Manufacturing Process for Ultra-Thin, Ultra-Reliable, and Implantable Liquid-Crystal-Polymer-Based Bioelectronic Interfaces

PROJECT SUMMARY: This proposal seeks to serve the needs of patients that require high-electrode-density neural interfaces that are extremely flexible, cause minimal tissue response, and function for the life of the patient. Clinical applications include high-channel-count brain-machine interfaces (BMI) to restore sensory and motor function, high-channel- count nerve interfaces for sensing and controlling state-of-the-art prosthetics limbs, next-generation deep-brain stimulation (DBS) systems, and many others. We propose to overcome this longevity barrier by significantly advancing the manufacturing processes used to produce implantable thin-film neural interfaces based on liquid crystal polymers (LCP), which when used in a thick-film form have demonstrated exceptional robustness and reliability. The work proposed is focused on significantly improving LCP-based neural-interface technology in two innovative and independent ways. First, in Aim 1 we will develop a microfabrication process that can produce bonded multi-layer LCP-based devices that are at least 5X thinner than possible with today's manufacturing processes (i.e.,  10 μm compared to  50 μm) without compromising the strength of the bond between the LCP layers and between the LCP layers and a metal layer. Second, in Aim 2 we will develop a manufacturing process that can produce metal features on highly roughened LCP that are 10X thinner (i.e., 1 μm compared to >10 μm) and 5X narrower (i.e., 5 μm compared to  25 μm) than demonstrated commercially with LCP today, and in a manner that increases the bond strength of the metal layer to both LCP layers, increases electrical-isolation reliability, and does not compromise electrical-conduction reliability. Much thinner and narrower interfaces have been shown to cause far less adverse tissue response and should result in higher signal to noise ratio and interface operational lifetime. To assess the material and electrical reliability of our much thinner and narrower LCP interfaces, we will use aggressive RAA soak tests and statistically measure channel isolation and resistance as a function of dielectric-layer parameters (i.e., layer thickness, roughness, bonding parameters, and other process parameters) and metal-layer parameters (i.e., metal trace thickness, width, separation, length, and integration method). We will compare results with implants produced using other thin-film polymer-metal neural-interface technologies (e.g., polyimide) and commercial thick-film LCP.