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A Neuromorphic Device Implemented on a Salmon‐DNA Electrolyte and its Application to Artificial Neural Networks

A bioinspired neuromorphic device operating as synapse and neuron simultaneously, which is fabricated on an electrolyte based on Cu(2+)‐doped salmon deoxyribonucleic acid (S‐DNA) is reported. Owing to the slow Cu(2+) diffusion through the base pairing sites in the S‐DNA electrolyte, the synaptic ope...

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Autores principales: Kang, Dong‐Ho, Kim, Jeong‐Hoon, Oh, Seyong, Park, Hyung‐Youl, Dugasani, Sreekantha Reddy, Kang, Beom‐Seok, Choi, Changhwan, Choi, Rino, Lee, Sungjoo, Park, Sung Ha, Heo, Keun, Park, Jin‐Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724472/
https://www.ncbi.nlm.nih.gov/pubmed/31508292
http://dx.doi.org/10.1002/advs.201901265
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author Kang, Dong‐Ho
Kim, Jeong‐Hoon
Oh, Seyong
Park, Hyung‐Youl
Dugasani, Sreekantha Reddy
Kang, Beom‐Seok
Choi, Changhwan
Choi, Rino
Lee, Sungjoo
Park, Sung Ha
Heo, Keun
Park, Jin‐Hong
author_facet Kang, Dong‐Ho
Kim, Jeong‐Hoon
Oh, Seyong
Park, Hyung‐Youl
Dugasani, Sreekantha Reddy
Kang, Beom‐Seok
Choi, Changhwan
Choi, Rino
Lee, Sungjoo
Park, Sung Ha
Heo, Keun
Park, Jin‐Hong
author_sort Kang, Dong‐Ho
collection PubMed
description A bioinspired neuromorphic device operating as synapse and neuron simultaneously, which is fabricated on an electrolyte based on Cu(2+)‐doped salmon deoxyribonucleic acid (S‐DNA) is reported. Owing to the slow Cu(2+) diffusion through the base pairing sites in the S‐DNA electrolyte, the synaptic operation of the S‐DNA device features special long‐term plasticity with negative and positive nonlinearity values for potentiation and depression (α(p) and α(d)), respectively, which consequently improves the learning/recognition efficiency of S‐DNA‐based neural networks. Furthermore, the representative neuronal operation, “integrate‐and‐fire,” is successfully emulated in this device by adjusting the duration time of the input voltage stimulus. In particular, by applying a Cu(2+) doping technique to the S‐DNA neuromorphic device, the characteristics for synaptic weight updating are enhanced (|α(p)|: 31→20, |α(d)|: 11→18, weight update margin: 33→287 nS) and also the threshold conditions for neuronal firing (amplitude and number of stimulus pulses) are modulated. The improved synaptic characteristics consequently increase the Modified National Institute of Standards and Technology (MNIST) pattern recognition rate from 38% to 44% (single‐layer perceptron model) and from 89.42% to 91.61% (multilayer perceptron model). This neuromorphic device technology based on S‐DNA is expected to contribute to the successful implementation of a future neuromorphic system that simultaneously satisfies high integration density and remarkable recognition accuracy.
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spelling pubmed-67244722019-09-10 A Neuromorphic Device Implemented on a Salmon‐DNA Electrolyte and its Application to Artificial Neural Networks Kang, Dong‐Ho Kim, Jeong‐Hoon Oh, Seyong Park, Hyung‐Youl Dugasani, Sreekantha Reddy Kang, Beom‐Seok Choi, Changhwan Choi, Rino Lee, Sungjoo Park, Sung Ha Heo, Keun Park, Jin‐Hong Adv Sci (Weinh) Communications A bioinspired neuromorphic device operating as synapse and neuron simultaneously, which is fabricated on an electrolyte based on Cu(2+)‐doped salmon deoxyribonucleic acid (S‐DNA) is reported. Owing to the slow Cu(2+) diffusion through the base pairing sites in the S‐DNA electrolyte, the synaptic operation of the S‐DNA device features special long‐term plasticity with negative and positive nonlinearity values for potentiation and depression (α(p) and α(d)), respectively, which consequently improves the learning/recognition efficiency of S‐DNA‐based neural networks. Furthermore, the representative neuronal operation, “integrate‐and‐fire,” is successfully emulated in this device by adjusting the duration time of the input voltage stimulus. In particular, by applying a Cu(2+) doping technique to the S‐DNA neuromorphic device, the characteristics for synaptic weight updating are enhanced (|α(p)|: 31→20, |α(d)|: 11→18, weight update margin: 33→287 nS) and also the threshold conditions for neuronal firing (amplitude and number of stimulus pulses) are modulated. The improved synaptic characteristics consequently increase the Modified National Institute of Standards and Technology (MNIST) pattern recognition rate from 38% to 44% (single‐layer perceptron model) and from 89.42% to 91.61% (multilayer perceptron model). This neuromorphic device technology based on S‐DNA is expected to contribute to the successful implementation of a future neuromorphic system that simultaneously satisfies high integration density and remarkable recognition accuracy. John Wiley and Sons Inc. 2019-07-15 /pmc/articles/PMC6724472/ /pubmed/31508292 http://dx.doi.org/10.1002/advs.201901265 Text en © 2019 The Authors. Published by WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Communications
Kang, Dong‐Ho
Kim, Jeong‐Hoon
Oh, Seyong
Park, Hyung‐Youl
Dugasani, Sreekantha Reddy
Kang, Beom‐Seok
Choi, Changhwan
Choi, Rino
Lee, Sungjoo
Park, Sung Ha
Heo, Keun
Park, Jin‐Hong
A Neuromorphic Device Implemented on a Salmon‐DNA Electrolyte and its Application to Artificial Neural Networks
title A Neuromorphic Device Implemented on a Salmon‐DNA Electrolyte and its Application to Artificial Neural Networks
title_full A Neuromorphic Device Implemented on a Salmon‐DNA Electrolyte and its Application to Artificial Neural Networks
title_fullStr A Neuromorphic Device Implemented on a Salmon‐DNA Electrolyte and its Application to Artificial Neural Networks
title_full_unstemmed A Neuromorphic Device Implemented on a Salmon‐DNA Electrolyte and its Application to Artificial Neural Networks
title_short A Neuromorphic Device Implemented on a Salmon‐DNA Electrolyte and its Application to Artificial Neural Networks
title_sort neuromorphic device implemented on a salmon‐dna electrolyte and its application to artificial neural networks
topic Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724472/
https://www.ncbi.nlm.nih.gov/pubmed/31508292
http://dx.doi.org/10.1002/advs.201901265
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