The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
A Physics-Based Compact Model of Metal-Oxide-Based RRAM DC and AC Operations
Abstract
A physics-based compact model of metal-oxide-based resistive-switching random access memory (RRAM) cell under dc and ac operation modes is presented. In this model, the conductive filament evolution corresponding to the resistive switching process is modeled by considering the transport behaviors of oxygen vacancies and oxygen ions together with the temperature effect. Both the metallic-like and electron hopping conduction transports are considered to model the conduction of RRAM. The model can reproduce both the typical I-V characteristics of RRAM in high-/low-resistance state (LRS) and the nonlinear characteristics in LRS. Moreover, to accurately model ac operation mode, the effects of parasitic capacitance and resistance are included in our model. The developed compact model is verified and calibrated by measured data in different HfOx-based RRAM devices under dc and ac operation modes. The excellent agreement between the model predictions and experimental results shows a promising prospect of the future implementation of this compact model in large-scale circuit simulation to optimize the design of RRAM.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Nanoionics-based resistive switching memories
Waser, R., & Aono, M. (2007) · Nature Materials · doi:10.1038/nmat2023 · Cited by 4,923
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
Guan, X., Yu, S., & Wong, H.-S. P. (2012) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2012.2184545 · Cited by 355 · cited 3×
“The generation probability (Pg) of Vo under electric field during dt is governed by the following equation [12]:”
BackgroundYu, S., Gao, B., Fang, Z., Yu, H., Kang, J., & Wong, H.-S. P. (2012) · 2012 International Electron Devices Meeting · doi:10.1109/iedm.2012.6479018 · Cited by 213
Self-citationDevice and SPICE modeling of RRAM devices
Sheridan, P., Kim, K.-H., Gaba, S., Chang, T., Chen, L., & Lu, W. (2011) · Nanoscale · doi:10.1039/c1nr10557d · Cited by 98
Cited by
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
Self-citationThe fabrication and MOSFET-only circuit implementation of semiconductor memristor
Babacan, Y., Yesil, A., & Gul, F. (2018) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2018.2808530 · Cited by 98
A Compact Model of Analog RRAM With Device and Array Nonideal Effects for Neuromorphic Systems
Liao, Y., Gao, B., Xu, F., Yao, P., Chen, J., Zhang, W., Tang, J., Wu, H., & Qian, H. (2020) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2020.2975314 · Cited by 53
Self-citation
Metadata
- Authors
- Huang, P., Liu, X. Y., Chen, B., Li, H. T., Wang, Y. J., Deng, Y. X., Wei, K. L., Zeng, L., Gao, B., Du, G., Zhang, X., & Kang, J. F.
- Venue
- IEEE Transactions on Electron Devices
- Published
- 2013-12
- Volume
- 60
- Issue
- 12
- Pages
- 4090-4097
- ISSN
- 0018-9383 (ISSN-L)
- 1557-9646
- OpenAlex
- W1979260777
- Cited by
- 206
- References
- 5
- FWCI
- 8.99
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Physics-Based Compact Model of Metal-Oxide-Based RRAM DC and AC Operations. https://app.cochat.ai/papers/10.1109/ted.2013.2287755
- The paper
- Huang, P., Liu, X. Y., Chen, B., Li, H. T., Wang, Y. J., Deng, Y. X., Wei, K. L., Zeng, L., Gao, B., Du, G., Zhang, X., & Kang, J. F. (2013). A Physics-Based Compact Model of Metal-Oxide-Based RRAM DC and AC Operations. IEEE Transactions on Electron Devices. https://doi.org/10.1109/ted.2013.2287755
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.