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Artificial olfactory memory system based on conductive metal-organic frameworks

Author

Listed:
  • Xiaomeng Yin

    (Chinese Academy of Sciences (CAS)
    University of Chinese Academy of Sciences)

  • Hao Zhang

    (Tianjin University of Technology)

  • Xuezhi Qiao

    (Chinese Academy of Sciences (CAS)
    University of Chinese Academy of Sciences)

  • Xinyuan Zhou

    (Tianjin University of Technology)

  • Zhenjie Xue

    (Tianjin University of Technology)

  • Xiangyu Chen

    (Chinese Academy of Sciences (CAS))

  • Haochen Ye

    (Chinese Academy of Sciences (CAS)
    University of Chinese Academy of Sciences)

  • Cancan Li

    (Chinese Academy of Sciences (CAS)
    University of Chinese Academy of Sciences)

  • Zhe Tang

    (Tianjin University of Technology)

  • Kailin Zhang

    (Tianjin University of Technology)

  • Tie Wang

    (Chinese Academy of Sciences (CAS)
    University of Chinese Academy of Sciences
    Tianjin University of Technology)

Abstract

The olfactory system can generate unique sensory memories of various odorous molecules, guiding emotional and cognitive decisions. However, most existing electronic noses remain constrained to momentary concentration, failing to trigger specific memories for different smells. Here, we report an artificial olfactory memory system utilizing conductive metal-organic frameworks (Ce-HHTP) that integrates sensing and memory and exhibits short- and long-term memory responses to alcohols and aldehydes. Experiments and theoretical calculations show that distinct memories are derived from the specific combinations of Ce-HHTP with O atoms in different guest. An unmanned aircraft equipped with this system realized the sensory memories in established areas. Moreover, the fusion of portable detection boxes and wearable flexible electrodes demonstrated the immense potential in off-site pollution monitoring and health management. This work represents an artificial olfactory memory system with two specific sensory memories under simultaneous conditions, laying the foundation for bionic design with qualities of human olfactory memory.

Suggested Citation

  • Xiaomeng Yin & Hao Zhang & Xuezhi Qiao & Xinyuan Zhou & Zhenjie Xue & Xiangyu Chen & Haochen Ye & Cancan Li & Zhe Tang & Kailin Zhang & Tie Wang, 2024. "Artificial olfactory memory system based on conductive metal-organic frameworks," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-52567-0
    DOI: 10.1038/s41467-024-52567-0
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