Physisorption-assistant optoelectronic synaptic transistors based on Ta2NiSe5/SnS2 heterojunction from ultraviolet to near-infrared

Neuromorphic computing vision is the most promising technological solution to overcome the arithmetic bottleneck in machine vision applications. All-in-one neuromorphic sensors have been attracting increased attention because they can integrate visual perception, processing, and memory functionalities into one single device. However, the limited responsivity and data retention time of all-in-one neuromorphic sensors usually hinder their potential in multispectral machine vision, especially in the near-infrared (NIR) band which contains critical information for pattern recognition. Here, we demonstrate physisorption-assistant optoelectronic synaptic transistors based on Ta<sub>2</sub>NiSe<sub>5</sub>/SnS<sub>2</sub> heterojunction, which present tunable synaptic functionality in broadband (375-1310 nm). We propose a strategy about the physisorption-assistant persistent photoconductivity (PAPPC) effect to effectively solve the problem in detecting and storing the NIR light information. Under this strategy, the responsivity and data retention time of our devices were significantly enhanced and prolonged in broadband from 375 to 1310 nm. Further, the devices realize multilevel non-volatile optoelectronic memory through the modulation of several optical and back-gate signals to simulate emotion-controlled learning and memory processes, optical writing-electric erasing, and associative learning. Moreover, we developed a simplified human visual system to simulate color-cognitive perception and memory functions. Our approach offers a route for creating advanced all-in-one neuromorphic sensors and developing neuromorphic computing vision.

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Publication Details

Journal
Light Science & Applications
Published
2025-03-17
DOI
https://doi.org/10.1038/s41377-025-01792-3
Citations
26
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
18.99
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article

Physisorption-assistant optoelectronic synaptic transistors based on Ta2NiSe5/SnS2 heterojunction from ultraviolet to near-infrared

Chao Lin, Mingxiu Liu, Dabing Li, Mario Lanza et al.
26 citations
Light Science & Applications
Advanced Memory and Neural Computing
18.99
article

Physisorption-assistant optoelectronic synaptic transistors based on Ta2NiSe5/SnS2 heterojunction from ultraviolet to near-infrared

Chao Lin, Mingxiu Liu, Dabing Li, Mario Lanza, Yaru Shi, Junru An, Shaojuan Li, Yahui Li, Yanze Feng, Zhilin Liu, Yuquan Zheng, Fan Tan, Chunlu Chang, Mengqi Che, Nan Zhang, Xingyu Zhao
article en
26 citations

Abstract

Neuromorphic computing vision is the most promising technological solution to overcome the arithmetic bottleneck in machine vision applications. All-in-one neuromorphic sensors have been attracting increased attention because they can integrate visual perception, processing, and memory functionalities into one single device. However, the limited responsivity and data retention time of all-in-one neuromorphic sensors usually hinder their potential in multispectral machine vision, especially in the near-infrared (NIR) band which contains critical information for pattern recognition. Here, we demonstrate physisorption-assistant optoelectronic synaptic transistors based on Ta<sub>2</sub>NiSe<sub>5</sub>/SnS<sub>2</sub> heterojunction, which present tunable synaptic functionality in broadband (375-1310 nm). We propose a strategy about the physisorption-assistant persistent photoconductivity (PAPPC) effect to effectively solve the problem in detecting and storing the NIR light information. Under this strategy, the responsivity and data retention time of our devices were significantly enhanced and prolonged in broadband from 375 to 1310 nm. Further, the devices realize multilevel non-volatile optoelectronic memory through the modulation of several optical and back-gate signals to simulate emotion-controlled learning and memory processes, optical writing-electric erasing, and associative learning. Moreover, we developed a simplified human visual system to simulate color-cognitive perception and memory functions. Our approach offers a route for creating advanced all-in-one neuromorphic sensors and developing neuromorphic computing vision.

Light Science & ApplicationsVol. 14(1)
Chinese Academy of Sciences (CN), Changchun Institute of Optics, Fine Mechanics and Physics (CN), University of Chinese Academy of Sciences (CN), King Abdullah University of Science and Technology (SA)
Quality Education
Openalex Percentile: Top 1%
Advanced Memory and Neural Computing
18.99
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