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Memory-electroluminescence for multiple action-potentials combination in bio-inspired afferent nerves

Author

Listed:
  • Kun Wang

    (Fuzhou University)

  • Yitao Liao

    (Fuzhou University)

  • Wenhao Li

    (Fuzhou University)

  • Junlong Li

    (Fuzhou University)

  • Hao Su

    (Fuzhou University)

  • Rong Chen

    (Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China)

  • Jae Hyeon Park

    (Hanyang University)

  • Yongai Zhang

    (Fuzhou University
    Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China)

  • Xiongtu Zhou

    (Fuzhou University
    Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China)

  • Chaoxing Wu

    (Fuzhou University
    Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China)

  • Zhiqiang Liu

    (Chinese Academy of Sciences)

  • Tailiang Guo

    (Fuzhou University
    Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China)

  • Tae Whan Kim

    (Hanyang University)

Abstract

The development of optoelectronics mimicking the functions of the biological nervous system is important to artificial intelligence. This work demonstrates an optoelectronic, artificial, afferent-nerve strategy based on memory-electroluminescence spikes, which can realize multiple action-potentials combination through a single optical channel. The memory-electroluminescence spikes have diverse morphologies due to their history-dependent characteristics and can be used to encode distributed sensor signals. As the key to successful functioning of the optoelectronic, artificial afferent nerve, a driving mode for light-emitting diodes, namely, the non-carrier injection mode, is proposed, allowing it to drive nanoscale light-emitting diodes to generate a memory-electroluminescence spikes that has multiple sub-peaks. Moreover, multiplexing of the spikes can be obtained by using optical signals with different wavelengths, allowing for a large signal bandwidth, and the multiple action-potentials transmission process in afferent nerves can be demonstrated. Finally, sensor-position recognition with the bio-inspired afferent nerve is developed and shown to have a high recognition accuracy of 98.88%. This work demonstrates a strategy for mimicking biological afferent nerves and offers insights into the construction of artificial perception systems.

Suggested Citation

  • Kun Wang & Yitao Liao & Wenhao Li & Junlong Li & Hao Su & Rong Chen & Jae Hyeon Park & Yongai Zhang & Xiongtu Zhou & Chaoxing Wu & Zhiqiang Liu & Tailiang Guo & Tae Whan Kim, 2024. "Memory-electroluminescence for multiple action-potentials combination in bio-inspired afferent nerves," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47641-6
    DOI: 10.1038/s41467-024-47641-6
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