无机材料学报 ›› 2023, Vol. 38 ›› Issue (4): 421-428.DOI: 10.15541/jim20220709

• 专栏:神经形态材料与器件(特邀编辑:万青) • 上一篇    下一篇

明胶/羧化壳聚糖栅控氧化物神经形态晶体管

陈鑫力(), 李岩, 王伟胜, 石智文, 竺立强()   

  1. 宁波大学 物理科学与技术学院, 宁波 315211
  • 收稿日期:2022-11-28 修回日期:2022-12-26 出版日期:2023-04-20 网络出版日期:2023-01-11
  • 通讯作者: 竺立强, 教授. E-mail: zhuliqiang@nbu.edu.cn
  • 作者简介:陈鑫力(1997-), 男, 硕士研究生. E-mail: 2111077006@nbu.edu.cn
  • 基金资助:
    国家自然科学基金(51972316);国家自然科学基金(U22A2075);宁波市重大科技攻关项目(2021Z116)

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: zhuliqiang@nbu.edu.cn
  • About author:CHEN Xinli (1997-), male, Master candidate. E-mail: 2111077006@nbu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(51972316);National Natural Science Foundation of China(U22A2075);Ningbo Key Technologies R&D Programme(2021Z116)

摘要:

模仿大脑感知信息处理方式对于仿生智能感知系统的设计具有重要意义, 而采用具有生物相容性和生物可降解特性的功能材料构建环境友好型神经形态器件是突触电子学研究的重要内容。本研究采用明胶/羧化壳聚糖(GEL/C-CS)复合电解质薄膜作为栅介质制作氧化物神经形态晶体管, 模仿了不同湿度下的突触响应行为, 包括兴奋性突触后电流和双脉冲易化。基于不同刺激数量下的突触塑性行为, 提出了一种触觉对物体识别程度的量化处理方式。进一步搭建人工神经网络, 实现了对MNIST手写数字的识别, 识别精度达90%以上。这种GEL/C-CS栅控神经形态器件对仿生智能感知和脑启发神经形态系统的设计具有一定的参考价值。

关键词: 氧化物神经形态晶体管, 明胶/羧化壳聚糖复合电解质, 触觉感知, 模式识别

Abstract:

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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