Monolithic Integration of 2D and 3D Carbon MEMS-Based Multi-Microelectrode Arrays for Neural Interfaces-on-Chip
High Resolution Image Download MS PowerPoint Slide Microelectrodes play a crucial role in Nervous System-on-Chip (NoC) technologies by enabling advanced neural circuit modeling. However, challenges remain in electrode patternability, design flexibility, scalability, long-term insulation reliability, and biocompatibility, while standard microfabrication processes restrict the integration of functional materials for advanced MEA designs. Despite significant progress in bioelectronic materials, electrode−tissue interfaces remain a major bottleneck. Carbon offers excellent biocompatibility and mechanical and chemical robustness but remains challenging to pattern compared to conventional metallic electrodes. Consequently, carbon microelectrodes are increasingly explored for real-time monitoring of neurotransmitters, key indicators of neural network activity. Complex multimaterial architectures and aggressive pretreatment strategies are often employed to enhance performance; however, limited control over the resulting electrode structures hampers a clear correlation between microelectrode behavior and design. Optimizing electrode dimensions and geometry is therefore critical for improving design versatility and spatial resolution. Here, we present a modular multi-microelectrode array (MEA) platform based on pyrolytic carbon (PyC), enabling the monolithic integration of multiple electrode geometries, inter-electrode spacings, and 3D micropillar architecture within a single, unified fabrication process. Lithographically defined PyC microelectrodes were fabricated from SU-8 photoresist via pyrolysis. The fabricated MEAs were validated using cyclic voltammetry measurements. Through geometric tuning within this modular design, ultramicroelectrode-like behavior was achieved using scalable, low-cost photolithographic fabrication. A 3D PyC microelectrode (20 μm diameter, 400 μm inter-electrode spacing) demonstrated a dopamine detection limit of 5 nM over a concentration range of 0.01−100 μM. Biocompatibility of the PyC surfaces was confirmed through cell viability assays using SH-SY5Y neuroblastoma cells after 10 days of culture.
Authors
- Sami Franssila (ORCID: https://orcid.org/0000-0003-1386-3684)
- Lingju Meng (ORCID: https://orcid.org/0000-0003-3106-5408)
- Joonas J. Heikkinen (ORCID: https://orcid.org/0000-0003-2870-7940)
- Yağmur Demircan Yalçın (ORCID: https://orcid.org/0000-0002-3363-489X)
- Ville P. Jokinen (ORCID: https://orcid.org/0000-0001-6347-7461)
- Anas Al‐Azawi (ORCID: https://orcid.org/0000-0002-9576-9159)
- Yalda Shoja (ORCID: https://orcid.org/0000-0003-0867-3069)
- Noora Isoaho (ORCID: https://orcid.org/0000-0003-1687-9796)
- Jouko Lahtinen (ORCID: https://orcid.org/0000-0002-1192-9945)
- Pei‐Yin Chi
- Henrik Romppainen
- Regina Luttge
Institutions
- NanoScale Corporation (United States) (US)
- Eindhoven University of Technology (NL)
- Aalto University (FI)
Publication Details
- Journal
- ACS Applied Electronic Materials
- Published
- 2026-06-16
- DOI
- https://doi.org/10.1021/acsaelm.6c00229
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00