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 ∼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.