Artificial Neuronal Devices Based on Emerging Materials: Neuronal Dynamics and Applications
Abstract
Artificial neuronal devices are critical building blocks of neuromorphic computing systems and currently the subject of intense research motivated by application needs from new computing technology and more realistic brain emulation. Researchers have proposed a range of device concepts that can mimic neuronal dynamics and functions. Although the switching physics and device structures of these artificial neurons are largely different, their behaviors can be described by several neuron models in a more unified manner. In this paper, the reports of artificial neuronal devices based on emerging volatile switching materials are reviewed from the perspective of the demonstrated neuron models, with a focus on the neuronal functions implemented in these devices and the exploitation of these functions for computational and sensing applications. Furthermore, the neuroscience inspirations and engineering methods to enrich the neuronal dynamics that remain to be implemented in artificial neuronal devices and networks toward realizing the full functionalities of biological neurons are discussed.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 09, 2023
- Source ID
- 10.1002/adma.202205047
Entities
People
- Han Wang
- Hefei Liu
- Hung‐yu Chen
- Jiahui Ma
- Jiangbin Wu
- Jingyi Zou
- Nan Wang
- Sen Lin
- Xu Zhang
- Yuan Qin
- Yuhao Zhang
- Zhonghao Du
Organizations
- Carnegie Mellon University
- National Natural Science Foundation of China
- Natural Science Foundation of Chongqing
- University of Southern California
- Virginia Tech