Incorporation of the electrode-electrolyte interface into finite-element models of metal microelectrodes

Donald R. Cantrell, Samsoon Inayat, Allen Taflove, Rodney S. Ruoff, John B. Troy

Research output: Contribution to journalArticlepeer-review

85 Scopus citations


An accurate description of the electrode-electrolyte interfacial impedance is critical to the development of computational models of neural recording and stimulation that aim to improve understanding of neuro-electric interfaces and to expedite electrode design. This work examines the effect that the electrode-electrolyte interfacial impedance has upon the solutions generated from time-harmonic finite-element models of cone- and disk-shaped platinum microelectrodes submerged in physiological saline. A thin-layer approximation is utilized to incorporate a platinum-saline interfacial impedance into the finite-element models. This approximation is easy to implement and is not computationally costly. Using an iterative nonlinear solver, solutions were obtained for systems in which the electrode was driven at ac potentials with amplitudes from 10 mV to 500 mV and frequencies from 100 Hz to 100 kHz. The results of these simulations indicate that, under certain conditions, incorporation of the interface may strongly affect the solutions obtained. This effect, however, is dependent upon the amplitude of the driving potential and, to a lesser extent, its frequency. The solutions are most strongly affected at low amplitudes where the impedance of the interface is large. Here, the current density distribution that is calculated from models incorporating the interface is much more uniform than the current density distribution generated by models that neglect the interface. At higher potential amplitudes, however, the impedance of the interface decreases, and its effect on the solutions obtained is attenuated.

Original languageEnglish (US)
Pages (from-to)54-67
Number of pages14
JournalJournal of Neural Engineering
Issue number1
StatePublished - Mar 1 2008

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience


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