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Recent Advances on Neuromorphic Devices Based on Chalcogenide Phase‐Change Materials
Author(s) -
Xu Ming,
Mai Xianliang,
Lin Jun,
Zhang Wei,
Li Yi,
He Yuhui,
Tong Hao,
Hou Xiang,
Zhou Peng,
Miao Xiangshui
Publication year - 2020
Publication title -
advanced functional materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.069
H-Index - 322
eISSN - 1616-3028
pISSN - 1616-301X
DOI - 10.1002/adfm.202003419
Subject(s) - neuromorphic engineering , von neumann architecture , chalcogenide , materials science , computer science , computer architecture , computer data storage , phase change memory , nanotechnology , key (lock) , computation , big data , artificial neural network , artificial intelligence , optoelectronics , computer hardware , computer security , layer (electronics) , algorithm , operating system
Traditional von Neumann computing architecture with separated computation and storage units has already impeded the data processing performance and energy efficiency, calling for emerging neuromorphic electronic and optical devices and systems which can mimic the human brain to shift this paradigm. Material‐level innovation has become the key component to this revolution of information technology. Chalcogenide phase‐change material (PCM) as a well‐acknowledged data‐storage medium is a promising candidate to tackle this challenge. In this review, the use of PCMs to implement artificial neurons and synapses from both the electronic and optical respects is discussed, and in particular, the structure–property physics and transition dynamics that enable such brain‐inspired and in‐memory computing applications are emphasized. Recent advances on the atomic‐level amorphous and crystalline structures, transition mechanisms, materials optimization and design, neural and synaptic devices, brain‐inspired chips, and computing systems, as well as the future opportunities of PCMs, are summarized and discussed.