Nanowire FET based neural element for robotic tactile sensing skin

William Taube Navaraj, Carlos García Núñez, Dhayalan Shakthivel, Vincenzo Vinciguerra, Fabrice Labeau, Duncan H. Gregory, Ravinder Dahiya

Research output: Contribution to journalArticle

30 Citations (Scopus)

Abstract

This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs) based hardware-implementable neural network (HNN) approach for tactile data processing in electronic skin (e-skin). The viability of Si nanowires (NWs) as the active material for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin) in the backplane. The modeling and simulation of υ-NWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υ-NWFETs as the building block for HNN. The simulation has been further extended to υ-NWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO based capacitive tactile sensors array) integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υ-NWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET devices confirm the dependence of turn-off voltages on the (synaptic) weight of each gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals.
Original languageEnglish
Article number501
Number of pages20
JournalFrontiers in Neuroscience
Volume11
DOIs
Publication statusPublished - 20 Sep 2017
Externally publishedYes

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Nanowires
Touch
Robotics
Skin
Equipment and Supplies
Weights and Measures
Computer Communication Networks
Gestures
Printing
Automatic Data Processing
Information Systems
Hand
Metals

Keywords

  • silicon nanowire
  • tactile skin
  • sparse coding
  • Nanowire Field Effect Transistor
  • neuro-robotics

Cite this

Taube Navaraj, W., García Núñez, C., Shakthivel, D., Vinciguerra, V., Labeau, F., Gregory, D. H., & Dahiya, R. (2017). Nanowire FET based neural element for robotic tactile sensing skin. Frontiers in Neuroscience, 11, [501]. https://doi.org/10.3389/fnins.2017.00501
Taube Navaraj, William ; García Núñez, Carlos ; Shakthivel, Dhayalan ; Vinciguerra, Vincenzo ; Labeau, Fabrice ; Gregory, Duncan H. ; Dahiya, Ravinder. / Nanowire FET based neural element for robotic tactile sensing skin. In: Frontiers in Neuroscience. 2017 ; Vol. 11.
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Taube Navaraj, W, García Núñez, C, Shakthivel, D, Vinciguerra, V, Labeau, F, Gregory, DH & Dahiya, R 2017, 'Nanowire FET based neural element for robotic tactile sensing skin', Frontiers in Neuroscience, vol. 11, 501. https://doi.org/10.3389/fnins.2017.00501

Nanowire FET based neural element for robotic tactile sensing skin. / Taube Navaraj, William; García Núñez, Carlos; Shakthivel, Dhayalan; Vinciguerra, Vincenzo; Labeau, Fabrice; Gregory, Duncan H.; Dahiya, Ravinder.

In: Frontiers in Neuroscience, Vol. 11, 501, 20.09.2017.

Research output: Contribution to journalArticle

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T1 - Nanowire FET based neural element for robotic tactile sensing skin

AU - Taube Navaraj, William

AU - García Núñez, Carlos

AU - Shakthivel, Dhayalan

AU - Vinciguerra, Vincenzo

AU - Labeau, Fabrice

AU - Gregory, Duncan H.

AU - Dahiya, Ravinder

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N2 - This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs) based hardware-implementable neural network (HNN) approach for tactile data processing in electronic skin (e-skin). The viability of Si nanowires (NWs) as the active material for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin) in the backplane. The modeling and simulation of υ-NWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υ-NWFETs as the building block for HNN. The simulation has been further extended to υ-NWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO based capacitive tactile sensors array) integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υ-NWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET devices confirm the dependence of turn-off voltages on the (synaptic) weight of each gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals.

AB - This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs) based hardware-implementable neural network (HNN) approach for tactile data processing in electronic skin (e-skin). The viability of Si nanowires (NWs) as the active material for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin) in the backplane. The modeling and simulation of υ-NWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υ-NWFETs as the building block for HNN. The simulation has been further extended to υ-NWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO based capacitive tactile sensors array) integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υ-NWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET devices confirm the dependence of turn-off voltages on the (synaptic) weight of each gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals.

KW - silicon nanowire

KW - tactile skin

KW - sparse coding

KW - Nanowire Field Effect Transistor

KW - neuro-robotics

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DO - 10.3389/fnins.2017.00501

M3 - Article

VL - 11

JO - Frontiers in Neuroscience

JF - Frontiers in Neuroscience

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