Predicting charge transport properties in organic photovoltaic devices with coarse grained models

In this work we examine the structure-function relationships between chemical structure, morphology, and electronic properties in organic photovoltaic (OPV) devices. Understanding these relationships is critical to improving OPV device efficiency. We evaluate the limit to which we can predict charge transport properties of OPV devices using coarse-grained (CG) models, molecular dynamics simulations, and quantum chemical calculations. CG models allow us to access the relevant length and time scales required to study the nanostructure morphology of OPV active layers but they lack the fine-grained detail required to perform electronic structure calculations. We therefore use the CG to atomistic fine-graining capabilities of the MorphCT software package, so that we can conduct quantum chemical calculations to determine the charge transport properties of a variety of morphologies at different state points, to highlight processing conditions that are expected to produce the most efficient devices. In particular, we evaluate the efficacy of our high-throughput OPV device morphology screening for blends of poly(benzodithiophene-thienopyrrolo-dione) (pBDT-TPD) and phenyl C71 butyric acid methyl ester (PC71BM).