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首页> 外文期刊>Advanced Functional Materials >Bio-Inspired Photoelectric Artificial Synapse based on Two- Dimensional Ti_3C_2T_x MXenes Floating Gate
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Bio-Inspired Photoelectric Artificial Synapse based on Two- Dimensional Ti_3C_2T_x MXenes Floating Gate

机译：生物启发的光电人工突触基于二维TI_3C_2T_X mxenes浮栅

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摘要

The highly parallel artificial neural systems based on transistor-like devices have recently attracted widespread attention due to their high-efficiency computing potential and the ability to mimic biological neurobehavior. For the past decades, plenty of breakthroughs related to synaptic transistors have been investigated and reported. In this work, a kind of photoelectronic transistor that successfully mimics the behaviors of biological synapses has been proposed and systematically analyzed. For the individual device, MXenes and the self-assembled titanium dioxide on the nanosheet surface serve as floating gate and tunneling layers, respectively. As the unit electronics of the neural network, the typical synaptic behaviors and the reliable memory stability of the synaptic transistors have been demonstrated through the voltage test. Furthermore, for the first time, the UV-responsive synaptic properties of the MXenes floating gated transistor and its applications, including conditional reflex and supervised learning, have been measured and realized. These photoelectric synapse characteristics illustrate the great potential of the device in bio-imitation vision applications. Finally, through the simulation based on an artificial neural network algorithm, the device successfully realizes the recognition application of handwritten digital images. Thus, this article provides a highly feasible solution for applying artificial synaptic devices to hardware neuromorphic networks.
机译：基于晶体管状器件的高度平行的人工神经系统，最近由于其高效计算潜力和模拟生物神经震颤的能力而引起了广泛的关注。在过去的几十年中，研究并报道了与突触晶体管相关的大量突破。在这项工作中，已经提出了一种成功模仿生物突触的行为的一种光电晶体管已经提出和系统地分析。对于各个装置，纳米片表面上的各个装置和自组装二氧化钛分别用作浮栅和隧道层。作为神经网络的单位电子器件，通过电压测试证明了典型的突触行为和突触晶体管的可靠记忆稳定性。此外，首次进行了浮动门控晶体管及其应用，包括条件反射和监督学习的MXENES的UV响应突触特性及其应用。这些光电突触特性说明了生物模仿视觉应用中器件的巨大潜力。最后，通过基于人工神经网络算法的仿真，设备成功地实现了手写数字图像的识别应用。因此，本文提供了一种高度可行的解决方案，用于将人工突触装置应用于硬件神经形态网络。

著录项

  • 来源
    《Advanced Functional Materials》 |2021年第45期|2106000.1-2106000.11|共11页
  • 作者

    Zhao Tianshi; Zhao Chun; Xu Wangying; Liu Yina; Gao Hao; Mitrovic Ivona Z.; Lim Eng Gee; Yang Li; Zhao Ce Zhou;

  • 作者单位

    Xian Jiaotong Liverpool Univ Sch Adv Technol Suzhou 215123 Peoples R China|Univ Liverpool Dept Elect Engn & Elect Liverpool L69 3GJ Merseyside England;

    Xian Jiaotong Liverpool Univ Sch Adv Technol Suzhou 215123 Peoples R China;

    Shenzhen Univ Coll Mat Sci & Engn Shenzhen 518060 Peoples R China;

    Xian Jiaotong Liverpool Univ Dept Math Sci Suzhou 215123 Peoples R China;

    Eindhoven Univ Technol Dept Elect Engn Eindhoven Netherlands;

    Univ Liverpool Dept Elect Engn & Elect Liverpool L69 3GJ Merseyside England;

    Xian Jiaotong Liverpool Univ Sch Adv Technol Suzhou 215123 Peoples R China;

    Xian Jiaotong Liverpool Univ Dept Chem Suzhou 215123 Peoples R China;

    Xian Jiaotong Liverpool Univ Sch Adv Technol Suzhou 215123 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    image recognition; MXenes; neuromorphic computing; photoelectric plasticity; synaptic transistors;

    机译：图像识别;mxenes;神经形态计算;光电塑性;突触晶体管;

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