Intrinsically Stretchable Neuromorphic Vision Arrays for Conformal Polarization Imaging and Adaptive Perception

Micro‑unmanned aerial vehicles urgently require compact, lightweight, and low‑power conformal vision modules capable of wide‑field imaging, polarization perception, and illumination‑adaptive processing. However, the monolithic integration of intrinsic stretchability, polarization sensitivity, and neuromorphic adaptation within a single deformable optoelectronic platform has remained a major challenge. Here, we report an intrinsically stretchable neuromorphic vision transistor array based on a semiconducting composite film consisting of an organic conjugated polymer (TDPP‑Se), CdSe/ZnS quantum dots (QDs), and an elastomeric SEBS matrix. The QDs significantly enhance photoresponsivity and enable gate‑tunable light adaptation, while shear‑aligned polymer chains yield strong polarization sensitivity with a high polarization ratio. The devices integrate sensing, memory, and in‑sensor computing with an ultralow energy consumption of ∼0.56 pJ per synaptic event, and retain stable multimodal performance under tensile strains up to 50%. When conformally laminated onto hemispherical substrates, the system achieves a mechanically tunable FOV from 53° to 149°. When the experimentally measured array responses are computationally mapped onto image preprocessing, the resulting vision framework achieves a classification accuracy of 95.6% under dynamic illumination, strong background interference, and large mechanical deformation. This work establishes a conformal neuromorphic vision platform for robust and energy-efficient artificial vision in micro-autonomous systems.

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Publication Details

Journal
Advanced Materials
Published
2026-10-05
DOI
https://doi.org/10.1002/adma.75254
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Intrinsically Stretchable Neuromorphic Vision Arrays for Conformal Polarization Imaging and Adaptive Perception

Haifeng Ling, Wenping Hu, Deyang Ji, Xianfeng Shen et al.
Advanced Materials
Advanced Memory and Neural Computing
article

Intrinsically Stretchable Neuromorphic Vision Arrays for Conformal Polarization Imaging and Adaptive Perception

Haifeng Ling, Wenping Hu, Deyang Ji, Xianfeng Shen, Shanshuo Liu, Huiqi Yang, Xin Gao, Haorui Zhang, Weiyu Wang, Xiaoying Zhang, Xiangxiang Li, Hui Yang
article en

Abstract

Micro‑unmanned aerial vehicles urgently require compact, lightweight, and low‑power conformal vision modules capable of wide‑field imaging, polarization perception, and illumination‑adaptive processing. However, the monolithic integration of intrinsic stretchability, polarization sensitivity, and neuromorphic adaptation within a single deformable optoelectronic platform has remained a major challenge. Here, we report an intrinsically stretchable neuromorphic vision transistor array based on a semiconducting composite film consisting of an organic conjugated polymer (TDPP‑Se), CdSe/ZnS quantum dots (QDs), and an elastomeric SEBS matrix. The QDs significantly enhance photoresponsivity and enable gate‑tunable light adaptation, while shear‑aligned polymer chains yield strong polarization sensitivity with a high polarization ratio. The devices integrate sensing, memory, and in‑sensor computing with an ultralow energy consumption of ∼0.56 pJ per synaptic event, and retain stable multimodal performance under tensile strains up to 50%. When conformally laminated onto hemispherical substrates, the system achieves a mechanically tunable FOV from 53° to 149°. When the experimentally measured array responses are computationally mapped onto image preprocessing, the resulting vision framework achieves a classification accuracy of 95.6% under dynamic illumination, strong background interference, and large mechanical deformation. This work establishes a conformal neuromorphic vision platform for robust and energy-efficient artificial vision in micro-autonomous systems.

Advanced Materials
Tianjin University (CN), Taiyuan Normal University (CN), Nanjing University of Posts and Telecommunications (CN), Shanxi Normal University (CN)
Openalex Percentile: Top 22%
Advanced Memory and Neural Computing
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