Abstract:
Neural interfaces are engineered with implantable electrodes that are key in forming efficient connection between the brain and a machine. The implantable electrodes are essentially a combination of exposed conductive regions and passivated coatings. The conductive coatings act as sensors or stimulators while the insulation encapsulates the conductive tracks and device to provide protection against the harsh in vivo environment. For efficient design of implantable electrodes it is important to understand the factors affecting the interface of conductive coatings and neural tissue. Assuming the conductive materials are noble and corrosion-free, the reliability of the device would highly depend on the long term stability of the encapsulation. While the efficiency metric is different for conductive and insulating materials, in both cases electrochemical impedance spectroscopy and equivalent circuit model fitting can be used to diagnose their performance. This thesis is a culmination of experimental and modeling work performed on implantable conducting and insulating coatings for neural interfaces. For conductive coatings (iridium oxide and carbon nanotubes) the goal was to characterize the difference between in vitro and in vivo performance. For insulation (Parylene C and Al2O3-Parylene C) the aim was to estimate the mean time to failure and to understand the modes of failure.
