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Mitigating Interfacial Contamination for Scalable Integration of Graphene in Neuroelectronic Devices
Aina Galceran1, Marta Delgà-Fernández1, Xavi Illa2,3
1Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, 08193 Bellaterra, Spain.
Accounts of Materials Research
|May 4, 2026
Summary
Graphene field-effect transistors (gSGFETs) show promise for neuroelectronic interfaces but are hindered by processing contamination. Sacrificial layers, like copper, offer a solution to protect graphene and improve device reliability for scalable applications.
Area of Science:
- Materials Science
- Neurotechnology
- Nanotechnology
Background:
- Graphene exhibits unique properties (transparency, flexibility, biocompatibility, electrical performance) making it ideal for next-generation neuroelectronic interfaces.
- Solution-gated field-effect transistors (gSGFETs) fabricated with graphene offer high spatial density and DC-coupled, wide-bandwidth neural signal recording.
- Graphene's sensitivity to surface charges makes device performance critically dependent on interfacial physicochemical phenomena and the pristine condition of the graphene layer.
Purpose of the Study:
- To highlight the potential of gSGFETs in neurotechnology.
- To review the impact of uncontrolled graphene surface states on device behavior during microfabrication.
- To explore strategies for mitigating process-induced contamination and improving gSGFET reliability.
Main Methods:
- Review of existing microfabrication processes for graphene-based devices.
- Analysis of the effects of photolithographic processing on graphene integrity and device characteristics.
- Investigation of graphene cleaning methods and the development of sacrificial protective layers.
Main Results:
- Photolithography introduces residues, adsorbed charges, and defects, leading to doping, reduced mobility, and time-dependent shifts in gSGFET transfer characteristics.
- Current cleaning methods are mild and insufficient to ensure the homogeneity and reproducibility required for reliable gSGFET technology.
- Sacrificial protective layers, particularly copper (Cu), show promise as effective barriers against process-induced contamination.
Conclusions:
- Process-induced contamination significantly degrades gSGFET performance, limiting device-to-device reproducibility and scalability.
- Mild cleaning approaches are inadequate for achieving the necessary graphene surface quality for reliable neuroelectronic interfaces.
- Integrating sacrificial layers, such as Cu, into microfabrication workflows is a promising strategy to enhance graphene-based neurotechnology's reliability and enable industrial translation.
