The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
On the Switching Parameter Variation of Metal-Oxide RRAM—Part I: Physical Modeling and Simulation Methodology
Abstract
The variation of switching parameters is one of the major challenges to both the scaling and volume production of metal-oxide-based resistive random-access memories (RRAMs). In this two-part paper, the source of such parameter variation is analyzed by a physics-based simulator, which is equipped with the capability to simulate a large number ( ~1000) of cyclic SET-RESET operations. By comparing the simulation results with experimental data, it is found that the random current fluctuation experimentally observed in the RESET processes is caused by the competition between trap generation and recombination, whereas the variation of the high resistance states and the tail bits are directly correlated to the randomness of the trap dynamics. A combined strategy with a bilayer dielectric material and a write-verification technique is proposed to minimize the resistance variation. We describe the simulation methodology and discuss the dc results in Part I. The corroboration of the model and the device optimization strategy will be discussed in Part II.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The intrinsic variability of switching behavior in memristors has been a major obstacle to their adoption as the next generation of universal memory.”
From A novel true random number generator based on a stochastic diffusive memristor (2017) · cites this paper as [25]
In the citing paper
“On the other hand, this natural stochasticity can be valuable for hardware security applications.”
From A novel true random number generator based on a stochastic diffusive memristor (2017) · cites this paper as [27]
Citations
Cites
A note on two problems in connexion with graphs
Dijkstra, E. (1959) · Numerische Mathematik · doi:10.1007/bf01386390 · Cited by 24,351
Electronic Processes in Non-Crystalline Materials
Mott, N. F., Davis, E. A., & Lösche, A. (1972) · De Gruyter eBooks · doi:10.1515/9783112653326-018 · Cited by 9,331
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
Electronic processes in non-crystalline materials
Jonscher, A. K. (1972) · Thin Solid Films · doi:10.1016/0040-6090(72)90068-5 · Cited by 4,021
Electronic Processes in Ionic Crystals
Mott, N. F., & Gurney, R. W. (1940) · CERN Document Server (European Organization for Nuclear Research) · Cited by 2,466
Lee, M.-J., Lee, C. B., Lee, D., Lee, S. R., Chang, M., Hur, J. H., Kim, Y.-B., Kim, C.-J., Seo, D. H., Seo, S., et al. (2011) · Nature Materials · doi:10.1038/nmat3070 · Cited by 2,228
Atomic structure of conducting nanofilaments in TiO2 resistive switching memory
Kwon, D.-H., Kim, K. M., Jang, J. H., Jeon, J. M., Lee, M. H., Kim, G. H., Li, X.-S., Park, G.-S., Lee, B., Han, S., et al. (2010) · Nature Nanotechnology · doi:10.1038/nnano.2009.456 · Cited by 2,092
Electronic Processes in Ionic Crystals
Fröhlich, H. (1949) · Nature · doi:10.1038/164377a0 · Cited by 1,310
Resistive Random Access Memory (ReRAM) Based on Metal Oxides
Akinaga, H., & Shima, H. (2010) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2070830 · Cited by 1,037
Yu, S., Wu, Y., Jeyasingh, R., Kuzum, D., & Wong, H.-S. P. (2011) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2011.2147791 · Cited by 805
Self-citation
Cited by
Sorted by citations
Resistive switching memories based on metal oxides: mechanisms, reliability and scaling
Ielmini, D. (2016) · Semiconductor Science and Technology · doi:10.1088/0268-1242/31/6/063002 · Cited by 912
“Increasing the compliance current results in more defects being generated in the insulating layer, thus causing the presence of more parallel CFs [84].”
BackgroundMethodInfluentialA comprehensive review on emerging artificial neuromorphic devices
Zhu, J., Zhang, T., Yang, Y., & Huang, R. (2020) · Applied Physics Reviews · doi:10.1063/1.5118217 · Cited by 783
Yu, S., Gao, B., Fang, Z., Yu, H. Y., Kang, J., & Wong, H. ‐. P. (2013) · Advanced Materials · doi:10.1002/adma.201203680 · Cited by 526
Self-citationA novel true random number generator based on a stochastic diffusive memristor
Jiang, H., Belkin, D., Savel’ev, S. E., Lin, S., Wang, Z., Li, Y., Joshi, S., Midya, R., Li, C., Rao, M., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00869-x · Cited by 459
Brain-inspired computing with memristors: Challenges in devices, circuits, and systems
Zhang, Y., Wang, Z., Zhu, J., Yang, Y., Rao, M., Song, W., Zhuo, Y., Zhang, X., Cui, M., Shen, L., et al. (2020) · Applied Physics Reviews · doi:10.1063/1.5124027 · Cited by 389
Metadata
- Authors
- Guan, X., Yu, S., & Wong, H.-S. P.
- Affiliations
- Stanford SystemX Alliance (US)
- Venue
- IEEE Transactions on Electron Devices
- Published
- 2012-04
- Volume
- 59
- Issue
- 4
- Pages
- 1172-1182
- ISSN
- 0018-9383 (ISSN-L)
- 1557-9646
- OpenAlex
- W2067242107
- Cited by
- 355
- References
- 43
- Citations by year
- 2026: 8 · 2025: 16 · 2024: 19 · 2023: 21 · 2022: 18 · 2021: 18 · 2020: 29 · 2019: 23 · 2018: 26 · 2017: 35 · 2016: 39 · 2015: 35 · 2014: 32 · 2013: 23 · 2012: 13
- FWCI
- 21.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Electron Devices (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Ferroelectric and Negative Capacitance Devices
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Semiconductor materials and devices
- Keywords
- resistive random access memory, current fluctuations, reset operation, high resistance state, bilayer dielectric, physics-based device modeling
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
