Graphene-based neural interfaces offer an innovative solution to surpass the resolution limit of traditional neural recording, integrating neuroelectronics with optogenetics for combined electrophysiological and optical neural monitoring, among others. Three important factors in these interfaces are achieving a high signal-to-noise ratio (SNR), maintaining effective stimulation properties, and ensuring strong cell adhesion to neural tissue, which can be enhanced through surface topography modifications. This work explores two main approaches to enhance graphene-based neural interfaces: (1) exploring the creation of thin graphene films on molybdenum to integrate transistors and electrodes within a single fabrication process, which can potentially enhance the signal-to-noise ratio (SNR) while maintaining stimulation efficacy; and (2) creating corrugated graphene structures that increase surface area and improve cell adhesion. A major challenge in this work is establishing a transfer-free chemical vapor deposition (CVD) process on molybdenum for both approaches. While this method offers significant benefits, such as reducing defects and contamination, the challenge lies in the limited understanding of the mechanisms behind graphene growth on this catalyst. Exploring new molybdenum configurations to provide a better understanding of the graphene growth mechanism on this catalyst is also a relevant part of this work.
Experiments revealed that graphene grown on thick, unpatterned molybdenum produced high quality few layer graphene (FLG), while patterned thick molybdenum produced multilayer structures with high defect density. Based on the results obtained, a mechanism for graphene growth on thick molybdenum catalysts is proposed. However, the decision was made to proceed with the second research approach due to time limitations. Considering corrugated graphene structures, Raman analysis showed higher-quality graphene layers within the valleys, fact that supports the proposed growth model. sheet resistance values ranged from 60 Ω/sq – 180 Ω/sq, being these values among the lowest reported in the literature for undoped graphene. These low values are attributed to the combination of an FLG graphene with good interlayer electronic coupling, which is possible because of the low number of defects in the material. Results are promising for enabling high-density optically transparent neural interfaces with graphene tracks. Additionally, small and denser corrugations enhanced the electrode surface area, showing reduced impedance at 1 kHz compared to flat electrodes. Electrodes with 1 μm, 5 μm, and 20 μm corrugations shown impedance reductions in comparison to flat electrodes, demonstrating an increased surface area. The area normalized impedance decreased from 35.5 kΩ ± 0.7 kΩ for flat electrodes to a minimum of 26.2 kΩ ± 1.1 kΩ. The electrodes achieved a maximum charge storage capacity (CSC) of 80.6 μC/cm2 and a maximum charge injection capacity (CIC) of 7.71 μC/cm2, which are lower than the threshold for stimulation applications. However, these values could be potentially optimized through fabrication refinement. Furthermore, the biocompatibility tests indicated that corrugated graphene patterns are biocompatible have the potential to actively influence stem cell cytoskeleton dynamics, highlighting their promise as a safe and novel inclusion in interfaces for next- generation neural applications.