Descriptor‐Guided Computational Screening of Non‐Fullerene Acceptor Cores for Organic Solar Cells
Kun‐Han Lin, J. Terence Blaskovits, Wenlan Liu, Shu‐Yi Hu, Kuei‐Jhong Lin, Sandeep Sharma, Julien Gorenflot, Martin Heeney, Frédéric Laquai, Denis AndrienkoABSTRACT
Non‐fullerene acceptors (NFAs) have propelled organic photovoltaic efficiencies toward 21%, yet their modular acceptor–donor–acceptor chemistry creates a vast combinatorial design space that calls for efficient prescreening. Here we establish a computation‐driven screening workflow and apply it to over 4000 optimized A–B–(D–S)–B–A NFA molecules assembled from experimentally reported building blocks. Using a sequential set of device‐relevant criteria – suppressed dipole moment, a target quadrupole for efficient charge separation, trap‐free electron transport, sufficient interfacial energetic driving force, strong visible‐light absorption, and a sufficiently large photovoltaic gap – we downselect from over 4000 to the top 10 NFA candidates for common polymer donors (P3HT, PBDB‐T, PBDB‐T‐2F, and PBDB‐T‐SF). The top candidates recover established high‐performance motifs, including Y6‐type structures and an O‐IDTBR‐like candidate, supporting the validity of the descriptor set. Statistical analysis further reveals a clear division of control: donor building blocks primarily determine ionization energies, acceptor/end groups determine electron affinities, and the quadrupole moment provides a broadly tunable electrostatic handle that is only weakly correlated with frontier orbital energetics. Comparison to synthesized reference NFAs shows good agreement for thin‐film electronic and optical properties, while device performance highlights the importance of morphology beyond descriptor‐based prescreening.