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 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.

Data on liquid gated CNT network FETs on flexible substrates.

This article presents the raw and analyzed data from a set of experiments performed to study the role of junctions on the electrostatic gating of carbon nanotube (CNT) network field effect transistor (FET) aptasensors. It consists of the raw data used for the calculation of junction and bundle densities and describes the calculation of metallic content of the bundles. In addition, the data set consists of the electrical measurement data in a liquid gated environment for 119 different devices with four different CNT densities and summarizes their electrical properties.

Metallic-semiconducting junctions create sensing hot-spots in carbon nanotube FET aptasensors near percolation.

Easily fabricated random network carbon nanotube field-effect transistors (CNT-FETs) have benefitted from improved separation techniques to deliver CNTs with current formulations providing at least 99% semiconducting tube content. Amongst the most promising applications of this device platform are electronic biosensors, where the network conduction is affected through tethered probes such as aptamers which act as molecular scale electrostatic gates. However, the prevailing assumption that these biosensor devices would be optimized if metallic tubes were entirely eliminated has not been examined.