Brain Machine Interfaces (BMI) provide a communication pathway between the electrical conducting units of the brain (neurons) and external devices. BMI technology may provide improved neurological and physiological functions to patients suffering from disabilities due to damaged nervous systems. Unfortunately, microelectrodes used in Intracortical Neural Interfaces (INI), a subset of the BMI device family, have yet to demonstrate long-term in vivo performance due to material, mechanical and electrical failures. Many state-of-the-art INI devices are constructed using stacks of multiple materials, such as silicon (Si), titanium (Ti), platinum (Pt), parylene C, and polyimide. Not only must each material tolerate the biological environment without exacerbating the inflammatory response, each of the materials used must physically withstand the environment as well as interact well with each other.
One approach to address abiotic mechanisms has been optimizing the materials required to fabricate the INI devices. Silicon Carbide (SiC) is a physically robust, hemo and biocompatible, and chemically inert semiconductor. An ‘all-SiC’, or monolithic SiC, device may be the disruptive technology needed in the BMI field to finally achieve long-term and wide-spread use of this technology in humans. The all-SiC device concept is where SiC serves as all device layers: the base (substrate), the conducting traces (electrodes), and the surface conformal insulating layer. The monolithic SiC neural probe is realized by forming high-quality pn junctions of heavily doped SiC on a layer of the opposite polarity. Heavily doped semiconductors display semi-metallic electrical performance, which allow for efficient electrical conduction in the electrode without the deleterious effects of metal ions interacting with the neural environment. The conformal insulator is realized using amorphous-SiC (a-SiC) which can be patterned to open windows to allow electrical conduction to occur between the electrode tips and the brain.
Several generations of monolithic SiC devices have been fabricated, tested and are reported in this dissertation. The devices were fabricated utilizing two polytypes of SiC (4H-SiC and 3C-SiC). The monolithic SiC microelectrodes were fabricated utilizing techniques used in the fabrication of Si based microelectrodes. Monolithic SiC devices fabricated include planar single-ended MEAs (with varying lengths and varying active recording area), 60-channel MEAs for in-vitro studies, and 16-electrode Michigan style neural probes for in-vivo studies. Electrical testing of the pn junction demonstrated that the 4H-SiC device can block a forward bias voltage of up to 2.3V and displays reverse bias leakage below 1 nArms well past -20V. Current leakage between adjacent electrodes was ~7.5 nArms over a voltage range of -50V to +50V. Furthermore, electrochemical results show that the 4H-SiC microelectrodes interact with an electrochemical environment primarily through capacitive mechanisms and has an impedance comparable to gold electrodes. Electrode impedance ranged from 675±130 kΩ (GSA = 496 µm2) to 46.5±4.80 kΩ (GSA = 500K µm2). However, the 4H-SiC devices cannot deliver charge as efficiently as other conventionally used microelectrode materials, such as iridium oxide (IrOx), but a larger water window compensates for this since larger stimulation voltages are supported compared to IrOx.
All studies and data collected thus far indicate that the monolithic SiC neural device can aid in the advancement of chronic INI use in clinical settings. The all-SiC devices rely on the integration of only robust and highly compatible SiC material, they may offer a promising solution to probe delamination and biological rejection associated with the use of multiple materials used in many current INI devices. Follow-on work is planned to prove this assertion via in vivo studies.
Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-8671 |
Date | 09 November 2018 |
Creators | Bernardin, Evans K. |
Publisher | Scholar Commons |
Source Sets | University of South Flordia |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Graduate Theses and Dissertations |
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