Efficient Computational Screening of Organic Polymer Photovoltaics

There has been increasing interest in rational, computationally driven design methods for materials, including organic photovoltaics (OPVs). Our approach, focuses on a screening pipeline, using a genetic algorithm for first stage screening and multiple filtering stages for further refinement. An important step forward is to expand our diversity of candidate compounds, including both synthetic and property-based measures of diversity. For example, top monomer pairs from our screening are all donor-donor (D-D) combinations, in contrast with the typical donor-acceptor (D-A) motif used in organic photovoltaics. We also find a strong sequence effect, in which the average HOMO-LUMO gap of tetramers changes by similar to 0.2 eV as a function of monomer sequence (e.g., ABBA versus BAAB); this has rarely been explored in conjugated polymers. Beyond such optoelectronic optimization, we discuss other properties needed for high-efficiency organic solar cells, and applications of screening methods to other areas, including non-fullerene n-type materials, tandem cells, and improving charge and exciton transport.