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author:

Li, L. (Li, L..) [1] | Jiang, C. (Jiang, C..) [2]

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Scopus

Abstract:

Implantable electrodes are crucial for stimulation safety and recording quality of neuronal activity. To enhance their electrochemical performance, electrodeposited nanostructured platinum (nanoPt) and iridium oxide (IrOx) have been proposed due to their advantages of in situ deposition and ease of processing. However, their unstable adhesion has been a challenge in practical applications. This study investigated the electrochemical performance and stability of nanoPt and IrOx coatings on hierarchical platinum-iridium (Pt-Ir) substrates prepared by femtosecond laser, compared with the coatings on smooth Pt-Ir substrates. Ultrasonic testing, agarose gel testing, and cyclic voltammetry (CV) testing were used to evaluate the coatings’ stability. Results showed that the hierarchical Pt-Ir substrate significantly enhanced the charge-storage capacity of electrodes with both coatings to more than 330 mC/cm2, which was over 75 times that of the smooth Pt-Ir electrode. The hierarchical substrate could also reduce the cracking of nanoPt coatings after ultrasonic, agarose gel and CV testing. Although some shedding was observed in the IrOx coating on the hierarchical substrate after one hour of sonication, it showed good stability in the agarose gel and CV tests. Stable nanoPt and IrOx coatings may not only improve the electrochemical performance but also benefit the function of neurobiochemical detection. © 2023 by the authors.

Keyword:

coating stability femtosecond laser hierarchical structures iridium oxide neural electrodes platinum

Community:

  • [ 1 ] [Li L.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Jiang C.]National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 100084, China
  • [ 3 ] [Li L.]National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 100084, China
  • [ 4 ] [Li L.]IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China

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Source :

Micromachines

ISSN: 2072-666X

Year: 2024

Issue: 1

Volume: 15

3 . 0 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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