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Self-selective van der Waals heterostructures for large scale memory array
The large-scale crossbar array is a promising architecture for hardware-amenable energy efficient three-dimensional memory and neuromorphic computing systems. While accessing a memory cell with negligible sneak currents remains a fundamental issue in the crossbar array architecture, up-to-date memor...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6639341/ https://www.ncbi.nlm.nih.gov/pubmed/31320651 http://dx.doi.org/10.1038/s41467-019-11187-9 |
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author | Sun, Linfeng Zhang, Yishu Han, Gyeongtak Hwang, Geunwoo Jiang, Jinbao Joo, Bomin Watanabe, Kenji Taniguchi, Takashi Kim, Young-Min Yu, Woo Jong Kong, Bai-Sun Zhao, Rong Yang, Heejun |
author_facet | Sun, Linfeng Zhang, Yishu Han, Gyeongtak Hwang, Geunwoo Jiang, Jinbao Joo, Bomin Watanabe, Kenji Taniguchi, Takashi Kim, Young-Min Yu, Woo Jong Kong, Bai-Sun Zhao, Rong Yang, Heejun |
author_sort | Sun, Linfeng |
collection | PubMed |
description | The large-scale crossbar array is a promising architecture for hardware-amenable energy efficient three-dimensional memory and neuromorphic computing systems. While accessing a memory cell with negligible sneak currents remains a fundamental issue in the crossbar array architecture, up-to-date memory cells for large-scale crossbar arrays suffer from process and device integration (one selector one resistor) or destructive read operation (complementary resistive switching). Here, we introduce a self-selective memory cell based on hexagonal boron nitride and graphene in a vertical heterostructure. Combining non-volatile and volatile memory operations in the two hexagonal boron nitride layers, we demonstrate a self-selectivity of 10(10) with an on/off resistance ratio larger than 10(3). The graphene layer efficiently blocks the diffusion of volatile silver filaments to integrate the volatile and non-volatile kinetics in a novel way. Our self-selective memory minimizes sneak currents on large-scale memory operation, thereby achieving a practical readout margin for terabit-scale and energy-efficient memory integration. |
format | Online Article Text |
id | pubmed-6639341 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66393412019-07-22 Self-selective van der Waals heterostructures for large scale memory array Sun, Linfeng Zhang, Yishu Han, Gyeongtak Hwang, Geunwoo Jiang, Jinbao Joo, Bomin Watanabe, Kenji Taniguchi, Takashi Kim, Young-Min Yu, Woo Jong Kong, Bai-Sun Zhao, Rong Yang, Heejun Nat Commun Article The large-scale crossbar array is a promising architecture for hardware-amenable energy efficient three-dimensional memory and neuromorphic computing systems. While accessing a memory cell with negligible sneak currents remains a fundamental issue in the crossbar array architecture, up-to-date memory cells for large-scale crossbar arrays suffer from process and device integration (one selector one resistor) or destructive read operation (complementary resistive switching). Here, we introduce a self-selective memory cell based on hexagonal boron nitride and graphene in a vertical heterostructure. Combining non-volatile and volatile memory operations in the two hexagonal boron nitride layers, we demonstrate a self-selectivity of 10(10) with an on/off resistance ratio larger than 10(3). The graphene layer efficiently blocks the diffusion of volatile silver filaments to integrate the volatile and non-volatile kinetics in a novel way. Our self-selective memory minimizes sneak currents on large-scale memory operation, thereby achieving a practical readout margin for terabit-scale and energy-efficient memory integration. Nature Publishing Group UK 2019-07-18 /pmc/articles/PMC6639341/ /pubmed/31320651 http://dx.doi.org/10.1038/s41467-019-11187-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Sun, Linfeng Zhang, Yishu Han, Gyeongtak Hwang, Geunwoo Jiang, Jinbao Joo, Bomin Watanabe, Kenji Taniguchi, Takashi Kim, Young-Min Yu, Woo Jong Kong, Bai-Sun Zhao, Rong Yang, Heejun Self-selective van der Waals heterostructures for large scale memory array |
title | Self-selective van der Waals heterostructures for large scale memory array |
title_full | Self-selective van der Waals heterostructures for large scale memory array |
title_fullStr | Self-selective van der Waals heterostructures for large scale memory array |
title_full_unstemmed | Self-selective van der Waals heterostructures for large scale memory array |
title_short | Self-selective van der Waals heterostructures for large scale memory array |
title_sort | self-selective van der waals heterostructures for large scale memory array |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6639341/ https://www.ncbi.nlm.nih.gov/pubmed/31320651 http://dx.doi.org/10.1038/s41467-019-11187-9 |
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