Memristive Behaviors Dominated by Reversible Nucleation Dynamics of Phase-Change Nanoclusters.

Journal: Small (Weinheim an der Bergstrasse, Germany)
Published Date:

Abstract

One of the important steps for realizing artificial intelligence is identifying elementary units that are beneficial for neural network construction. A type of memristive behavior in which phase-change nanoclusters nucleate adaptively in two adjacent dielectric layers with distinct distribution patterns is demonstrated. This memristive system responds in potentiation to increased stimulation strength and fire action potential after threshold stimulation. Reversible nucleation of phase-change nanoclusters is confirmed after both in situ and ex situ examinations using high-resolution transmission electron microscopy. The dynamics at the nanoscale level dominates the actions of the two dielectric layers. The oscillation response over a long period is due to the competition between crystalline and amorphous phases in the layer near the bottom electrode. Weight mutation, that is, action potential firing, is caused by the blockage of the filament in the layer near the top electrode. The memristive system is compact and able to execute complicated functions of a complete neuron and performs an important role in neuromorphic computing.

Authors

  • Qin Wan
    Ocular and Stem Cell Translational Research Section, National Eye Institute, NIH, Bethesda, Maryland, USA.
  • Fei Zeng
    Department of Gynecology, Third Xiangya Hospital, Central South University, Changsha 410013, China. 444838636@qq.com.
  • Yiming Sun
    Eye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Zhejiang Provincial Key Laboratory of Ophthalmology, Zhejiang Provincial Clinical Research Center for Eye Diseases, Zhejiang Provincial Engineering Institute on Eye Diseases, Hangzhou, Zhejiang, People's Republic of China.
  • Tongjin Chen
    Key Laboratory of Advanced Materials (MOE), School of Materials Science and Engineering, Tsinghua University, Beijing, 100084, P. R. China.
  • Junwei Yu
    Key Laboratory of Advanced Materials (MOE), School of Materials Science and Engineering, Tsinghua University, Beijing, 100084, P. R. China.
  • Huaqiang Wu
    Institue of Microelectronics, Tsinghua University, Beijing, 100084, China.
  • Zhen Zhao
  • Jiangli Cao
    School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100082, P. R. China.
  • Feng Pan
    Department of Radiation Oncology, China-Japan Union Hospital of Jilin University, Changchun, China.