Self-rectifying resistive memory in passive crossbar arrays

Conventional computing architectures are poor suited to the unique workload demands of deep learning, which has led to a surge in interest in memory-centric computing. Herein, a trilayer (Hf(0.8)Si(0.2)O(2)/Al(2)O(3)/Hf(0.5)Si(0.5)O(2))-based self-rectifying resistive memory cell (SRMC) that exhibit...

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Detalles Bibliográficos
Autores principales: Jeon, Kanghyeok, Kim, Jeeson, Ryu, Jin Joo, Yoo, Seung-Jong, Song, Choongseok, Yang, Min Kyu, Jeong, Doo Seok, Kim, Gun Hwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137934/
https://www.ncbi.nlm.nih.gov/pubmed/34016978
http://dx.doi.org/10.1038/s41467-021-23180-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137934/
https://www.ncbi.nlm.nih.gov/pubmed/34016978
http://dx.doi.org/10.1038/s41467-021-23180-2

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