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Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications.

ABSTRACT: 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.

SUBMITTER: Browning LA

PROVIDER: S-EPMC8000135 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications.

Browning Leo A LA Watterson William W Happe Erica E Silva Savannah S Abril Valenzuela Roberto R Smith Julian J Dierkes Marissa P MP Taylor Richard P RP Plank Natalie O V NOV Marlow Colleen A CA

Nanomaterials (Basel, Switzerland) 20210304 3

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 fea ...[more]

PMID: 33806365

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Project description:Investments in the transfer and storage of thermal energy along with renewable energy sources strengthen health and economic infrastructure. These factors intensify energy diversification and the more rapid post-COVID recovery of economies. Ionanofluids (INFs) composed of long multiwalled carbon nanotubes (MWCNTs) rich in sp2-hybridized atoms and ionic liquids (ILs) display excellent thermal conductivity enhancement with respect to the pure IL, high thermal stability, and attractive rheology. However, the influence of the morphology, physicochemistry of nanoparticles and the IL-nanostructure interactions on the mechanism of heat transfer and rheological properties of INFs remain unidentified. Here, we show that intertube nanolayer coalescence, supported by 1D geometry assembly, leads to the subzipping of MWCNT bundles and formation of thermal bridges toward 3D networks in the whole INF volume. We identified stable networks of straight and bent MWCNTs separated by a layer of ions at the junctions. We found that the interactions between the ultrasonication-induced breaking nanotubes and the cations were covalent in nature. Furthermore, we found that the ionic layer imposed by close MWCNT surfaces favored enrichment of the cis conformer of the bis(trifluoromethylsulfonyl)imide anion. Our results demonstrate how the molecular perfection of the MWCNT structure with its supramolecular arrangement affects the extraordinary thermal conductivity enhancement of INFs. Thus, we gave the realistic description of the interactions at the IL-CNT interface with its (super)structure and chemistry as well as the molecular structure of the continuous phase. We anticipate our results to be a starting point for more complex studies on the supramolecular zipping mechanism. For example, ionically functionalized MWCNTs toward polyionic systems─of projected and controlled nanolayers─could enable the design of even more efficient heat-transfer fluids and miniaturization of flexible electronics.

Dataset Information

Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications.

Publications

Investigation of Fractal Carbon Nanotube Networks for Biophilic Neural Sensing Applications.

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