Resolving Atomic‐Scale Interactions in Nonfullerene Acceptor Organic Solar Cells with Solid‐State NMR Spectroscopy, Crystallographic Modelling, and Molecular Dynamics Simulations. Issue 6 (22nd December 2021) - R. Luginbuhl, Benjamin; Raval, Parth; Pawlak, Tomasz; Du, Zhifang; Wang, Tonghui; Kupgan, Grit; Schopp, Nora; Chae, Sangmin; Yoon, Sangcheol; Yi, Ahra; Jung Kim, Hyo; Coropceanu, Veaceslav; et al.
Abstract: Fused‐ring core nonfullerene acceptors (NFAs), designated "Y‐series, " have enabled high‐performance organic solar cells (OSCs) achieving over 18% power conversion efficiency (PCE). Since the introduction of these NFAs, much effort has been expended to understand the reasons for their exceptional performance. While several studies have identified key optoelectronic properties that govern high PCEs, little is known about the molecular level origins of large variations in performance, spanning from 5% to 18% PCE, for example, in the case of PM6:Y6 OSCs. Here, a combined solid‐state NMR, crystallography, and molecular modeling approach to elucidate the atomic‐scale interactions in Y6 crystals, thin films, and PM6:Y6 bulk heterojunction (BHJ) blends is introduced. It is shown that the Y6 morphologies in BHJ blends are not governed by the morphology in neat films or single crystals. Notably, PM6:Y6 blends processed from different solvents self‐assemble into different structures and morphologies, whereby the relative orientations of the sidechains and end groups of the Y6 molecules to their fused‐ring cores play a crucial role in determining the resulting morphology and overall performance of the solar cells. The molecular‐level understanding of BHJs enabled by this approach will guide the engineering of next‐generation NFAs for stable and efficient OSCs. Abstract : The combined results from solid‐state NMR, crystallography, and modelling techniques highlight key differences in the Y6 morphology in PM6:Y6 blends cast from different solvents, which lead to different power conversion efficiencies in solar cells. By interpreting the experimental data step‐by‐step and using the results from each step, a more complete understanding of the underlying fundamental processes is reached.