Artificial Synapses Based on Multiterminal Memtransistors for Neuromorphic Application. (22nd April 2019) - Wang, Lin; Liao, Wugang; Wong, Swee Liang; Yu, Zhi Gen; Li, Sifan; Lim, Yee‐Fun; Feng, Xuewei; Tan, Wee Chong; Huang, Xin; Chen, Li; Liu, Liang; Chen, Jingsheng; et al.
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‐MoS2 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 MoS2 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. Abstract : Multiterminal memtransistor‐based artificial synapses are realized using monolayer polycrystalline MoS2 grown by a scalable chemical vapor deposition process . The device shows a robust nonvolatile resistive switching behavior, which efficiently emulates the long‐term synaptic plasticity of biological synapses. Moreover, the memtransistor offers another degree‐of‐freedom to tune the synaptic plasticity by a third gate terminal, making it promising for enabling complex neuromorphic learning.