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Carbon Nanotube Optoelectronic Synapse Transistor Arrays with Ultra‐Low Power Consumption for Stretchable Neuromorphic Vision Systems

Tanghao Xie, Qinan Wang, Min Li, Yuxiao Fang, Gang Li, Shuangshuang Shao, Wenbo Yu, Suyun Wang, Weibing Gu, Chun Zhao, Minghua Tang, Jianwen Zhao

2023Advanced Functional Materials63 citationsDOI

Abstract

Abstract High‐performance stretchable optoelectronic synaptic transistor arrays are key units for constructing and mimicking simulated neuromorphic vision systems. In this study, ultra‐low power consumption and low‐operation‐voltage stretchable all‐carbon optoelectronic synaptic thin film transistors (TFTs) using sorted semiconducting single‐walled carbon nanotubes (sc‐SWCNTs) modified with CdSe/ZnS quantum dots as active layers on ionic liquid‐based composite elastomer substrates are first reported. The resulting stretchable TFT devices show enhancement‐mode characteristics with excellent electrical properties (such as the record on/off ratios up to 10 5 , negligible hysteresis, and small subthreshold swing), excellent mechanical tensile properties (such as the only 12.4% and 6.4% degradations of the carrier mobility after 20% vertical and horizontal strain stretching), and optoelectronic synaptic plasticity (for the recognition of Morse codes) with ultra‐low power consumptions (15.38 aJ) at the operating voltage from −1 to 0.2 V. At the same time, the designed nonvolatile conductance of the stretchable SWCNT optoelectronic synapse thin film transistors (SSOSTFTs) stimulated by UV light and the bending angle are first used to simulate stretchable neuromorphic vision systems (including the functions of the crystalline lens and optic cone cells as bionic eyes) for detecting the atmospheric environment with a record accuracy of 95.1% as a bionic eye.

Topics & Concepts

Materials scienceNeuromorphic engineeringOptoelectronicsCarbon nanotubeTransistorNanotechnologyVoltageElectrical engineeringComputer scienceArtificial neural networkMachine learningEngineeringAdvanced Memory and Neural ComputingAdvanced Sensor and Energy Harvesting MaterialsNeuroscience and Neural Engineering
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