Beyond Descriptor-Based AI Design: Sp2-Hybridized Branched Side Chains Enable Pre-Aggregation-Driven Seeding Effects in Green-Solvent-Processed Organic Solar Cells

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 sp2-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 sp2-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.