling of recombination. 

Fig. 8 shows dependence of simulated J-V curves on disorder energy. 

Fig. 9 show dependence of simulated J-V curves on temperature. 

Fig. 10 shows mobility enhancement vs. wave function decay length. 

Fig. 11 shows the effect of the disorder parameter on / MMA s defined in the text. 

Fig. 12 shows the dependence of various components of the recombination rate prefactor on the disorder parameter. 

## DETAILED DESCRIPTION 

## I) Introduction 

In the past decades, tremendous progress has occurred in the held of disordered organic semiconductors. For example, organic light-emitting diodes (OLEDs), com posed of layers of amorphous organic thin him, have already entered the display and lighting markets. In order t o understand the physics and speed up further device development, it is crucial t o make use of device modeling techniques which can both describe the essential physics and be computationally efficient. 

For unipolar devices, various methods have been applied t o disordered organic semiconductor devices, including one-dimensional (ID) drift-diffusion (1D-DD) simu lations, three-dimensional Kinetic Monte Carlo (3D-KMC) simulations, one-dimensional master equation (1D-ME) simulations, and three-dimensional master-equation (SO ME) simulations. 1D-DD modeling is widely used for inorganic semiconductor d e vices. It has also been intensively used t o model organic semiconductor devices, because the method is relatively simple and fast. However, the method has various limitations. For example, it assumes the system t o be a continuous medium without explicitly including the details at the molecular level. These details are only implicitly 

