4.7 Article

Artificial nociceptor based on TiO2 nanosheet memristor

Journal

SCIENCE CHINA-MATERIALS
Volume 64, Issue 7, Pages 1703-1712

Publisher

SCIENCE PRESS
DOI: 10.1007/s40843-020-1564-y

Keywords

nanosheets; nociceptor; memristors; artificial synapses; sensitization

Funding

  1. National Natural Science Foundation of China [61674050, 61874158]
  2. Project of Distinguished Youth of Hebei Province [A2018201231]
  3. Hundred Persons Plan of Hebei Province [E2018050004, E2018050003]
  4. Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province [SLRC2019018]
  5. Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences [XDB44000000-7]
  6. Outstanding Young Scientific Research and Innovation Team of Hebei University
  7. Highlevel Talent Research Startup Project of Hebei University [521000981426]
  8. Special Support Funds for National High Level Talents [041500120001, 521000981429]

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The study focused on a memristor with an Al/TiO2/Pt structure, showcasing its ability to simulate synaptic functions and verify pain behaviors of real nociceptors. This work highlights the potential application of TiO2-based devices in next-generation neuromorphological systems.
With the development of technology, the learning and memory functions of artificial memristor synapses are necessary for realizing artificial neural networks and neural neuromorphic computing. Owing to their high scalability performance, nanosheet materials have been widely employed in cellular-level learning, but the behaviors of nociceptor based on nanosheet materials have rarely been studied. Here, we present a memristor with an Al/TiO2/Pt structure. After electroforming, the memristor device showed a gradual conductance regulation and could simulate synaptic functions such as the potentiation and depression of synaptic weights. We also designed a new scheme that verifies the pain sensitization, desensitization, allodynia, and hyperalgesia behaviors of real nociceptors in the fabricated memristor. Memristors with these behaviors can significantly improve the quality of intelligent electronic devices. Data fitting showed that the high resistance and low resistance states were consistent with the hopping conduction mechanism. This work promises the application of TiO2-based devices in next-generation neuromorphological systems.

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