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April 22, 2026Advanced Energy Materials3 citationsOpen Access

Beyond Descriptor‐Based AI Design: Sp 2 ‐Hybridized Branched Side Chains Enable Pre‐Aggregation–Driven Seeding Effects in Green‐Solvent‐Processed Organic Solar Cells

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SJSeokhwan JeongDWDonghoo WonZSZhe Sun

Key Points

  • This work aims to explore the effects of sp2-hybridized branched side chains on molecular design in organic solar cells.
  • Introduced a YBOV non-fullerene acceptor with sp2-hybridized branched side chains.
  • Analyzed solution-state pre-aggregation effects on film formation in organic solar cells.
  • Compared device performance against benchmark L8-BO-based devices.
  • YBOV-based organic solar cells achieved efficiencies of up to 19.67%.
  • Devices exhibited a densely packed crystalline microstructure due to pre-aggregation effects.
  • Machine-learning predictions aligned closely with experimental results, highlighting the significance of pre-aggregation.

Abstract

ABSTRACT Descriptor‐based artificial intelligence (AI) has emerged as a paradigm for molecular design in organic solar cells (OSCs); however, it inherently overlooks collective effects governed by bond hybridization, intermolecular coupling, and aggregation thermodynamics. Such effects are encoded at the solution stage, where pre‐aggregation of photoactive materials dictates nucleation pathways, phase separation, and molecular ordering during film formation. Herein, we introduce a YBOV non‐fullerene acceptor featuring sp 2 ‐hybridized branched side chains that exhibit an unprecedentedly strong solution‐state pre‐aggregation propensity. This behavior translates into highly ordered solid films with a densely packed crystalline microstructure, enabled by a thermodynamically stabilized core–terminal dimer. As a result, incorporation of YBOV into OSCs not only outperforms the benchmark L8‐BO‐based device, but also confers an effective nucleation seeding‐agent function across diverse host OSC platforms, delivering efficiencies of up to 19.67% via green‐solvent processing by alleviating the intrinsic current–voltage trade‐off. Machine‐learning predictions largely match experimental photovoltaic parameters with a slight upward bias, except for open‐circuit voltage​, which exhibits anomalous behavior driven by pre‐aggregation–driven seeding effects beyond descriptor‐based AI. This work establishes sp 2 ‐hybridized branched side chains as a new molecular design principle, introducing pre‐aggregation‐enabled seeding effects beyond AI prediction and providing a universal strategy for high‐performance OSCs.

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Cite This Study

Jeong et al. (2026) studied this question.

synapsesocial.com/papers/69e865b56e0dea528ddea1f7https://doi.org/10.1002/aenm.70967
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