Artificial Neuronal Devices Based on Emerging Materials: Neuronal Dynamics and Applications

• Published in: Advanced materials (Weinheim) Vol. 35; no. 37; p. e2205047
• Main Authors: Liu, Hefei, Qin, Yuan, Chen, Hung‐Yu, Wu, Jiangbin, Ma, Jiahui, Du, Zhonghao, Wang, Nan, Zou, Jingyi, Lin, Sen, Zhang, Xu, Zhang, Yuhao, Wang, Han
• Format: Journal Article
• Language: English
• Published: Germany Wiley Subscription Services, Inc 01.09.2023
• Subjects: Materials science; Neurons; Switching; spiking neural networks; sensory neurons; brain emulation; artificial neurons; neuromorphic computing
• ISSN: 0935-9648; 1521-4095; 1521-4095
• DOI: 10.1002/adma.202205047

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.