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Metal oxide-resistive memory using graphene-edge electrodes
The emerging paradigm of ‘abundant-data' computing requires real-time analytics on enormous quantities of data collected by a mushrooming network of sensors. Todays computing technology, however, cannot scale to satisfy such big data applications with the required throughput and energy efficien...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Pub. Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4598621/ https://www.ncbi.nlm.nih.gov/pubmed/26406356 http://dx.doi.org/10.1038/ncomms9407 |
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author | Lee, Seunghyun Sohn, Joon Jiang, Zizhen Chen, Hong-Yu Philip Wong, H.-S. |
author_facet | Lee, Seunghyun Sohn, Joon Jiang, Zizhen Chen, Hong-Yu Philip Wong, H.-S. |
author_sort | Lee, Seunghyun |
collection | PubMed |
description | The emerging paradigm of ‘abundant-data' computing requires real-time analytics on enormous quantities of data collected by a mushrooming network of sensors. Todays computing technology, however, cannot scale to satisfy such big data applications with the required throughput and energy efficiency. The next technology frontier will be monolithically integrated chips with three-dimensionally interleaved memory and logic for unprecedented data bandwidth with reduced energy consumption. In this work, we exploit the atomically thin nature of the graphene edge to assemble a resistive memory (∼3 Å thick) stacked in a vertical three-dimensional structure. We report some of the lowest power and energy consumption among the emerging non-volatile memories due to an extremely thin electrode with unique properties, low programming voltages, and low current. Circuit analysis of the three-dimensional architecture using experimentally measured device properties show higher storage potential for graphene devices compared that of metal based devices. |
format | Online Article Text |
id | pubmed-4598621 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Pub. Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-45986212015-10-21 Metal oxide-resistive memory using graphene-edge electrodes Lee, Seunghyun Sohn, Joon Jiang, Zizhen Chen, Hong-Yu Philip Wong, H.-S. Nat Commun Article The emerging paradigm of ‘abundant-data' computing requires real-time analytics on enormous quantities of data collected by a mushrooming network of sensors. Todays computing technology, however, cannot scale to satisfy such big data applications with the required throughput and energy efficiency. The next technology frontier will be monolithically integrated chips with three-dimensionally interleaved memory and logic for unprecedented data bandwidth with reduced energy consumption. In this work, we exploit the atomically thin nature of the graphene edge to assemble a resistive memory (∼3 Å thick) stacked in a vertical three-dimensional structure. We report some of the lowest power and energy consumption among the emerging non-volatile memories due to an extremely thin electrode with unique properties, low programming voltages, and low current. Circuit analysis of the three-dimensional architecture using experimentally measured device properties show higher storage potential for graphene devices compared that of metal based devices. Nature Pub. Group 2015-09-25 /pmc/articles/PMC4598621/ /pubmed/26406356 http://dx.doi.org/10.1038/ncomms9407 Text en Copyright © 2015, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Lee, Seunghyun Sohn, Joon Jiang, Zizhen Chen, Hong-Yu Philip Wong, H.-S. Metal oxide-resistive memory using graphene-edge electrodes |
title | Metal oxide-resistive memory using graphene-edge electrodes |
title_full | Metal oxide-resistive memory using graphene-edge electrodes |
title_fullStr | Metal oxide-resistive memory using graphene-edge electrodes |
title_full_unstemmed | Metal oxide-resistive memory using graphene-edge electrodes |
title_short | Metal oxide-resistive memory using graphene-edge electrodes |
title_sort | metal oxide-resistive memory using graphene-edge electrodes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4598621/ https://www.ncbi.nlm.nih.gov/pubmed/26406356 http://dx.doi.org/10.1038/ncomms9407 |
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