A 3D-Printed Neural Probe with Geometry-Defined Lithography-Free Metallization and Parylene Encapsulation
Abstract Two-photon polymerization enables neural probes with complex three-dimensional geometries, but selectively metallizing and insulating these structures remains challenging. We present a geometry-defined fabrication process that combines trench-guided metallization with vapor-deposited Parylene-C encapsulation and lithography-free electrode exposure. Re-entrant trenches guide line-of-sight Ti/Au evaporation to form electrically separated interconnects connected to electrode sites and contact pads. A conformal Parylene-C coating then seals the high-aspect-ratio trenches over the interconnects, and a timed, maskless O₂ plasma etch-back followed by SF₆/O₂ plasma treatment exposes the electrodes and pads while retaining insulation over the recessed interconnects. We fabricated a prototype comprising a 2 mm-long shank with four mushroom-shaped electrodes, each 15 µm in diameter. Scanning electron microscopy showed metal deposition at the trench bottoms, Parylene-C coverage, and selective electrode exposure after plasma processing. Electrochemical impedance spectroscopy in phosphate-buffered saline showed an impedance magnitude of approximately 1 MΩ at 1 kHz before and after insertion into 0.6% agarose gel. The probe reached a 2 mm insertion depth without observed buckling or fracture. These results demonstrate a fabrication proof of concept for 3D-printed neural probes using geometry-defined metallization and selective Parylene encapsulation, providing a potential route toward scalable fabrication of 3D-printed bioelectronic microsystems
Authors
- Armin Sedighi (ORCID: https://orcid.org/0000-0001-8208-8672)
- Mehedi Hasan (ORCID: https://orcid.org/0009-0002-0194-4575)
- Yong Xu (ORCID: https://orcid.org/0000-0003-3601-0246)
Institutions
- Wayne State University (US)
Publication Details
- Journal
- Research Square
- Published
- 2026-11-06
- DOI
- https://doi.org/10.21203/rs.3.rs-11627269/v1
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- preprint
Funders
- National Science Foundation