Artificial Axon with Dendritic-like Plasticity by Biomimetic Interface Engineering of Anisotropic Two-Dimensional Tellurium.

Journal: Nano letters
Published Date:

Abstract

Spiking neural network (SNN) hardware relies on implicit assumptions that prioritize dendritic/synaptic learning above axon/synaptic concerns, compromising performances in signal capacity, accuracy, and compactness of SNN systems. Herein, we develop an artificial axon by utilizing the heterogeneity and interface state tunability in anisotropic two-dimensional (2D) tellurium (Te). By operating a multiterminal axon under the bioelectricity level, the device achieved neuron-like heterogeneous axon dynamics expansion (∼258%). An excellent dendritic-like tunability (∼197%) exhibits gain on the axons. The synergistic axon-dendrite optimization device exhibits 5-bit programmable conductance, signal filtering, and input enhancing. The accuracy of recognizing data sets based on the SNN algorithm demonstrates efficient optimization (5.2% higher accuracy) of networks by the device features, especially in the case of performing image preprocessing. This artificial neuron solution with anisotropic 2D materials utilizing biomimetic interface engineering provides a universal strategy for compact, high-precision parallel architecture of SNN hardware.

Authors

  • Jiwei Chen
    School of Microelectronics, South China University of Technology, Guangzhou 511442, China.
  • Changjian Zhou
    Department of Data and Computing, Northeast Agricultural University, Harbin 150030, P. R. China.
  • Yingjie Luo
    College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, PR China.
  • Wenbo Li
    Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Xianhu Hydrogen Valley, Foshan 528200, China.
  • Xiankai Lin
    Songshan Lake Materials Laboratory, Songshan Lake Mat Lab, Dongguan 523808, China.
  • Chunlei Zhang
    Center for Robust Speech Systems (CRSS), The University of Texas at Dallas, 800 West Campbell Road, Richardson, Texas 75080, USA.
  • Siyu Liao
    School of Integrated Circuit, Sun Yat-Sen university, Shenzhen 518107, China.
  • Ruolan Wen
    School of Microelectronics, South China University of Technology, Guangzhou 511442, China.
  • Guitian Qiu
    Songshan Lake Materials Laboratory, Songshan Lake Mat Lab, Dongguan 523808, China.
  • Qian Zhang
    The Neonatal Intensive Care Unit, Peking Union Medical College Hospital, Peking, China.
  • Jianxian Yi
    Songshan Lake Materials Laboratory, Songshan Lake Mat Lab, Dongguan 523808, China.
  • Wenhan Lei
    Songshan Lake Materials Laboratory, Songshan Lake Mat Lab, Dongguan 523808, China.
  • Lin Wang
    Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China.
  • Syed Rizwan
    Physics Characterization & Simulations Lab (PCSL), Department of Physics and Astronomy, School of Natural Sciences, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
  • Pei Lin
    Key Laboratory of Materials Physics, Ministry of Education, School of Physics, Zhengzhou University, Zhengzhou 450001, China.
  • Qijie Liang
    Songshan Lake Materials Laboratory, Songshan Lake Mat Lab, Dongguan 523808, China.