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Comparative study of tuning of microfabrication parameters for improving electrochemical performance of platinum and glassy carbon microelectrodes in neural prosthetics

  • Nha Uyen Huynh
  • Sam KassegneEmail author
  • George Youssef
Technical Paper
  • 18 Downloads

Abstract

Neural prosthetics, which are increasingly being considered for the dual functionalities of recording and stimulation, are implanted in a corrosive biochemical environment that requires them to possess superior electrical and electrochemical stability and performance. These probes are required to withstand these operating conditions through billions of cycles of pulses of electrical stimulations and also maintain electrochemical sensitivity for potential applications in voltammetry. In this research, microelectrodes made of two material systems; namely, platinum and glassy carbon, supported on a flexible substrate are fabricated and investigated for correlation between process parameters and the electrochemical efficacy of the neural interfaces, particularly charge storage capacity and corrosion rate. Using scanning electron and atomic force microscopies, the correlation between process parameters, surface morphology and topography in both platinum and glassy carbon were investigated. The results demonstrate that changes in surface topography and the rate of corrosion are correlated to variations in the process parameters. Furthermore, the results indicate a relationship between surface roughness and corrosion rate, in which the increase or decrease of the former corresponds to a similar change in the latter.

Notes

Acknowledgements

This material is based on research work supported by National Science Foundation (NSF) Grant Number EEC-1028725 under the ERC program. The authors also acknowledge the use of equipment at the San Diego State University Electron Microscopy Facility acquired by NSF instrumentation grant DBI-0959908. The authors are grateful for Mr. Atif Mohammed for his assistance and insightful discussions about the AFM.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Mechanical Engineering DepartmentSan Diego State UniversitySan DiegoUSA
  2. 2.NSF-ERC Center for NeurotechnologySeattleUSA

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