Abstract
Resistive random access memory (ReRAM), a new emerging nonvolatile memory technology based on changes in electrical resistivity of a dielectric film, offers promising advantages such as scalability, fast switching, and low operation voltage. However, for ReRAM to become a successful technology, it is necessary to accurately control the stochastic nature of the conductive nanoscale filaments (CNFs) that governs the resistive switching (RS) behavior of the device and limits its long-term stability and reliability. In this paper, we developed a highly scalable nanostructured/textured electrode that is composed of an array of Al nanotips based on an anodic aluminum oxide template. The nanotips improve the RS characteristics by intensifying the electric field at the apex of each nanotip which is demonstrated using numerical simulations. The localized electric field induces the repetitive nucleation/formation/rupture of the CNFs in a more controlled fashion compared to a flat Al electrode. As a result, the nanotip sample exhibits uniform and reduced forming/reset voltages as low as 4.70 ± 0.98 V/1.00 ± 0.19 V, stable endurance, and long-term retention. As a result, we were able to achieve ultralow-power and error-free operation of 100 cells covering a large area, significantly demonstrating improved uniformity and reliability compared to devices made using flat Al electrodes. This universal bottom-up strategy of self-organized nanostructured-electrodes provides a pathway toward large-scale, highly reliable, and RS memory devices.
Original language | English (US) |
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Pages (from-to) | 938-943 |
Number of pages | 6 |
Journal | IEEE Transactions on Electron Devices |
Volume | 66 |
Issue number | 2 |
DOIs | |
State | Published - Jan 1 2019 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: The authors would like to thank Y.-L. Wang, Academia Sinica, Taipei, Taiwan, for the device structure fabrication and E. S. Mungan, Purdue University, West Lafayette, IN, USA, for her feedback on device performance.