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Metal oxide-resistive memory using graphene-edge electrodes

Author

Listed:
  • Seunghyun Lee

    (Stanford University)

  • Joon Sohn

    (Stanford University)

  • Zizhen Jiang

    (Stanford University)

  • Hong-Yu Chen

    (Stanford University
    Present address: Memory Strategy Group, SanDisk Corporation, 951 SanDisk Drive, Milpitas, California 95035, USA.)

  • H.-S. Philip Wong

    (Stanford University)

Abstract

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.

Suggested Citation

  • Seunghyun Lee & Joon Sohn & Zizhen Jiang & Hong-Yu Chen & H.-S. Philip Wong, 2015. "Metal oxide-resistive memory using graphene-edge electrodes," Nature Communications, Nature, vol. 6(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms9407
    DOI: 10.1038/ncomms9407
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    Cited by:

    1. S. S. Teja Nibhanupudi & Anupam Roy & Dmitry Veksler & Matthew Coupin & Kevin C. Matthews & Matthew Disiena & Ansh & Jatin V. Singh & Ioana R. Gearba-Dolocan & Jamie Warner & Jaydeep P. Kulkarni & Gen, 2024. "Ultra-fast switching memristors based on two-dimensional materials," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Maosong Xie & Yueyang Jia & Chen Nie & Zuheng Liu & Alvin Tang & Shiquan Fan & Xiaoyao Liang & Li Jiang & Zhezhi He & Rui Yang, 2023. "Monolithic 3D integration of 2D transistors and vertical RRAMs in 1T–4R structure for high-density memory," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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