The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Gate-tunable memristive phenomena mediated by grain boundaries in single-layer MoS2
Open accessAbstract
Continued progress in high-speed computing depends on breakthroughs in both materials synthesis and device architectures. The performance of logic and memory can be enhanced significantly by introducing a memristor, a two-terminal device with internal resistance that depends on the history of the external bias voltage. State-of-the-art memristors, based on metal-insulator-metal (MIM) structures with insulating oxides, such as TiO₂, are limited by a lack of control over the filament formation and external control of the switching voltage. Here, we report a class of memristors based on grain boundaries (GBs) in single-layer MoS₂ devices. Specifically, the resistance of GBs emerging from contacts can be easily and repeatedly modulated, with switching ratios up to ∼10(3) and a dynamic negative differential resistance (NDR). Furthermore, the atomically thin nature of MoS₂ enables tuning of the set voltage by a third gate terminal in a field-effect geometry, which provides new functionality that is not observed in other known memristive devices.
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Cites
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Self-citationGrains and grain boundaries in highly crystalline monolayer molybdenum disulphide
van der Zande, A. M., Huang, P. Y., Chenet, D. A., Berkelbach, T. C., You, Y., Lee, G.-H., Heinz, T. F., Reichman, D. R., Muller, D. A., & Hone, J. C. (2013) · Nature Materials · doi:10.1038/nmat3633 · Cited by 2,197
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Ion Gated Synaptic Transistors Based on 2D van der Waals Crystals with Tunable Diffusive Dynamics
Zhu, J., Yang, Y., Jia, R., Liang, Z., Zhu, W., Rehman, Z. U., Bao, L., Zhang, X., Cai, Y., Song, L., et al. (2018) · Advanced Materials · doi:10.1002/adma.201800195 · Cited by 499
Aging of Transition Metal Dichalcogenide Monolayers
Gao, J., Li, B., Tan, J., Chow, P., Lu, T.-M., & Koratkar, N. (2016) · ACS Nano · doi:10.1021/acsnano.5b07677 · Cited by 490
The 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
He, Z., & Que, W. (2016) · Applied Materials Today · doi:10.1016/j.apmt.2016.02.001 · Cited by 438
Metadata
- Authors
- Sangwan, V. K., Jariwala, D., Kim, I. S., Chen, K.-S., Marks, T. J., Lauhon, L. J., & Hersam, M. C.
- Venue
- Nature Nanotechnology
- Published
- 2015-04-06
- Volume
- 10
- Issue
- 5
- Pages
- 403-406
- ISSN
- 1748-3387 (ISSN-L)
- 1748-3395
- OpenAlex
- W1977042446
- Cited by
- 709
- References
- 33
- FWCI
- 28.55
- Type
- journal article
- Language
- en
- Open access
- green
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