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Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications

We propose a carbon-nanotube-based neural sensor designed to exploit the electrical sensitivity of an inhomogeneous fractal network of conducting channels. This network forms the active layer of a multi-electrode field effect transistor that in future applications will be gated by the electrical pot...

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Autores principales: Browning, Leo A., Watterson, William, Happe, Erica, Silva, Savannah, Abril Valenzuela, Roberto, Smith, Julian, Dierkes, Marissa P., Taylor, Richard P., Plank, Natalie O. V., Marlow, Colleen A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8000135/
https://www.ncbi.nlm.nih.gov/pubmed/33806365
http://dx.doi.org/10.3390/nano11030636
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author Browning, Leo A.
Watterson, William
Happe, Erica
Silva, Savannah
Abril Valenzuela, Roberto
Smith, Julian
Dierkes, Marissa P.
Taylor, Richard P.
Plank, Natalie O. V.
Marlow, Colleen A.
author_facet Browning, Leo A.
Watterson, William
Happe, Erica
Silva, Savannah
Abril Valenzuela, Roberto
Smith, Julian
Dierkes, Marissa P.
Taylor, Richard P.
Plank, Natalie O. V.
Marlow, Colleen A.
author_sort Browning, Leo A.
collection PubMed
description We propose a carbon-nanotube-based neural sensor designed to exploit the electrical sensitivity of an inhomogeneous fractal network of conducting channels. This network forms the active layer of a multi-electrode field effect transistor that in future applications will be gated by the electrical potential associated with neuronal signals. Using a combination of simulated and fabricated networks, we show that thin films of randomly-arranged carbon nanotubes (CNTs) self-assemble into a network featuring statistical fractal characteristics. The extent to which the network’s non-linear responses will generate a superior detection of the neuron’s signal is expected to depend on both the CNT electrical properties and the geometric properties of the assembled network. We therefore perform exploratory experiments that use metallic gates to mimic the potentials generated by neurons. We demonstrate that the fractal scaling properties of the network, along with their intrinsic asymmetry, generate electrical signatures that depend on the potential’s location. We discuss how these properties can be exploited for future neural sensors.
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spelling pubmed-80001352021-03-28 Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications Browning, Leo A. Watterson, William Happe, Erica Silva, Savannah Abril Valenzuela, Roberto Smith, Julian Dierkes, Marissa P. Taylor, Richard P. Plank, Natalie O. V. Marlow, Colleen A. Nanomaterials (Basel) Article We propose a carbon-nanotube-based neural sensor designed to exploit the electrical sensitivity of an inhomogeneous fractal network of conducting channels. This network forms the active layer of a multi-electrode field effect transistor that in future applications will be gated by the electrical potential associated with neuronal signals. Using a combination of simulated and fabricated networks, we show that thin films of randomly-arranged carbon nanotubes (CNTs) self-assemble into a network featuring statistical fractal characteristics. The extent to which the network’s non-linear responses will generate a superior detection of the neuron’s signal is expected to depend on both the CNT electrical properties and the geometric properties of the assembled network. We therefore perform exploratory experiments that use metallic gates to mimic the potentials generated by neurons. We demonstrate that the fractal scaling properties of the network, along with their intrinsic asymmetry, generate electrical signatures that depend on the potential’s location. We discuss how these properties can be exploited for future neural sensors. MDPI 2021-03-04 /pmc/articles/PMC8000135/ /pubmed/33806365 http://dx.doi.org/10.3390/nano11030636 Text en © 2021 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 (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Browning, Leo A.
Watterson, William
Happe, Erica
Silva, Savannah
Abril Valenzuela, Roberto
Smith, Julian
Dierkes, Marissa P.
Taylor, Richard P.
Plank, Natalie O. V.
Marlow, Colleen A.
Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications
title Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications
title_full Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications
title_fullStr Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications
title_full_unstemmed Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications
title_short Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications
title_sort investigation of fractal carbon nanotube networks for biophilic neural sensing applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8000135/
https://www.ncbi.nlm.nih.gov/pubmed/33806365
http://dx.doi.org/10.3390/nano11030636
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