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

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

doi:10.1038/s41377-025-01792-3

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

Original Articles

- Physisorption-assistant optoelectronic synaptic transistors based on Ta₂NiSe₅/SnS₂ heterojunction from ultraviolet to near-infrared
- Physisorption-assistant optoelectronic synaptic transistors based on Ta₂NiSe₅/SnS₂ heterojunction from ultraviolet to near-infrared
- LSA 2025年14卷第5期页码：1278-1289
- Affiliations：
  
  1.State Key Laboratory of Luminescence Science and Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
  2.University of Chinese Academy of Sciences (UCAS), Beijing 100049, China
  3.State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
  4.Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, Changchun 130033, China
  5.Materials Science and Engineering Program, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia
- Author bio：
  
  Nan Zhang (zhangnan@ciomp.ac.cn)
  Shaojuan Li (lishaojuan@ciomp.ac.cn)
- Funds：
- DOI：10.1038/s41377-025-01792-3
  中图分类号：
- 收稿日期：2024-07-22，
  
  修回日期：2025-01-21，
  
  录用日期：2025-02-18，
  
  网络出版日期：2025-03-17，
  
  纸质出版日期：2025-05-31
- Accepted：
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Physisorption-assistant optoelectronic synaptic transistors based on Ta₂NiSe₅/SnS₂ heterojunction from ultraviolet to near-infrared[J]. LSA, 2025,14(5):1278-1289.

Tan, F. et al. Physisorption-assistant optoelectronic synaptic transistors based on Ta₂NiSe₅/SnS₂ heterojunction from ultraviolet to near-infrared. Light: Science & Applications, 14, 1278-1289 (2025).
Physisorption-assistant optoelectronic synaptic transistors based on Ta₂NiSe₅/SnS₂ heterojunction from ultraviolet to near-infrared[J]. LSA, 2025,14(5):1278-1289. DOI： 10.1038/s41377-025-01792-3.

Tan, F. et al. Physisorption-assistant optoelectronic synaptic transistors based on Ta₂NiSe₅/SnS₂ heterojunction from ultraviolet to near-infrared. Light: Science & Applications, 14, 1278-1289 (2025). DOI： 10.1038/s41377-025-01792-3.

摘要

Abstract

Neuromorphic computing vision is the most promising technological solution to overcome the arithmetic bottleneck in m

achine 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

NiSe

/SnS

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.

关键词

Keywords

references

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