The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Robust memristors based on layered two-dimensional materials
Open accessAbstract
Van der Waals heterostructures are formed by stacking layers of different two-dimensional materials and offer the possibility to design new materials with atomic-level precision. By combining the valuable properties of different 2D systems, such heterostructures could potentially be used to address existing challenges in the development of electronic devices, particularly those that require vertical multi-layered structures. Here we show that robust memristors with good thermal stability, which is lacking in traditional memristors, can be created from a van der Waals heterostructure composed of graphene/MoS2–xOx/graphene. The devices exhibit excellent switching performance with an endurance of up to 107 and a high operating temperature of up to 340 °C. With the help of in situ electron microscopy, we show that the thermal stability is due to the MoS2–xOx switching layer, as well as the graphene electrodes and the atomically sharp interface between the electrodes and the switching layer. We also show that the devices have a well-defined conduction channel and a switching mechanism that is based on the migration of oxygen ions. Finally, we demonstrate that the memristor devices can be fabricated on a polyimide substrate and exhibit good endurance against over 1,000 bending cycles, illustrating their potential for flexible electronic applications.Memristors that offer good thermal stability, which is lacking in traditional memristors, can be created from a van der Waals heterostructure composed of graphene/MoS2–xOx/graphene.
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
Graphene: Status and Prospects
Geim, A. K. (2009) · Science · doi:10.1126/science.1158877 · Cited by 13,942
Strukov, D. B., Snider, G. S., Stewart, D. R., & Williams, R. S. (2008) · Nature · doi:10.1038/nature06932 · Cited by 11,828
Memristor—The Missing Circuit Element
Chua, L. (1971) · IEEE Transactions on Circuit Theory · doi:10.1109/tct.1971.1083337 · Cited by 10,268
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
Nanoionics-based resistive switching memories
Waser, R., & Aono, M. (2007) · Nature Materials · doi:10.1038/nmat2023 · Cited by 4,923
Nanoscale Memristor Device as Synapse in Neuromorphic Systems
Jo, S. H., Chang, T., Ebong, I., Bhadviya, B. B., Mazumder, P., & Lu, W. (2010) · Nano Letters · doi:10.1021/nl904092h · Cited by 4,174
Memristive devices for computing
Yang, J. J., Strukov, D. B., & Stewart, D. R. (2013) · Nature Nanotechnology · doi:10.1038/nnano.2012.240 · Cited by 3,885
Self-citationTraining and operation of an integrated neuromorphic network based on metal-oxide memristors
Prezioso, M., Merrikh-Bayat, F., Hoskins, B. D., Adam, G. C., Likharev, K. K., & Strukov, D. B. (2015) · Nature · doi:10.1038/nature14441 · Cited by 3,001
Memristive switching mechanism for metal/oxide/metal nanodevices
Yang, J. J., Pickett, M. D., Li, X., Ohlberg, D. A. A., Stewart, D. R., & Williams, R. S. (2008) · Nature Nanotechnology · doi:10.1038/nnano.2008.160 · Cited by 2,987
Self-citationMemristors with diffusive dynamics as synaptic emulators for neuromorphic computing
Wang, Z., Joshi, S., Savel’ev, S. E., Jiang, H., Midya, R., Lin, P., Hu, M., Ge, N., Strachan, J. P., Li, Z., et al. (2017) · Nature Materials · doi:10.1038/nmat4756 · Cited by 2,358
Self-citation
Cited by
Resistive switching materials for information processing
Wang, Z., Wu, H., Burr, G. W., Hwang, C. S., Wang, K. L., Xia, Q., & Yang, J. J. (2020) · Nature Reviews Materials · doi:10.1038/s41578-019-0159-3 · Cited by 1,214
Self-citationThe Future of Memristors: Materials Engineering and Neural Networks
Sun, K., Chen, J., & Yan, X. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202006773 · Cited by 482
Xu, R., Jang, H., Lee, M.-H., Amanov, D., Cho, Y., Kim, H., Park, S., Shin, H.-J., & Ham, D. (2019) · Nano Letters · doi:10.1021/acs.nanolett.8b05140 · Cited by 452
Gate-tunable van der Waals heterostructure for reconfigurable neural network vision sensor
Wang, C.-Y., Liang, S.-J., Wang, S., Wang, P., Li, Z., Wang, Z., Gao, A., Pan, C., Liu, C., Liu, J., et al. (2020) · Science Advances · doi:10.1126/sciadv.aba6173 · Cited by 452
Self-citationChen, S., Mahmoodi, M. R., Shi, Y., Mahata, C., Yuan, B., Liang, X., Wen, C., Hui, F., Akinwande, D., Strukov, D. B., et al. (2020) · Nature Electronics · doi:10.1038/s41928-020-00473-w · Cited by 448
Metadata
- Authors
- Wang, M., Cai, S., Pan, C., Wang, C., Lian, X., Zhuo, Y., Xu, K., Cao, T., Pan, X., Wang, B., Liang, S.-J., Yang, J. J., Wang, P., & Miao, F.
- Venue
- Nature Electronics
- Published
- 2018-02-05
- Volume
- 1
- Issue
- 2
- Pages
- 130-136
- ISSN
- 2520-1131 (ISSN-L)
- OpenAlex
- W2781720065
- Cited by
- 796
- References
- 16
- FWCI
- 29.92
- Type
- journal article
- Language
- en
- Open access
- green
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: Robust memristors based on layered two-dimensional materials. https://app.cochat.ai/papers/10.1038/s41928-018-0021-4
- The paper
- Wang, M., Cai, S., Pan, C., Wang, C., Lian, X., Zhuo, Y., Xu, K., Cao, T., Pan, X., Wang, B., Liang, S.-J., Yang, J. J., Wang, P., & Miao, F. (2018). Robust memristors based on layered two-dimensional materials. Nature Electronics. https://doi.org/10.1038/s41928-018-0021-4
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.
