Measurement of Signal‐to‐Noise Ratio In Graphene‐Based Passive Microelectrode Arrays

This work aims to investigate the influence of various electrode materials on the signal-to-noise ratio (SNR) of passive microelectrode arrays (MEAs) intended for use in neural interfaces. Noise reduction substantially improves the performance of systems which electrically interface with extracellular solutions. The MEAs are fabricated using gold, indium tin oxide (ITO), inkjet printed (IJP) graphene, and chemical vapor deposited (CVD) graphene. 3D-printed Nylon reservoirs are adhered to glass substrates with identical MEA patterns and filled with neuronal cell culture media. To precisely control the electrode area and minimize the parasitic coupling of metal interconnects and solution, SU-8 photoresist is patterned to expose only the area of the electrode to solution and cap the remainder of the sample. Voltage signals with varying amplitude and frequencies are applied to the solution using glass micropipettes, and the response is measured on an oscilloscope from a microprobe placed on the contact pad external to the reservoir. The time domain response signal is transformed into a frequency spectrum, and SNR is calculated. As the magnitude or the frequency of the input signal gets larger, a significantly increased signal-to-noise ratio was observed in CVD graphene MEAs compared to others. This result indicates that 2-dimensional nanomaterials such as graphene can provide better signal integrity and potentially lead to improved performance in hybrid neural interface systems.