Citation: Xu Ke, Wang Jinfen. 1D and 2D Nanomaterials-based Electronics for Neural Interfaces[J]. Acta Physico-Chimica Sinica, ;2020, 36(12): 200305. doi: 10.3866/PKU.WHXB202003050 shu

1D and 2D Nanomaterials-based Electronics for Neural Interfaces

Xu Ke ^1,2,3 ,
Wang Jinfen ^1,2,,

1.
CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, P. R. China
2.
CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, National Center for Nanoscience and Technology, Beijing 100190, P. R. China
3.
University of Chinese Academy of Sciences, Beijing 100049, P. R. China

Corresponding author: Wang Jinfen, wangjinfen@nanoctr.cn
Received Date: 21 March 2020
Revised Date: 22 April 2020
Accepted Date: 23 April 2020
Available Online: 29 April 2020
Fund Project: Strategic Priority Research Program of Chinese Academy of Sciences XDB32030100The project was supported by the National Natural Science Foundation of China (21790393, 61971150) and Strategic Priority Research Program of Chinese Academy of Sciences (XDB32030100)the National Natural Science Foundation of China 61971150the National Natural Science Foundation of China 21790393

Neural interfaces have contributed significantly to our understanding of brain functions as well as the development of neural prosthetics. An ideal neural interface should create a seamless and reliable link between the nervous system and external electronics for long periods of time. Implantable electronics that are capable of recording and stimulating neuronal activities have been widely applied for the study of neural circuits or the treatment of neurodegenerative diseases. However, the relatively large cross-sectional footprints of conventional electronics can cause acute tissue damage during implantation. In addition, the mechanical mismatch between conventional rigid electronics and soft brain tissue has been shown to induce chronic tissue inflammatory responses, leading to signal degradation during long-term studies. Thus, it is essential to develop new strategies to overcome these existing challenges and construct more stable neural interfaces. Owing to their unique physical and chemical properties, one-dimensional (1D) and two-dimensional (2D) nanomaterials constitute promising candidates for next-generation neural interfaces. In particular, novel electronics based on 1D and 2D nanomaterials, including carbon nanotubes (CNTs), silicon nanowires (SiNWs), and graphene (GR), have been demonstrated for neural interfaces with improved performance. This review discusses recent developments in neural interfaces enabled by 1D and 2D nanomaterials and their electronics. The ability of CNTs to promote neuronal growth and electrical activity has been proven, demonstrating the feasibility of using CNTs as conducting layers or as modifying layers for electronics. Owing to their good mechanical, electrical and biological properties, CNTs-based electronics have been demonstrated for neural recording and stimulation, neurotransmitter detection, and controlled drug release. Different from CNTs-based electronics, SiNWs-based field effect transistors (FETs) and microelectrode arrays have been successfully demonstrated for intracellular recording of action potentials through penetration into neural cells. Significantly, SiNWs FETs can detect neural activity at the level of individual axons and dendrites with a high signal-to-noise ratio. Their ability to record multiplexed intracellular signals renders SiNWs-based electronics superior to traditional intracellular recording techniques such as patch-clamp recording. Besides, SiNWs have been explored for optically controlled nongenetic neuromodulation due to their tunable electrical and optical properties. As the star of the 2D nanomaterials family, GR has been applied as biomimetic substrates for neural regeneration. Transparent GR-based electronics combining electrophysiological measurements, optogenetics, two-photon microscopy with multicellular calcium imaging have been applied for the construction of multimodal neural interfaces. Finally, we provide an overview of the challenges and future perspectives of nanomaterial-based neural interfaces.
- Carbon nanotube,
- Silicon nanowire,
- Graphene,
- Neural interface,
- Electrophysiology
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