A graph-based formulation for computational characterization of bulk heterojunction morphology

To improve the efficiency of organic solar cells, it is essential to understand the role of morphology and to tailor fabrication process to get desired morphologies. In this context, a comprehensive set of computational tools to quantify and classify the 2D/3D heterogeneous internal structure of thin films is invaluable. We present a graph-based framework to efficiently compute a broad suite of physically meaningful morphology descriptors. These morphology descriptors are further classified according to the physical subprocesses within OSCs - photon absorption, exciton diffusion, charge separation, and charge transport. This approach is motivated by the equivalence between a discretized 2D/3D morphology and a labeled, weighted, undirected graph. We utilize this approach to pose six key questions related to structure characterization. These questions are the basis for a comprehensive suite of morphology descriptors. To advocate the appropriateness of the formulated suite, we correlate these morphology descriptors with analysis using a excitonic-drift-diffusion-based device model. A very high correlation between the fast graph-based approach and computationally intensive full scale analysis illustrates the potential of our formulation to rapidly characterize a large set of morphologies. Finally, our approach is showcased by characterizing the effect of thermal annealing on time-evolution of a model thin film morphology.