Non-halogenated-blade-coating-triggered high-performance flexible large-area single-component organic solar cells: Flexible moiety-incorporated non-fully conjugated block copolymers with intrinsic non-halogenated-solvent-blade-coating window

초록

Single-component organic solar cells (SCOSCs) possess unique advantages in stability over multi-component ones (MCOSCs), yet their development in large-area blade-coating and flexible devices has progressed slowly, hampered by the typical trade-offs among efficiency, non-halogenated-solvent processability, and mechanical flexibility. Herein, we innovatively developed a new type of non-fully conjugated block copolymer (NF-CBC) PM6-b-PYIT-A with intrinsic non-halogenated-solvent-processability and mechanical robustness by integrating the strategy of synthesizing CBC via covalent linkage with flexible-moiety incorporation into the CBC backbone. Benefiting from suppressed aggregation behavior and extended nucleation/growth time, PM6-b-PYIT-5A exhibits superior compatibility with the broadened non-halogenated-solvent processing window. In contrast to the typical efficiency loss in the MCOSCs, the new NF-CBC PM6-b-PYIT-5A with flexible moiety achieved record power conversion efficiencies (PCEs) of 13.36% for small-area spin-coating devices and 12.05% for large-area blade-coating devices processed with non-halogenated solvents instead, significantly outperforming the reference PM6-b-PYIT with fully rigid backbones (12.80% and 10.60%). Moreover, the flexible moiety creates abetter stress-dissipation system, enabling outstanding stretchability with 80% PCE retention at 40.39% strain for PM6-b-PYIT-5A, far surpassing PM6-b-PYIT (22.46%). This work demonstrates that the synthetic strategy for NF-CBCs, coupled with non-halogenated-solvent processing, triggers a pronounced performance reversal in SCOSCs, thus harnessing the flexible moiety to enable high-performance, large-area, stretchable SCOSCs. (c) 2026 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. and Science Press. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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