Reconfigurable halide perovskite nanocrystal memristors for neuromorphic computing

John, Rohit Abraham; Demirağ, Yiğit; Shynkarenko, Yevhen; Berezovska, Yuliia; Ohannessian, Natacha; Payvand, Melika; Zeng, Peng; Bodnarchuk, Maryna I; Krumeich, Frank; Kara, Gökhan; Shorubalko, Ivan; Nair, Manu V; Cooke, Graham A; Lippert, Thomas; Indiveri, Giacomo; Kovalenko, Maksym V

doi:10.1038/s41467-022-29727-1

Citations

Citation copied

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, 13(1), 2074. https://doi.org/10.1038/s41467-022-29727-1

Abstract

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