Litcius/Paper detail

Ultralow-Power Synaptic Transistor Based on Wafer-Scale MoS<sub>2</sub> Thin Film for Neuromorphic Application

Chen Wang, Hao Liu, Lin Chen, Hao Zhu, Ji Li, Qingqing Sun, David Wei Zhang

2021IEEE Electron Device Letters17 citationsDOI

Abstract

In the next-generation computing framework, synaptic devices modulated using analogue weight storage are expected with capability of performing neuromorphic computing tasks. Recently, 2D transition metal dichalcogenides (TMDCs) based solid-state devices have demonstrated excellent electrical performance showing great potential in nanoscale synaptic electronics. In this letter, artificial synaptic transistors are proposed and fabricated on the atomic layer deposited 2D MoS <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> thin film with an integrated high-k dielectric gate stack. The synapse cells can simulate fundamental synaptic functions similar to those of biological synapses, such as long-term potentiation and depression. Moreover, the ultralow power consumption shows that the proposed synapse is more efficient than most three-terminal synaptic transistors. We also emulate a multi-synapse network to demonstrate intrinsic heterogeneity in biological brain. The experimental results have validated the feasibility of synaptic devices based on 2D TMDCs and have contributed a promising approach to the development of the next-generation brain-like neuromorphic systems.

Topics & Concepts

Neuromorphic engineeringMaterials scienceSynapseTransistorSynaptic weightOptoelectronicsWaferComputer scienceNanotechnologyElectrical engineeringNeuroscienceArtificial neural networkVoltageEngineeringArtificial intelligenceBiologyAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesTransition Metal Oxide Nanomaterials