Fabrication of planar full-SiC-based nanostructured multi-electrode arrays (MEA) for neural interfaces
Year: 2026
Type: article
Abstract: Despite many efforts for developing robust neural implants, existing devices still suffer from short lifespans. The device lifespan is limited by the triggering of the immune response after implantation, leading to structural and functional degradation of the device materials. Among the considered alternatives, Silicon Carbide (SiC) is a particularly attractive material due to its chemical inertness and biocompatibility. Moreover, monolithic SiC-based neural interfaces may be less prone to layer delamination observed in polymer-based implants. Recording neural signals with high spatial resolution requires limiting the electrode dimension at the microscale. However, decreasing the microelectrode dimension impacts the electrochemical impedance and degrades the signal-to-noise ratio. To overcome this restriction, structurization of the electrode surface using nano and microfabrication techniques appears to be a suitable solution allowing to increase the active area without the need of depositing additional active material, thus preserving the monolithic character of the device. In this study, we developed planar multi-electrode arrays fully based on a 4H-SiC stack composed of conductive n-doped and semi-insulating V-doped layer grown by Chemical Vapor Deposition (CVD) on a bulk wafer. To boost the electrochemical performances of the device, the electrode active surface area was nanostructured with a nanopillar array patterned using e-beam and dry etching techniques. Although the effectiveness of the nanofabrication step was partially mitigated by the enhanced roughness of the microelectrode surface, electrochemical measurement demonstrates a positive impact of the nanopatterning of the microelectrode impedance. Our results suggest that nanostructuration is a promising approach for the impedance modulation of small dimension electrodes.
Source: Micro and Nano Engineering
Authors: Fabrice Iacovella, Scott Greenhorn, Gwenaelle Pound-Lana, Lucas Labbe, Sébastien Labau, Camille Petit-Etienne, Anne Quesnel-Hellmann, Fabien Mehr, Andrei Uvarov, Marcin Zielinski, Lionel Rousseau, Franck Bassani, Mohammed Irar, Clément Hébert, Blaise Yvert, Konstantinos Zekentes, Edwige Bano, Cécile Gourgon, Jumana Boussey
Institutions: Institut polytechnique de Grenoble, Centre National de la Recherche Scientifique, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, CEA Grenoble, Laboratoire des Technologies de la Microélectronique, Centre de Radiofréquences, Optique et Micro-nanoélectronique des Alpes, Inserm, Grenoble Institute of Neurosciences, NOVASiC (France), Université Gustave Eiffel, Laboratoire d'électronique, systèmes de communication et microsystèmes, Centre Interuniversitaire de MicroElectronique et Nanotechnologies, Université Grenoble Alpes, Foundation for Research and Technology Hellas
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,780
Funder: Agence Nationale de la Recherche
OpenAlex ID: W7203487192
