Simulation and Measurement of Neuroelectrodes' Characteristics with Integrated High Aspect Ratio Nano Structures

  • Improving the interface between electrodes and neurons has been the focus of research for the last decade. Neuroelectrodes should show small geometrical surface area and low impedance for measuring and high charge injection capacities for stimulation. Increasing the electrochemically active surface area by using nanoporous electrode material or by integrating nanostructures onto planar electrodes is a common approach to improve this interface. In this paper a simulation approach for neuro electrodes' characteristics with integrated high aspect ratio nano structures based on a point-contact-model is presented. The results are compared with experimental findings conducted with real nanostructured microelectrodes. In particular, effects of carbon nanotubes and gold nanowires integrated onto microelectrodes are described. Simulated and measured impedance properties are presented and its effects onto the transfer function between the neural membrane potential and the amplifier output signal are studied based on the point-contact-model. Simulations show, in good agreement with experimental results, that electrode impedances can be dramatically reduced by the integration of high aspect ratio nanostructures such as gold nanowires and carbon nanotubes. This lowers thermal noise and improves the signal-to-noise ratio for measuring electrodes. It also may increase the adhesion of cells to the substrate and thus increase measurable signal amplitudes.

Export metadata

Additional Services

Search Google Scholar
Metadaten
Author:Christoph Nick, Helmut Schlaak, Christiane Thielemann
DOI:https://doi.org/10.3934/matersci.2015.3.189
Parent Title (English):AIMS Journal
Document Type:Article
Language:English
Year of Completion:2015
Release Date:2020/04/29
GND Keyword:Neuronales Netz; Mikroelektrode
Volume:2015
Issue:2
First Page:189
Last Page:202
Urheberrecht:0
research focus :Intelligent Systems / Artifical Intelligence and Data Science
Intelligent Systems / Clean Tech
Intelligent Systems / Intelligent Sensors and Signals
Materials / Material Testing & Sensor Technology
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International
Einverstanden ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.