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

Singaraju, Surya A. 1; Weller, Dennis D. 1; Gspann, Thurid S. 1; Aghassi-Hagmann, Jasmin ORCID iD icon 1; Tahoori, Mehdi B. 2
1 Institut für Nanotechnologie (INT), Karlsruher Institut für Technologie (KIT)
2 Institut für Technische Informatik (ITEC), Karlsruher Institut für Technologie (KIT)


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 In2O3 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 Ω and 500 kΩ 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 mm2, 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.

Verlagsausgabe §
DOI: 10.5445/IR/1000148904
Veröffentlicht am 25.07.2022
DOI: 10.3390/s22114000
Zitationen: 2
Web of Science
Zitationen: 2
Zitationen: 2
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Nanotechnologie (INT)
Institut für Technische Informatik (ITEC)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 1424-8220
KITopen-ID: 1000148904
HGF-Programm 43.31.02 (POF IV, LK 01) Devices and Applications
Erschienen in Sensors
Verlag MDPI
Band 22
Heft 11
Seiten Art.-Nr. 4000
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Vorab online veröffentlicht am 25.05.2022
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