Mechanically Durable Intrinsically Stretchable Neuromorphic Devices via Molecular Microstructure Design

ABSTRACT Intrinsically stretchable neuromorphic devices (ISNDs) have been widely investigated for intelligent wearable on‐device computing. However, conventional material design strategies that soften the polymer conjugated moiety to impart stretchability have shown limited mechanical durability, typically 10 3 cycles at 50% strain, with severe electrical degradation. Here, we present a highly durable ISND that maintains stable electrical performance for up to 10 5 cycles at 50% strain, enabled by molecularly controlling chain stacking of the semiconducting polymer. This is achieved by incorporating a microstructure‐controlling moiety into the polymer backbone, which modulates the chain packing from a bundle‐like to a mesh‐like structure. The resulting mesh‐like morphology forms robust and long‐range percolation networks that preserve charge transport pathways and structural integrity under mechanical deformation. Utilizing this material, we fabricate ISNDs that exhibit device‐level stretchability of up to 150% and exceptional cyclic stability, with less than 15% variation in output current after 10 5 cycles at 50% strain. Furthermore, we demonstrate reliable on‐device artificial intelligence using reservoir computing, with consistent classification accuracy maintained even after 10 5 mechanical cycling at 50% strain. This work offers a molecular design strategy for tuning semiconductor film morphology, achieving mechanical reliability in stretchable neuromorphic electronics for future wearable and biomedical systems.