Journal of Inorganic Materials ›› 2023, Vol. 38 ›› Issue (4): 421-428.DOI: 10.15541/jim20220709

• Topical Section on Neuromorphic Materials and Devices (Contributing Editor: WAN Qing) • Previous Articles     Next Articles

Gelatin/Carboxylated Chitosan Gated Oxide Neuromorphic Transistor

CHEN Xinli(), LI Yan, WANG Weisheng, SHI Zhiwen, ZHU Liqiang()   

  1. School of Physical Science and Technology, Ningbo University, Ningbo 315211, China
  • Received:2022-11-28 Revised:2022-12-26 Published:2023-04-20 Online:2023-01-11
  • Contact: ZHU Liqiang, professor. E-mail:
  • About author:CHEN Xinli (1997-), male, Master candidate. E-mail:
  • Supported by:
    National Natural Science Foundation of China(51972316);National Natural Science Foundation of China(U22A2075);Ningbo Key Technologies R&D Programme(2021Z116)


Mimicking of brain perceptual processing mode is of great importance for the design of bionic intelligent perceptual system. On the meantime, adopting functional materials with biocompatibility and biodegradability to construct environment-friendly neuromorphic devices is also an important aspect for synaptic electronics. Here, gelatin/carboxylated chitosan (GEL/C-CS) composite electrolyte film was adopted as gate dielectrics in oxide neuromorphic transistors. Synaptic plasticities, including excitory post synaptic current and paired pulse facilitation, were mimicked on the oxide neuromorphic transistor under different humidities. A quantitative processing method for tactile recognition of objects was proposed based on the spike number dependent synaptic plasticity. An artificial neural network was built in further. Recognition accuracy of MNIST handwritten digits is above 90%. Data from above evaluation show that the proposed GEL/C-CS gated neuromorphic device has a promising application potential in the design of bionic intelligent perceptual systems and brain inspired neuromorphic systems.

Key words: oxide neuromorphic transistor, gelatin/carboxylated chitosan (GEL/C-CS) composite electrolyte, tactile perception, pattern recognition

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