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On the stochastic nature of resistive switching in metal oxide RRAM: Physical modeling, monte carlo simulation, and experimental characterization
Abstract
The origin of switching parameter variations in metal oxide resistive switching random access memory (RRAM) is studied. The stochastic formation/rupture of the conductive filaments (CFs) is modeled and incorporated with a trap-assisted-tunneling (TAT) current solver. The experimental DC I–V characteristics and pulse transient waveform featuring the current fluctuation during the reset process are reproduced by Monte Carlo simulations. It is found that the wide spread of high resistance states (HRS) are due to the variation of tunneling gap distances, and the tail bits of the HRS are due to the newly generated traps near the electrode at the end of the reset process. To solve the over-reset and tail bits problems, a device structure with active/buffer bi-layer oxides combined with the reset-verify technique is proposed. Our model is corroborated by measured experimental data of HfOxbased RRAM.
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Cites
Redox‐Based Resistive Switching Memories – Nanoionic Mechanisms, Prospects, and Challenges
Waser, R., Dittmann, R., Staikov, G., & Szot, K. (2009) · Advanced Materials · doi:10.1002/adma.200900375 · Cited by 5,080
Cited by
Wong, H.-S. P., Lee, H.-Y., Yu, S., Chen, Y.-S., Wu, Y., Chen, P.-S., Lee, B., Chen, F. T., & Tsai, M.-J. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2190369 · Cited by 2,757
Self-citationConduction Mechanism of Valence Change Resistive Switching Memory: A Survey
Lim, E., & Ismail, R. (2015) · Electronics · doi:10.3390/electronics4030586 · Cited by 829
Woo, J., Moon, K., Song, J., Lee, S., Kwak, M., Park, J., & Hwang, H. (2016) · IEEE Electron Device Letters · doi:10.1109/led.2016.2582859 · Cited by 512
Understanding memristive switching via in situ characterization and device modeling
Sun, W., Gao, B., Chi, M., Xia, Q., Yang, J. J., Qian, H., & Wu, H. (2019) · Nature Communications · doi:10.1038/s41467-019-11411-6 · Cited by 482
Immunity to Device Variations in a Spiking Neural Network With Memristive Nanodevices
Querlioz, D., Bichler, O., Dollfus, P., & Gamrat, C. (2013) · IEEE Transactions on Nanotechnology · doi:10.1109/tnano.2013.2250995 · Cited by 420
Metadata
- Authors
- Yu, S., Guan, X., & Wong, H.-S. P.
- Venue
- 2011 International Electron Devices Meeting
- Publisher
- IEEE
- Published
- 2011-12
- Pages
- 17.3.1-17.3.4
- ISSN
- 0163-1918 (ISSN-L)
- OpenAlex
- W1977765713
- Cited by
- 204
- References
- 1
- FWCI
- 15.66
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Yu, S., Guan, X., & Wong, H.-S. P. (2011). On the stochastic nature of resistive switching in metal oxide RRAM: Physical modeling, monte carlo simulation, and experimental characterization. 2011 International Electron Devices Meeting. https://doi.org/10.1109/iedm.2011.6131572
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