Artificial Synapses Based on Multiterminal Memtransistors for Neuromorphic Application

Abstract Neuromorphic computing, which emulates the biological neural systems could overcome the high‐power consumption issue of conventional von‐Neumann computing. State‐of‐the‐art artificial synapses made of two‐terminal memristors, however, show variability in filament formation and limited capacity due to their inherent single presynaptic input design. Here, a memtransistor‐based artificial synapse is realized by integrating a memristor and selector transistor into a multiterminal device using monolayer polycrys‐talline‐MoS 2 grown by a scalable chemical vapor deposition (CVD) process. Notably, the memtransistor offers both drain‐ and gate‐tunable nonvolatile memory functions, which efficiently emulates the long‐term potentiation/depression, spike‐amplitude, and spike‐timing‐dependent plasticity of biological synapses. Moreover, the gate tunability function that is not achievable in two‐terminal memristors, enables significant bipolar resistive states switching up to four orders‐of‐magnitude and high cycling endurance. First‐principles calculations reveal a new resistive switching mechanism driven by the diffusion of double sulfur vacancy perpendicular to the MoS 2 grain boundary, leading to a conducting switching path without the need for a filament forming process. The seamless integration of multiterminal memtransistors may offer another degree‐of‐freedom to tune the synaptic plasticity by a third gate terminal for enabling complex neuromorphic learning.

Authors

Lin Wang; Wugang Liao; Swee Liang Wong; Zhi Gen Yu; Sifan Li; Yee‐Fun Lim; Xuewei Feng; Wee Chong Tan; Xin Huang; Li Chen; Liang Liu; Jingsheng Chen; Xiao Gong; Chunxiang Zhu; Xinke Liu; Yong‐Wei Zhang; Dongzhi Chi; Kah‐Wee Ang

Published

Apr 22, 2019

Journal or venue

Advanced Functional Materials

DOI

10.1002/adfm.201901106

Paper type

journal article

Source

Openalex