The purpose of this study is to determine fundamental structure-solvent-property relationships in organic photovoltaic polymers (OPV’s), with the overarching goal of increasing the efficiency of OPV’s. A typical silicon-based photovoltaic plant outputs approximately 88,000 m2 of photovoltaic cells each year- about the size of 16 football fields. On the other hand, an organic photovoltaic printer will produce the same area in up to 10 hours. OPV’s are incredibly fast, cheap, and easy to produce relative to their inorganic counterparts, but fall short within the realm of efficiency; the 10% efficiency of OPV’s can hardly rival the ~40% efficiency of inorganic photovoltaic technology. If the efficiency of OPV’s can be increased, this will have a drastic impact on the competitive marketability of photovoltaic technology. This project aims at developing computational models to study the role of solvents in the self-assembly of polythiophenes during the printing process. These models are generated in GROMACS, a program that uses classical forces such as Coulombic or Van Der Waals forces, to predict how molecules will behave with time. This is problematic, however, for OPV’s, as key interactions occur on the quantum level, and new classical force fields, which are computationally very efficient, need to be altered in order to accurately calculate these interactions. A force field is being developed and refined by comparing our computational results with experimental results from the Pozzo Research Group within the Department of Chemical Engineering. Once these results are reliably consistent with each other, we can begin running simulations and gathering data regarding how OPV’s assemble in various environments. In particular, this poster explains a systematic methodology I have developed to use the GROMACS program to perform molecular dynamics (MD) simulations of single chain OPV’s in various solvents as well as simulations of bulk OPV’s in the melt state.