Intrinsically stretchable all-polymer neuromorphic visual adaptive transistors based on multidimensional-phase-separation-induced micromesh

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Authors: Chengyu Wang, Mingcong Qin, Jianzhe Sun, Yangshuang Bian, Mingliang Zhu, Wenkang Shi, Jiaxin Hong, Yanyan Cao, Yiran Liu, Zhiyuan Zhao, Yunqi Liu, Yunlong Guo
Cited by: 1
References: 79

Abstract

Stretchable neuromorphic optoelectronics requiring real-time perception and dynamic adaptive processing create tempting opportunities for wearable intelligent vision equipment. Existing bionic vision devices often lack scale-modulus deformable photosensitive materials and exhibit redundant manufacturing for complex structures to integrate optical neurofunctions, highlighting a critical gap in achieving both ductility and multifunctionality. Herein, we propose a defect-tunable viscoelastic photosensitive bulk-heterojunction based on multidimensional-phase-separation-induced micromesh for all-organic intrinsically stretchable neuromorphic visual adaptive transistors. The resultant devices demonstrate maintained high photosensitivity and multimodal broad-wavelength photoadaptation even under 100% biaxial mechanical strain. Notably, a record-ultrafast adaptive time down to 0.4 s is achieved by the all-organic intrinsically stretchable visual adaptive transistors, allowing a high energy-saving ratio of 88.4%. Moreover, a low paired-pulse depression index down to 44.37% is also accomplished, exhibiting the ability of abnormal discharges reduction and normal neural network function restore. The superior bionic visual adaptive systems allowing detailed time-varying intelligent information conversion, can realize highly misleading encrypted wireless optical communications. Furthermore, contrast vision-adaptive pixels are successfully constructed to avoid element absence for advanced driving assistance systems simulation in extreme environments. This technology promises to advance skin-like neuromorphic vision systems for applications including visual cryptography, bioinspired robots and unmanned intelligence.

Fields of Study & Subjects

Advanced Sensor and Energy Harvesting Materials Advanced Materials and Mechanics Advanced Memory and Neural Computing

Publication details

Journal / source
Nature Communications
Publisher
Springer Science and Business Media LLC
Volume
17
Issue
1
Publication date
14 February 2026
Language
EN