Scalable Fabrication of 3D-Protruded Neural Microelectrodes Using Flexible PCB Technology for High-Fidelity Neural Interfaces
Flexible neural electrodes hold great promise for monitoring electrophysiological activity in the brain, but achieving both fabrication scalability and high signal fidelity remains a significant challenge. Conventional high-performance neural interfaces typically require complex and costly microfabrication processes, while simpler approaches often fail to optimize the electrode–tissue interface. Here, we introduce a scalable, cost-effective platform for fabricating high-performance three-dimensional (3D) neural electrodes using an industrial flexible printed circuit board (fPCB) process. We systematically compare two electrode architectures: (i) recessed microelectrodes with gold (Au) electroless plating, serving as a benchmark, and (ii) 3D protruded microelectrodes formed by tin (Sn) electroplating. To isolate the role of geometry, both electrode types were further functionalized with high-surface-area platinum black (Pt black) and poly(3,4-ethylenedioxythiophene) (PEDOT) coatings. Electrochemical analysis revealed that the Sn-protruded electrodes exhibited lower impedance at 1 kHz and a higher charge storage capacity (CSC) than Au-recessed electrodes. In vivo recordings from the mouse hippocampus further demonstrated that Sn-protruded electrodes achieved a significantly higher signal-to-noise ratio (SNR) and stronger spike amplitudes compared to both bare and coated Au-recessed electrodes. These findings establish 3D protruded electrode geometry as a key determinant of recording fidelity, primarily by reducing the electrode–neuron distance. More broadly, our results demonstrate that the fPCB-based approach provides a rapid, accessible, and scalable route to high-performance neural interfaces, highlighting its potential for widespread adoption in neural engineering.
Authors
- Hyogeun Shin (ORCID: https://orcid.org/0000-0002-3784-2717)
- Namsun Chou (ORCID: https://orcid.org/0000-0002-0929-2690)
- Joon‐Hyung Lee (ORCID: https://orcid.org/0000-0001-5597-4521)
- Minseok Kim (ORCID: https://orcid.org/0009-0002-4878-0926)
- Seungjun Lee (ORCID: https://orcid.org/0000-0003-3693-7615)
- Sehwan Park (ORCID: https://orcid.org/0000-0002-5905-6450)
- Giheon Kim
- Haeyun Lee
Institutions
- Daegu Gyeongbuk Institute of Science and Technology (KR)
- Kyungpook National University (KR)
- Korea Institute of Brain Science (KR)
- Korea Brain Research Institute (KR)
Publication Details
- Journal
- ACS Applied Electronic Materials
- Published
- 2025-11-11
- DOI
- https://doi.org/10.1021/acsaelm.5c02055
- Citations
- 2
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 1.82