Neuromorphic Nanoionics for Human-Machine Interaction : From Materials to Applications

© 2024 Wiley-VCH GmbH.

Bibliographische Detailangaben
Veröffentlicht in:Advanced materials (Deerfield Beach, Fla.). - 1998. - (2024) vom: 29. Feb., Seite e2311472
1. Verfasser: Liu, Xuerong (VerfasserIn)
Weitere Verfasser: Sun, Cui, Ye, Xiaoyu, Zhu, Xiaojian, Hu, Cong, Tan, Hongwei, He, Shang, Shao, Mengjie, Li, Run-Wei
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:Advanced materials (Deerfield Beach, Fla.)
Schlagworte:Journal Article Review human-machine interaction ion-gated transistor nanoionic memristor neuromorphic nanoionics synapse and neuron
Beschreibung
Zusammenfassung:© 2024 Wiley-VCH GmbH.
Human-machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing. This paper delivers a comprehensive review of recent developments in nanoionic device-based neuromorphic computing technologies and their pivotal role in shaping the next-generation of HMI. Through a detailed examination of fundamental mechanisms and behaviors, the paper explores the ability of nanoionic memristors and ion-gated transistors to emulate the intricate functions of neurons and synapses. Crucial performance metrics, such as reliability, energy efficiency, flexibility, and biocompatibility, are rigorously evaluated. Potential applications, challenges, and opportunities of using the neuromorphic computing technologies in emerging HMI technologies, are discussed and outlooked, shedding light on the fusion of humans with machines
Beschreibung:Date Revised 11.03.2024
published: Print-Electronic
Citation Status Publisher
ISSN:1521-4095
DOI:10.1002/adma.202311472