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Tactile Neuromorphic System: Convergence of Triboelectric Polymer Sensor and Ferroelectric Polymer Synapse

Authors
Kim, H.[Kim, Hyeongjun]Oh, S.[Oh, Seyong]Choo, H.[Choo, Hyongsuk]Kang, D.-H.[Kang, Dong-Ho]Park, J.-H.[Park, Jin-Hong]
Issue Date
23-Aug-2023
Publisher
American Chemical Society
Keywords
artificial synapses; neuromorphic computing; P(VDF-TrFE); pattern recognition; PDMS; tactile neuromorphic system; triboelectric sensor
Citation
ACS Nano, v.17, no.17, pp.17332 - 17341
Indexed
SCIE
SCOPUS
Journal Title
ACS Nano
Volume
17
Number
17
Start Page
17332
End Page
17341
URI
https://scholarworks.bwise.kr/skku/handle/2021.sw.skku/108443
DOI
10.1021/acsnano.3c05337
ISSN
1936-0851
Abstract
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%. © 2023 American Chemical Society.
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