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Artificial Neurons on Flexible Substrates: A Fully Printed Approach for Neuromorphic Sensing

Printed electronic devices have demonstrated their applicability in complex electronic circuits. There is recent progress in the realization of neuromorphic computing systems (NCSs) to implement basic synaptic functions using solution-processed materials. However, a fully printed neuron is yet to be...

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Autores principales: Singaraju, Surya A., Weller, Dennis D., Gspann, Thurid S., Aghassi-Hagmann, Jasmin, Tahoori, Mehdi B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182789/
https://www.ncbi.nlm.nih.gov/pubmed/35684621
http://dx.doi.org/10.3390/s22114000
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author Singaraju, Surya A.
Weller, Dennis D.
Gspann, Thurid S.
Aghassi-Hagmann, Jasmin
Tahoori, Mehdi B.
author_facet Singaraju, Surya A.
Weller, Dennis D.
Gspann, Thurid S.
Aghassi-Hagmann, Jasmin
Tahoori, Mehdi B.
author_sort Singaraju, Surya A.
collection PubMed
description Printed electronic devices have demonstrated their applicability in complex electronic circuits. There is recent progress in the realization of neuromorphic computing systems (NCSs) to implement basic synaptic functions using solution-processed materials. However, a fully printed neuron is yet to be realised. We demonstrate a fully printed artificial neuromorphic circuit on flexible polyimide (PI) substrate. Characteristic features of individual components of the printed system were guided by the software training of the NCS. The printing process employs graphene ink for passive structures and In [Formula: see text] O [Formula: see text] as active material to print a two-input artificial neuron on PI. To ensure a small area footprint, the thickness of graphene film is tuned to target a resistance and to obtain conductors or resistors. The sheet resistance of the graphene film annealed at 300 °C can be adjusted between 200 [Formula: see text] and 500 k [Formula: see text] depending on the number of printed layers. The fully printed devices withstand a minimum of 2% tensile strain for at least 200 cycles of applied stress without any crack formation. The area usage of the printed two-input neuron is 16.25 mm [Formula: see text] , with a power consumption of 37.7 mW, a propagation delay of 1 s, and a voltage supply of 2 V, which renders the device a promising candidate for future applications in smart wearable sensors.
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spelling pubmed-91827892022-06-10 Artificial Neurons on Flexible Substrates: A Fully Printed Approach for Neuromorphic Sensing Singaraju, Surya A. Weller, Dennis D. Gspann, Thurid S. Aghassi-Hagmann, Jasmin Tahoori, Mehdi B. Sensors (Basel) Article Printed electronic devices have demonstrated their applicability in complex electronic circuits. There is recent progress in the realization of neuromorphic computing systems (NCSs) to implement basic synaptic functions using solution-processed materials. However, a fully printed neuron is yet to be realised. We demonstrate a fully printed artificial neuromorphic circuit on flexible polyimide (PI) substrate. Characteristic features of individual components of the printed system were guided by the software training of the NCS. The printing process employs graphene ink for passive structures and In [Formula: see text] O [Formula: see text] as active material to print a two-input artificial neuron on PI. To ensure a small area footprint, the thickness of graphene film is tuned to target a resistance and to obtain conductors or resistors. The sheet resistance of the graphene film annealed at 300 °C can be adjusted between 200 [Formula: see text] and 500 k [Formula: see text] depending on the number of printed layers. The fully printed devices withstand a minimum of 2% tensile strain for at least 200 cycles of applied stress without any crack formation. The area usage of the printed two-input neuron is 16.25 mm [Formula: see text] , with a power consumption of 37.7 mW, a propagation delay of 1 s, and a voltage supply of 2 V, which renders the device a promising candidate for future applications in smart wearable sensors. MDPI 2022-05-25 /pmc/articles/PMC9182789/ /pubmed/35684621 http://dx.doi.org/10.3390/s22114000 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Singaraju, Surya A.
Weller, Dennis D.
Gspann, Thurid S.
Aghassi-Hagmann, Jasmin
Tahoori, Mehdi B.
Artificial Neurons on Flexible Substrates: A Fully Printed Approach for Neuromorphic Sensing
title Artificial Neurons on Flexible Substrates: A Fully Printed Approach for Neuromorphic Sensing
title_full Artificial Neurons on Flexible Substrates: A Fully Printed Approach for Neuromorphic Sensing
title_fullStr Artificial Neurons on Flexible Substrates: A Fully Printed Approach for Neuromorphic Sensing
title_full_unstemmed Artificial Neurons on Flexible Substrates: A Fully Printed Approach for Neuromorphic Sensing
title_short Artificial Neurons on Flexible Substrates: A Fully Printed Approach for Neuromorphic Sensing
title_sort artificial neurons on flexible substrates: a fully printed approach for neuromorphic sensing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182789/
https://www.ncbi.nlm.nih.gov/pubmed/35684621
http://dx.doi.org/10.3390/s22114000
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