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One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications
One-dimensional (1D) devices are becoming the most desirable format for wearable electronic technology because they can be easily woven into electronic (e-) textile(s) with versatile functional units while maintaining their inherent features under mechanical stress. In this study, we designed 1D fib...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662591/ https://www.ncbi.nlm.nih.gov/pubmed/32937532 http://dx.doi.org/10.1126/sciadv.aba1178 |
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author | Ham, Seonggil Kang, Minji Jang, Seonghoon Jang, Jingon Choi, Sanghyeon Kim, Tae-Wook Wang, Gunuk |
author_facet | Ham, Seonggil Kang, Minji Jang, Seonghoon Jang, Jingon Choi, Sanghyeon Kim, Tae-Wook Wang, Gunuk |
author_sort | Ham, Seonggil |
collection | PubMed |
description | One-dimensional (1D) devices are becoming the most desirable format for wearable electronic technology because they can be easily woven into electronic (e-) textile(s) with versatile functional units while maintaining their inherent features under mechanical stress. In this study, we designed 1D fiber-shaped multi-synapses comprising ferroelectric organic transistors fabricated on a 100-μm Ag wire and used them as multisynaptic channels in an e-textile neural network for wearable neuromorphic applications. The device mimics diverse synaptic functions with excellent reliability even under 6000 repeated input stimuli and mechanical bending stress. Various NOR-type textile arrays are formed simply by cross-pointing 1D synapses with Ag wires, where each output from individual synapse can be integrated and propagated without undesired leakage. Notably, the 1D multi-synapses achieved up to ~90 and ~70% recognition accuracy for MNIST and electrocardiogram patterns, respectively, even in a single-layer neural network, and almost maintained regardless of the bending conditions. |
format | Online Article Text |
id | pubmed-10662591 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-106625912020-07-10 One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications Ham, Seonggil Kang, Minji Jang, Seonghoon Jang, Jingon Choi, Sanghyeon Kim, Tae-Wook Wang, Gunuk Sci Adv Research Articles One-dimensional (1D) devices are becoming the most desirable format for wearable electronic technology because they can be easily woven into electronic (e-) textile(s) with versatile functional units while maintaining their inherent features under mechanical stress. In this study, we designed 1D fiber-shaped multi-synapses comprising ferroelectric organic transistors fabricated on a 100-μm Ag wire and used them as multisynaptic channels in an e-textile neural network for wearable neuromorphic applications. The device mimics diverse synaptic functions with excellent reliability even under 6000 repeated input stimuli and mechanical bending stress. Various NOR-type textile arrays are formed simply by cross-pointing 1D synapses with Ag wires, where each output from individual synapse can be integrated and propagated without undesired leakage. Notably, the 1D multi-synapses achieved up to ~90 and ~70% recognition accuracy for MNIST and electrocardiogram patterns, respectively, even in a single-layer neural network, and almost maintained regardless of the bending conditions. American Association for the Advancement of Science 2020-07-10 /pmc/articles/PMC10662591/ /pubmed/32937532 http://dx.doi.org/10.1126/sciadv.aba1178 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Ham, Seonggil Kang, Minji Jang, Seonghoon Jang, Jingon Choi, Sanghyeon Kim, Tae-Wook Wang, Gunuk One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications |
title | One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications |
title_full | One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications |
title_fullStr | One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications |
title_full_unstemmed | One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications |
title_short | One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications |
title_sort | one-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662591/ https://www.ncbi.nlm.nih.gov/pubmed/32937532 http://dx.doi.org/10.1126/sciadv.aba1178 |
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