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Abstract For advancing next‐generation optoelectronics, a versatile strategy for fabricating π‐conjugated polymer (π‐CP)/chiral‐small molecule (SM) hybrid films through co‐crystallization‐mediated chirality transfer is reported. The transfer of optical chirality from 1,1′‐binaphthyl–2,2′‐diamine (BN), a representative chiral inducer SM, to thin films of various achiral π‐CPs, including non‐fluorene π‐CPs, is achieved by simply blending the π‐CPs with BN using aromatic organic solvents. The resulting π‐CP/chiral‐SM hybrid films exhibit chiroptical responses at the main electronic absorption bands of various π‐CPs. Studies of the morphology, crystalline structure, and phase‐separation structure of a representative hybrid system of poly(3‐hexylthiophene) (P3HT) and BN reveal that these hybrid films exhibit a characteristic lamellar structure where the π‐CPs co‐crystallize with chiral BN molecules, facilitated by aromatic solvent‐assisted intermolecular π–π interactions. In‐depth photophysical analysis suggests that BN molecules co‐crystallized in the P3HT lamellar structure induce asymmetrically misaligned transition dipoles along the P3HT conjugated backbone, transferring optical chirality from BN to P3HT under circularly polarized light illumination. As a proof‐of‐concept, chiroptical photodiodes based on π‐CP/chiral‐SM hybrid films and printed micropatterns, exhibiting a distinguishable photocurrent response depending on the direction of circularly polarized light are successfully demonstrated. 

Abstract Conventional imaging and recognition systems require an extensive amount of data storage, pre-processing, and chip-to-chip communications as well as aberration-proof light focusing with multiple lenses for recognizing an object from massive optical inputs. This is because separate chips (i.e., flat image sensor array, memory device, and CPU) in conjunction with complicated optics should capture, store, and process massive image information independently. In contrast, human vision employs a highly efficient imaging and recognition process. Here, inspired by the human visual recognition system, we present a novel imaging device for efficient image acquisition and data pre-processing by conferring the neuromorphic data processing function on a curved image sensor array. The curved neuromorphic image sensor array is based on a heterostructure of MoS₂and poly(1,3,5-trimethyl-1,3,5-trivinyl cyclotrisiloxane). The curved neuromorphic image sensor array features photon-triggered synaptic plasticity owing to its quasi-linear time-dependent photocurrent generation and prolonged photocurrent decay, originated from charge trapping in the MoS₂-organic vertical stack. The curved neuromorphic image sensor array integrated with a plano-convex lens derives a pre-processed image from a set of noisy optical inputs without redundant data storage, processing, and communications as well as without complex optics. The proposed imaging device can substantially improve efficiency of the image acquisition and recognition process, a step forward to the next generation machine vision.