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Exploring Phase‐Change Memory: From Material Systems to Device Physics
Author(s) -
Ren Yanyun,
Sun Ruoyao,
Chen Stephenie Hiu Yuet,
Du Chunyu,
Han Su-Ting,
Zhou Ye
Publication year - 2021
Publication title -
physica status solidi (rrl) – rapid research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.786
H-Index - 68
eISSN - 1862-6270
pISSN - 1862-6254
DOI - 10.1002/pssr.202000394
Subject(s) - neuromorphic engineering , computer science , bandwidth (computing) , phase change memory , computer data storage , energy consumption , non volatile memory , electronic engineering , 3d optical data storage , efficient energy use , phase change , computer architecture , computer hardware , electrical engineering , artificial neural network , engineering , telecommunications , artificial intelligence , engineering physics , operating system
To deal with the growing demand for data storage and processing, phase‐change memory (PCM) provides one of the most promising candidates for next‐generation nonvolatile data storage and neuromorphic computing applications. A lot of effort has been made toward optimizing the materials and device design; thus, excellent device performances have been achieved including high density, fast switching speed, great endurance, and retention. In addition, the widely tunable optical characteristics of PCMs are irresistibly attractive for optoelectronic or all‐optical applications with unprecedented bandwidth, low energy consumption, and multilevel data storage. Herein, the materials system and switching mechanisms on experimental and modeling methods for PCM designs and applications are discussed. Electric‐domain and optical‐domain PCM‐based artificial synapses/neurons and their applications in neuromorphic computing are also reviewed. Finally, the future prospects and challenges of PCM‐based applications on materials, devices, algorithms, and system levels are highlighted.