Cargando…
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...
Autores principales: | , , , , |
---|---|
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 |
_version_ | 1784724122241073152 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9182789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT singarajusuryaa artificialneuronsonflexiblesubstratesafullyprintedapproachforneuromorphicsensing AT wellerdennisd artificialneuronsonflexiblesubstratesafullyprintedapproachforneuromorphicsensing AT gspannthurids artificialneuronsonflexiblesubstratesafullyprintedapproachforneuromorphicsensing AT aghassihagmannjasmin artificialneuronsonflexiblesubstratesafullyprintedapproachforneuromorphicsensing AT tahoorimehdib artificialneuronsonflexiblesubstratesafullyprintedapproachforneuromorphicsensing |