4.8 Article

Near-Infrared Artificial Synapses for Artificial Sensory Neuron System

Journal

SMALL
Volume 17, Issue 38, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/smll.202103837

Keywords

artificial sensory neuron; artificial synapses; flash memory; near-infrared; transistors

Funding

  1. NSFC Program [61805160, 62074104, 61974093]
  2. Guangdong Province Special Support Plan for High-Level Talents [2017TQ04X082]
  3. Guangdong Provincial Department of Science and Technology [2018B030306028, 2019A1515110702, 2020A1515011425]
  4. Science and Technology Innovation Commission of Shenzhen [JCYJ20180507182042530, JCYJ20180507182000722, JCYJ20180305124214580, 20200804172625001]
  5. Natural Science Foundation of Shenzhen University [860/000002110638]

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Computing based on artificial neuron networks is expected to enhance computing efficiency and has broad prospects in artificial visual systems. By inserting organic small molecule IR-780 iodide into memory devices, artificial synaptic functions can be regulated effectively.
The computing based on artificial neuron network is expected to break through the von Neumann bottleneck of traditional computer, and to greatly improve the computing efficiency, displaying a broad prospect in the application of artificial visual system. In the specific structural layout, it is a common method to connect the discrete photodetector with the artificial neuron in series, which enhances the complexity of signal recognition, conversion and storage. In this work, organic small molecule IR-780 iodide is inserted into the memory device as both the charge trapping layer and near-infrared (NIR) photoresponsive film. Through electrical and optical regulation, artificial synaptic functions including short-term plasticity, long-term plasticity, and spike rate dependence are realized. In the established artificial sensory neuron system, NIR optical pulses can significantly improve the spiking rate. Moreover, the spiking neural networks are further constructed by simulation for handwritten digit classification. This research may contribute to the development of light driven neural robots, optical signal encryption, and neural computing.

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