Implantable Multilayer Carbon-Structured Neural Nanoprobe for In Vivo Intracellular Electrophysiological and Chemical Signal Acquisition
Neural probes targeting single neurons are instrumental in overcoming the ambiguity associated with population-averaged signals and the attenuation of extracellular signals to reveal the fundamental units of neural coding. However, current neural probes are limited by resolution, structural design, and micro/nanotechnology, making it challenging to penetrate single neurons <i>in vivo</i> to directly record various neural signals. Here, we report a multilayer carbon-structured nanoprobe (MLCNP) for intracellular electrophysiological and chemical recordings <i>in vivo</i>. The sensing layers, composed of graphene and feather-shaped carbon nanowires (FCNW), and the protective layer of nanodiamond are prepared <i>via</i> microwave plasma chemical vapor deposition. The controlled exposure of nanotips, roughening of FCNW sensing layers, and adsorption of Pt nanoparticles on their surface are achieved through microplasma jet branch etching (MPJBE). The multilayer carbon structures and the MPJBE treatment significantly enhance the cathodic charge, peak cathodic current and sensitivity to dissolved O<sub>2</sub> of nanoprobes. The MLCNP with a tip diameter of approximately 70 nm and an exposed sensing area length of about 900 nm, demonstrates good cytocompatibility, minimal invasive damage, and selective O<sub>2</sub>-sensing capabilities. Finally, intracellular electrophysiological signals and variations in O<sub>2</sub> concentration, along with other potential biochemical signals, are successfully recorded <i>in vivo</i>, and the effects of pain stimulation on electrophysiological spikes were analyzed. The developed nanoprobe based on the new materials and processes and its successful acquisition of electrical and biochemical signals at the single-neuron level <i>in vivo</i>, hold profound significance for a deeper understanding of the intrinsic mechanisms of the nervous system.
Authors
- Mengfei Xu (ORCID: https://orcid.org/0000-0002-7738-3746)
- Kejun Tu (ORCID: https://orcid.org/0000-0002-7200-4743)
- Qingda Xu (ORCID: https://orcid.org/0000-0002-9713-5897)
- LONGCHUN WANG
- XiuYan Li
- Xia Yang (ORCID: https://orcid.org/0000-0002-3971-038X)
- Zhiyuan Du
- Jun Cao (ORCID: https://orcid.org/0000-0002-2790-753X)
- Kunyu Zheng
- Qingkun Liu
- Chunpeng Jiang
- Ning Wei
- Ye Xi
- Xiaolin Wang
- Jingquan Liu
- Quan Peng
- Bin Yang
Institutions
- Shandong University (CN)
- Shanghai Jiao Tong University (CN)
- Fraunhofer Institute for Integrated Circuits (DE)
Publication Details
- Journal
- ACS Sensors
- Published
- 2026-03-13
- DOI
- https://doi.org/10.1021/acssensors.5c04488
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00