Ultralow‐Power Highly‐Selective Near‐Infrared (≈850 nm) Carbon Nanotube Flexible Optoelectronic Synaptic Transistors for Real‐Time Trajectory Tracking

Optoelectronic synaptic devices are promising candidate components for brain-like efficient neuromorphic computing systems. The development of highly-selective near-infrared (NIR) optoelectronic synaptic devices is important for realizing more efficient optical computing, night monitoring, and robot visual perception. In this work, ultralow-power (56 aJ per light pulse), NIR (≈850 nm) highly-selective optoelectronic synaptic transistor devices based on carbon nanotube thin film transistors are developed by modification of the organic photosensitive material in the device channels. The optoelectronic synaptic devices showed high sensitivity and selectivity to 850 nm pulse light. It is noted that optoelectronic response currents of the optoelectronic synaptic transistor devices after stimulation by a single 850 nm pulse light can be nearly six times higher than those stimulated by single pulse UV light, which is attributed that IHIC has a low bandgap, strong NIR absorption, and ideal energy band alignment with carbon nanotubes. Under pulsed light stimulation, a range of complex synaptic functions are exhibited, including excitatory postsynaptic currents, paired-pulse facilitation, and the transition from short-term plasticity to long-term plasticity, spike-timing-dependent plasticity, and image perception and memory functions. Significantly, the real-time trajectory tracking of the car by the drone under nighttime conditions is successfully simulated using the optoelectronic synaptic transistor array.

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Publication Details

Journal
Small
Published
2025-04-08
DOI
https://doi.org/10.1002/smll.202412324
Citations
7
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
5.11

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article

Ultralow‐Power Highly‐Selective Near‐Infrared (≈850 nm) Carbon Nanotube Flexible Optoelectronic Synaptic Transistors for Real‐Time Trajectory Tracking

Jiao Lei, Chenguang Qiu, Shuangshuang Shao, Qinjun Zhang et al.
7 citations
Small
Advanced Memory and Neural Computing
5.11
article

Ultralow‐Power Highly‐Selective Near‐Infrared (≈850 nm) Carbon Nanotube Flexible Optoelectronic Synaptic Transistors for Real‐Time Trajectory Tracking

Jiao Lei, Chenguang Qiu, Shuangshuang Shao, Qinjun Zhang, Meng Deng, Chengyong Xu, Jianwen Zhao, Kaixiang Kang, Nianzi Sui, Min Li
article en
7 citations

Abstract

Optoelectronic synaptic devices are promising candidate components for brain-like efficient neuromorphic computing systems. The development of highly-selective near-infrared (NIR) optoelectronic synaptic devices is important for realizing more efficient optical computing, night monitoring, and robot visual perception. In this work, ultralow-power (56 aJ per light pulse), NIR (≈850 nm) highly-selective optoelectronic synaptic transistor devices based on carbon nanotube thin film transistors are developed by modification of the organic photosensitive material in the device channels. The optoelectronic synaptic devices showed high sensitivity and selectivity to 850 nm pulse light. It is noted that optoelectronic response currents of the optoelectronic synaptic transistor devices after stimulation by a single 850 nm pulse light can be nearly six times higher than those stimulated by single pulse UV light, which is attributed that IHIC has a low bandgap, strong NIR absorption, and ideal energy band alignment with carbon nanotubes. Under pulsed light stimulation, a range of complex synaptic functions are exhibited, including excitatory postsynaptic currents, paired-pulse facilitation, and the transition from short-term plasticity to long-term plasticity, spike-timing-dependent plasticity, and image perception and memory functions. Significantly, the real-time trajectory tracking of the car by the drone under nighttime conditions is successfully simulated using the optoelectronic synaptic transistor array.

SmallVol. 21(22)
Jiangsu University (CN), University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Peking University (CN), Suzhou University of Science and Technology (CN), Suzhou Institute of Nano-tech and Nano-bionics (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, China Postdoctoral Science Foundation, Basic Research Program of Jiangsu Province, Suzhou Institute of Nanotechnology, Chinese Academy of Sciences, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 5%
Advanced Memory and Neural Computing
5.11
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