The Materials Science Foundation Supporting the Microfabrication of Reliable Polyimide-Metal Neuroelectronic Interfaces

Thin-film polyimide-metal neuroelectronic interfaces hold the potential to alleviate many neurological disorders. However, their long-term reliability is challenged by an aggressive implant environment that causes delamination and degradation of critical materials, resulting in a degradation or complete loss of implant function. Herein, a rigorous and in-depth analysis is presented on the fabrication and modification of critical materials in these thin-film neural interfaces. Special attention is given to improving the interfacial adhesion between thin films and processing modifications to maximize device reliability. Fundamental material analyses are performed on the polyimide substrate and adhesion-promotion candidates, including amorphous silicon carbide (a-SiC:H), amorphous carbon, and silane coupling agents. Basic fabrication rules are identified to markedly improve polyimide self-adhesion, including optimizing the polyimide-cure profile and maximizing high-energy surface activation. In general, oxide-forming materials are identified as poor adhesive aids to polyimide without targeted modifications. Methods are identified to incorporate effective a-SiC:H interfacial layers to improve metal adherence to polyimide, in addition to examples of alloying between adjacent material layers that can impact the trace resistivity and long-term reliability of the thin-film interfaces. The provided rationale and consequences of key decisions made should promote more reproducible science using robust and reliable neuroelectronic technology.

Automated summary

This study presents a rigorous and in-depth analysis on the fabrication and modification of critical materials in thin-film polyimide-metal neuroelectronic interfaces, with a focus on improving the interfacial adhesion between thin films and maximizing device reliability. Methods to enhance metal adherence to polyimide through effective a-SiC:H interfacial layers are identified, along with examples of alloying between adjacent material layers impacting trace resistivity and long-term reliability of the interfaces. The rationale and consequences of key decisions made aim to promote more reproducible science using robust and reliable neuroelectronic technology.