Design and fabrication of nanostructured electrodes based on PEDOT for biological applications

Brain-computer interfaces (BCIs) represent frontier technologies in neuroscience, enabling direct communication between the brain and external devices. Despite significant advancements, developing biocompatible and reliable interfaces remains challenging. To address this issue, we developed stable and high-performance neural interfaces based on poly(3,4-ethylenedioxythiophene) (PEDOT) coatings on titanium nitride (TiN) microelectrodes for electrophysiological signal recording. The TiN microelectrodes were fabricated via a physical vapor deposition (PVD) technique, followed by laser scribing and photolithography. PEDOT coating interfaces were synthesized on TiN surfaces through various electrochemical deposition methods. Different dopants were utilized to improve the physical, mechanical, and electrochemical properties of the coatings. The findings indicate that by precisely controlling deposition parameters, it is possible to achieve various morphologies, from highly smooth and uniform surfaces to hierarchical brain-like microstructures. Cross-sectional field-emission scanning electron microscopy (FESEM) and energy-dispersive X-ray spectroscopy (EDAX) mapping analyses revealed that the formed PEDOT coatings possess thicknesses of 10–20 µm, with a uniform distribution of PEDOT characteristic elements across the coating layer. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) analysis and X-ray photoelectron spectroscopy (XPS) confirmed the successful preparation of pure and composite PEDOT layers. In contrast to conventional PEDOT materials, wettability tests showed that our surfaces exhibit superhydrophilic properties with a contact angle of ~7°, which can improve tissue-electrode interaction, thereby enhancing signal recording quality. Electrochemical analyses demonstrated over a 90% reduction in impedance for the coated samples compared to commercial gold electrodes. These results contribute to advancing materials for BCIs and improving neural signal recording processes.