神经形态工程学
突触重量
材料科学
铁电性
光电子学
肖特基势垒
晶体管
计算机科学
人工神经网络
电气工程
电子工程
工程类
人工智能
电压
电介质
二极管
作者
Fengben Xi,Yi Han,Andreas Grenmyr,Detlev Grützmacher,Qing‐Tai Zhao
标识
DOI:10.1109/jeds.2022.3166449
摘要
In this paper, artificial synapses based on four terminal ferroelectric Schottky barrier field effect transistors (FE-SBFETs) are experimentally demonstrated. The ferroelectric polarization switching dynamics gradually modulate the Schottky barriers, thus programming the device conductance by applying negative or postive pulses to imitate the excitation and inhibition behaviors of the biological synapse. The excitatory post-synaptic current can be modulated by the back-gate bias, enabling the reconfiguration of the weight profile with high speed of 20 ns and low energy (< 1 fJ/spike) consumption. Besides, the tunable long term potentiation and depression show high endurance and very small cycle-to-cycle variations. Based on the good linearity, high symmetricity and large dynamic range of the synaptic weight updates, a high recognition accuracy (92.6%) is achieved for handwritten digits by multilayer perceptron artificial neural networks. These findings demonstrate FE-SBFET has high potential as an ideal synaptic component for the future intelligent neuromorphic network.
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