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Paper   IPM / Nano-Sciences / 15887
School of Nano Science
  Title:   Size and Geometry of Multielectrode Arrays Determine the Efficiency of Electrical Interaction With Neurons Through Double-Layer Capacitance
  Author(s): 
1.  Mohaddese Vafaie
2.  Raheleh Mohammadpour
3.  Manouchehr Vossoughi
4.  Pezhman Sasanpour
  Status:   Published
  Journal: IEEE Sensors J.
  No.:  8
  Vol.:  19
  Year:  2019
  Publisher(s):   IEEE
  Supported by:  IPM
  Abstract:
Multielectrode array (MEA) structures are the vital parts in the interface between neural structures and external electronic circuits, both in excitation and detection. As a transducer, the performance of electrodes has direct effect on the quality of the recorded neural signal, as well as induced charge density during the stimulation in neural prosthesis. The size and geometry of the electrode structure have distinct effect on the performance of electrodes accordingly. In this paper, the effect of size and geometry of the electrodes has been investigated in their performance and the impedimetric features of the fabricated electrodes with different structures have been studied. Based on the importance of the electric double-layer (EDL) capacitance in the charge transduction, the effect of size and geometries in equal surface area on the EDL capacitance has been investigated, computationally and experimentally. Using computational a Modeling approach, the EDL capacitance for different size and geometries has been analyzed using finite element method in COMSOL environment. The electrodes with different size and geometries have been fabricated, and their EDL capacitance has been evaluated using electrochemical characterization techniques. The results indicate that the size and geometry of MEAs have the noticeable effect on their performances. Also, the structures with sharp corners (while having the same surface area) will show the highest value of double-layer capacitance, and the fragmentation of surface will increase the capacitance and the performance of operation. The results could be exploited for further optimization of flexible MEA for neural implants and brain excitations.

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