Mitigating Interfacial Contamination for Scalable Integration of Graphene in Neuroelectronic Devices

In the past decade, graphene has gained increasing attention as a material for the next generation of neuroelectronic interfaces thanks to its unique combination of properties, including transparency, flexibility, biocompatibility, and electrical performance. When integrated into thin-film technology microfabrication processes, graphene enables highly conformable and low invasive arrays of solution-gated field-effect transistors (gSGFETs), which are micrometric transducers that combine higher spatial density with the capability to record DC-coupled wide-bandwidth neural signals. The same atomic scale nature of graphene that confers its exceptional sensitivity to surface charges also renders device performance strongly dependent on interfacial physicochemical phenomena at the substrate-graphene-medium boundary, which, in turn, are strongly dependent on the quality and pristine condition of the graphene layer. From a materials science perspective, maintaining the structural and electronic integrity of graphene throughout the entire microfabrication process represents a great challenge. Photolithographic processing often introduces polymeric residues, resulting in adsorbed charges and defect sites that induce residual doping, degrade mobility, and lead to time-dependent shifts in the transfer characteristics of gSGFETs. These changes induced by processing reduce sensor sensitivity and generate device-to-device variability, which currently limits reproducible benchmarking and scale-up of the technology. In this Account, we highlight the remarkable potential of gSGFETs in neurotechnology and review the implications that the uncontrolled graphene surface states have on device behavior. We then present process engineering efforts aimed at addressing this issue through graphene cleaning methods. However, these cleaning approaches are necessarily mild to avoid damaging graphene and have not yet demonstrated the ability to fully ensure the homogeneity and reproducibility required for reliable technology. Finally, we examine emerging strategies based on the development of sacrificial protective layers, which act as effective barriers against process-induced contamination. We propose Cu as a particularly promising candidate given that, as the most common substrate for graphene growth, its etching chemistry has already been widely explored. The integration of sacrificial layers in the standardized microfabrication workflows represents a significant opportunity to improve the graphene-based technology's reliability, enabling its advancement and translation toward industrial applications.