神经形态工程学
摩擦电效应
材料科学
突触
铁电性
计算机科学
MNIST数据库
纳米技术
人工神经网络
神经科学
电子工程
光电子学
人工智能
工程类
电介质
复合材料
生物
作者
Hyeongjun Kim,Seyong Oh,Hyongsuk Choo,Do Hyung Kang,Jin‐Hong Park
出处
期刊:ACS Nano
[American Chemical Society]
日期:2023-08-23
标识
DOI:10.1021/acsnano.3c05337
摘要
Sensory neuromorphic systems are a promising technology, because they can replicate the way the human peripheral nervous system processes signals from the five sensory organs. Despite this potential, there are limited studies on how to implement these systems on a hardware neural network platform. In our research, we propose a tactile neuromorphic system that uses a poly(dimethylsiloxane) (PDMS)-based triboelectric sensor and a molybdenum disulfide (MoS2)/poly(vinylidene fluoride-trifluoro ethylene) (P(VDF-TrFE)) heterostructure-based ferroelectric synapse. The triboelectric sensor mimics a human tactile organ by converting tactile stimuli into electrical signals in real time. The ferroelectric synapse we developed demonstrates exceptional long-term potentiation/depression characteristics with a maximum dynamic range of 78 and a symmetrical value of 4.7. To assess the practicality of our proposed system, we conducted training and recognition simulations using Morse code alphabets and MNIST handwritten digits. The maximum recognition rate that we achieved was 96.17%.
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