Metal Oxide Resistive Memory using Graphene Edge Electrode

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 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 architecture using experimentally measured device properties show higher storage potential for graphene devices compared that of metal based devices.

41 pages, 15 figures

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Cited by in corpus (5)

• Memristor Crossbars with 4.5 Terabits-per-Inch-Square Density and Two Nanometer Dimension
• Two-dimensional layered materials for memristive and neuromorphic applications
• A memristive deep belief neural network based on silicon synapses
• Nanoscale Phase Change Memory with Graphene Ribbon Electrodes
• Minimizing the programming power of phase change memory by using graphene nanoribbon edge-contact