The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Reconfigurable halide perovskite nanocrystal memristors for neuromorphic computing
Open accessAbstract
Many in-memory computing frameworks demand electronic devices with specific switching characteristics to achieve the desired level of computational complexity. Existing memristive devices cannot be reconfigured to meet the diverse volatile and non-volatile switching requirements, and hence rely on tailored material designs specific to the targeted application, limiting their universality. “Reconfigurable memristors” that combine both ionic diffusive and drift mechanisms could address these limitations, but they remain elusive. Here we present a reconfigurable halide perovskite nanocrystal memristor that achieves on-demand switching between diffusive/volatile and drift/non-volatile modes by controllable electrochemical reactions. Judicious selection of the perovskite nanocrystals and organic capping ligands enable state-of-the-art endurance performances in both modes – volatile (2 × 10 6 cycles) and non-volatile (5.6 × 10 3 cycles). We demonstrate the relevance of such proof-of-concept perovskite devices on a benchmark reservoir network with volatile recurrent and non-volatile readout layers based on 19,900 measurements across 25 dynamically-configured devices.
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Cites
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Self-citationU1 snRNP regulates cancer cell migration and invasion in vitro
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Memristive devices for computing
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Pseudo-halide anion engineering for α-FAPbI3 perovskite solar cells
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Cited by
Han, J., Park, K., Tan, S., Vaynzof, Y., Xue, J., Diau, E. W.-G., Bawendi, M. G., Lee, J.-W., & Jeon, I. (2025) · Nature Reviews Methods Primers · doi:10.1038/s43586-024-00373-9 · Cited by 304
Linearly programmable two-dimensional halide perovskite memristor arrays for neuromorphic computing
Kim, S. J., Im, I. H., Baek, J. H., Choi, S., Park, S. H., Lee, D. E., Kim, J. Y., Kim, S. Y., Park, N.-G., Lee, D., et al. (2025) · Nature Nanotechnology · doi:10.1038/s41565-024-01790-3 · Cited by 157
Metadata
- Authors
- John, R. A., Demirağ, Y., Shynkarenko, Y., Berezovska, Y., Ohannessian, N., Payvand, M., Zeng, P., Bodnarchuk, M. I., Krumeich, F., Kara, G., Shorubalko, I., Nair, M. V., Cooke, G. A., Lippert, T., Indiveri, G., & Kovalenko, M. V.
- Venue
- Nature Communications
- Published
- 2022-04-19
- Volume
- 13
- Issue
- 1
- Pages
- 2074-2074
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W4224296904
- Cited by
- 292
- References
- 66
- FWCI
- 16.86
- Type
- journal article
- Language
- en
- Open access
- gold
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- John, R. A., Demirağ, Y., Shynkarenko, Y., Berezovska, Y., Ohannessian, N., Payvand, M., Zeng, P., Bodnarchuk, M. I., Krumeich, F., Kara, G., Shorubalko, I., Nair, M. V., Cooke, G. A., Lippert, T., Indiveri, G., & Kovalenko, M. V. (2022). Reconfigurable halide perovskite nanocrystal memristors for neuromorphic computing. Nature Communications. https://doi.org/10.1038/s41467-022-29727-1
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