The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Resistive Switching Memory Based on Bioinspired Natural Solid Polymer Electrolytes
Abstract
A solution-processed, chitosan-based resistive-switching memory device is demonstrated with Pt/Ag-doped chitosan/Ag structure. The memory device shows reproducible and reliable bipolar resistive switching characteristics. A memory device based on natural organic material is a promising device toward the next generation of nonvolatile nanoelectronics. The memory device based on chitosan as a natural solid polymer electrolyte can be switched reproducibly between high and low resistance states. In addition, the data retention measurement confirmed the reliability of the chitosan-based nonvolatile memory device. The transparent Ag-embedded chitosan film showed an acceptable and comparable resistive switching behavior on the flexible plastic substrate as well. A cost-effective, environmentally benign memory device using chitosan satisfies the functional requirements of nonvolatile memory operations.
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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
Nanoionics-based resistive switching memories
Waser, R., & Aono, M. (2007) · Nature Materials · doi:10.1038/nmat2023 · Cited by 4,923
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
Electrochemical metallization memories—fundamentals, applications, prospects
Valov, I., Waser, R., Jameson, J. R., & Kozicki, M. N. (2011) · Nanotechnology · doi:10.1088/0957-4484/22/25/254003 · Cited by 921
Nanobatteries in redox-based resistive switches require extension of memristor theory
Valov, I., Linn, E., Tappertzhofen, S., Schmelzer, S., van den Hurk, J., Lentz, F., & Waser, R. (2013) · Nature Communications · doi:10.1038/ncomms2784 · Cited by 587
Programmable Resistance Switching in Nanoscale Two-Terminal Devices
Jo, S. H., Kim, K.-H., & Lu, W. (2009) · Nano Letters · doi:10.1021/nl803669s · Cited by 302
Ji, Y., Zeigler, D. F., Lee, D. S., Choi, H., Jen, A. K.-Y., Ko, H. C., & Kim, T.-W. (2013) · Nature Communications · doi:10.1038/ncomms3707 · Cited by 177
Electrochemical metallization cells—blending nanoionics into nanoelectronics?
Lu, W., Jeong, D. S., Kozicki, M., & Waser, R. (2012) · MRS Bulletin · doi:10.1557/mrs.2012.5 · Cited by 113
Schindler, C., Valov, I., & Waser, R. (2009) · Physical Chemistry Chemical Physics · doi:10.1039/b901026b · Cited by 51
Cited by
Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics
Park, H., Lee, Y., Kim, N., Seo, D., Go, G., & Lee, T. (2020) · Advanced Materials · doi:10.1002/adma.201903558 · Cited by 533
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
2D MoS2 Neuromorphic Devices for Brain‐Like Computational Systems
Jiang, J., Guo, J., Wan, X., Yang, Y., Xie, H., Niu, D., Yang, J., He, J., Gao, Y., & Wan, Q. (2017) · Small · doi:10.1002/smll.201700933 · Cited by 328
Biocompatible and Flexible Chitosan‐Based Resistive Switching Memory with Magnesium Electrodes
Hosseini, N. R., & Lee, J. (2015) · Advanced Functional Materials · doi:10.1002/adfm.201502592 · Cited by 307
Self-citationShort-Term Plasticity and Long-Term Potentiation in Artificial Biosynapses with Diffusive Dynamics
Kim, M.-K., & Lee, J.-S. (2018) · ACS Nano · doi:10.1021/acsnano.7b08331 · Cited by 294
Self-citation
Metadata
- Authors
- Raeis Hosseini, N., & Lee, J.-S.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-12-16
- Volume
- 9
- Issue
- 1
- Pages
- 419-426
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2315901794
- Cited by
- 207
- References
- 9
- FWCI
- 7.61
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
