Near-infrared organic photoelectrochemical synaptic transistors by wafer-scale photolithography for neuromorphic visual system

Optoelectronic synapses can be crucial for advancing artificial intelligence and visual systems. Optoelectronic synapses based on organic field-effect transistors have been widely studied but still face significant challenges including obvious programming nonlinearity, restricted response wavelength, high operation voltage, and limited storage memory. Organic electrochemical transistors can be another candidate but lack intensive studies. Additionally, wafer-scale photolithographic fabrication on optoelectronic synapses responding to near-infrared (NIR) light is highly desirable but rarely reported. Here, we propose the NIR organic photoelectrochemical transistor (OPECT) array capable of low voltage multi-level memories fabricated by photolithography. Based on NIR photo-induced electrochemical doping mechanism, the OPECTs enable linear weight programming with ultra-low nonlinearity (-0.015) over a wide range (47.3). We further demonstrate OPECTs arrays for image sensing, memorization, and visualization. Eventually, a convolutional computing system is constructed, executing accurate recognition of noisy handwritten digits. This work offers a promising insight into neuromorphic sensory computing applications.

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Publication Details

Journal
Nature Communications
Published
2025-12-08
DOI
https://doi.org/10.1038/s41467-025-66891-6
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46

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Near-infrared organic photoelectrochemical synaptic transistors by wafer-scale photolithography for neuromorphic visual system

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Near-infrared organic photoelectrochemical synaptic transistors by wafer-scale photolithography for neuromorphic visual system

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article en
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Abstract

Optoelectronic synapses can be crucial for advancing artificial intelligence and visual systems. Optoelectronic synapses based on organic field-effect transistors have been widely studied but still face significant challenges including obvious programming nonlinearity, restricted response wavelength, high operation voltage, and limited storage memory. Organic electrochemical transistors can be another candidate but lack intensive studies. Additionally, wafer-scale photolithographic fabrication on optoelectronic synapses responding to near-infrared (NIR) light is highly desirable but rarely reported. Here, we propose the NIR organic photoelectrochemical transistor (OPECT) array capable of low voltage multi-level memories fabricated by photolithography. Based on NIR photo-induced electrochemical doping mechanism, the OPECTs enable linear weight programming with ultra-low nonlinearity (-0.015) over a wide range (47.3). We further demonstrate OPECTs arrays for image sensing, memorization, and visualization. Eventually, a convolutional computing system is constructed, executing accurate recognition of noisy handwritten digits. This work offers a promising insight into neuromorphic sensory computing applications.

Nature CommunicationsVol. 17(1)
Tongji University (CN), Nantong University (CN), Intelligent Systems Research (United States) (US)
National Natural Science Foundation of China, Tongji University, National Key Research and Development Program of China
Openalex Percentile: Top 14%
Advanced Memory and Neural Computing
1.46
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