The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Organic electronics for neuromorphic computing
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Citations
Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
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A fast learning algorithm for deep belief nets
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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 · cited 2×
“On the other hand, following the seminal paper from Leon Chua, in which he theoretically described a memristor 10 , and then the first experimental demonstration of a memristor in 2008 11 , there has been a significant amount of research into facilitating parallel computation, such as the…”
BackgroundMethodNanoscale 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 · cited 1×
“…4,40 , here we will focus mainly on organic memristive devices enabling continuous (that is, analogue) resistance tuning, which is ideally suited for on-chip learning and inference using parallel multiply– accumulate operations 6,41 and has also been proposed in a related inorganic system 42 .”
BackgroundMemristive devices for computing
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Training and operation of an integrated neuromorphic network based on metal-oxide memristors
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Cited by
Yang, J. C., Mun, J., Kwon, S. Y., Park, S., Bao, Z., & Park, S. (2019) · Advanced Materials · doi:10.1002/adma.201904765 · Cited by 1,641
Charge transport in high-mobility conjugated polymers and molecular semiconductors
Fratini, S., Nikolka, M., Salleo, A., Schweicher, G., & Sirringhaus, H. (2020) · Nature Materials · doi:10.1038/s41563-020-0647-2 · Cited by 895
Self-citationFlexible 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
Wang, M., Luo, Y., Wang, T., Wan, C., Pan, L., Pan, S., He, K., Neo, A., & Chen, X. (2021) · Advanced Materials · doi:10.1002/adma.202003014 · Cited by 451
Sun, T., Feng, B., Huo, J., Xiao, Y., Wang, W., Peng, J., Li, Z., Du, C., Wang, W., Zou, G., et al. (2024) · Nano-Micro Letters · doi:10.1007/s40820-023-01235-x · Cited by 384
Metadata
- Authors
- van de Burgt, Y., Melianas, A., Keene, S. T., Malliaras, G., & Salleo, A.
- Venue
- Nature Electronics
- Published
- 2018-07-13
- Volume
- 1
- Issue
- 7
- Pages
- 386-397
- ISSN
- 2520-1131 (ISSN-L)
- OpenAlex
- W2883711383
- Cited by
- 1,104
- References
- 23
- FWCI
- 31.61
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Organic electronics for neuromorphic computing. https://app.cochat.ai/papers/10.1038/s41928-018-0103-3
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- van de Burgt, Y., Melianas, A., Keene, S. T., Malliaras, G., & Salleo, A. (2018). Organic electronics for neuromorphic computing. Nature Electronics. https://doi.org/10.1038/s41928-018-0103-3
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.
