The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Designing crystallization in phase-change materials for universal memory and neuro-inspired computing
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Citations
Cites
Memristor—The Missing Circuit Element
Chua, L. (1971) · IEEE Transactions on Circuit Theory · doi:10.1109/tct.1971.1083337 · Cited by 10,268
Laio, A., & Parrinello, M. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.202427399 · Cited by 5,626
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
Training 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
Neuromorphic electronic systems
Mead, C. (1990) · Proceedings of the IEEE · doi:10.1109/5.58356 · Cited by 2,368
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
Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing
Kuzum, D., Jeyasingh, R. G. D., Lee, B., & Wong, H.-S. P. (2012) · Nano Letters · doi:10.1021/nl201040y · Cited by 1,267
Equivalent-accuracy accelerated neural-network training using analogue memory
Ambrogio, S., Narayanan, P., Tsai, H., Shelby, R. M., Boybat, I., di Nolfo, C., Sidler, S., Giordano, M., Bodini, M., Farinha, N. C. P., et al. (2018) · Nature · doi:10.1038/s41586-018-0180-5 · Cited by 1,151
Burr, G. W., Shelby, R. M., Sidler, S., di Nolfo, C., Jang, J., Boybat, I., Shenoy, R. S., Narayanan, P., Virwani, K., Giacometti, E. U., et al. (2015) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2015.2439635 · Cited by 936
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
A 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 758
The rise of intelligent matter
Kaspar, C., Ravoo, B. J., van der Wiel, W. G., Wegner, S. V., & Pernice, W. H. P. (2021) · Nature · doi:10.1038/s41586-021-03453-y · Cited by 526
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
An overview of phase-change memory device physics
Le Gallo, M., & Sebastian, A. (2020) · Journal of Physics D: Applied Physics · doi:10.1088/1361-6463/ab7794 · Cited by 460
Metadata
- Authors
- Zhang, W., Mazzarello, R., Wuttig, M., & Ma, E.
- Venue
- Nature Reviews Materials
- Published
- 2019-01-07
- Volume
- 4
- Issue
- 3
- Pages
- 150-168
- ISSN
- 2058-8437 (ISSN-L)
- OpenAlex
- W2911001665
- Cited by
- 885
- References
- 14
- FWCI
- 4.87
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Designing crystallization in phase-change materials for universal memory and neuro-inspired computing. https://app.cochat.ai/papers/10.1038/s41578-018-0076-x
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- Zhang, W., Mazzarello, R., Wuttig, M., & Ma, E. (2019). Designing crystallization in phase-change materials for universal memory and neuro-inspired computing. Nature Reviews Materials. https://doi.org/10.1038/s41578-018-0076-x
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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.