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Neuromorphic systems

Reservoir computing with 2D materials

Nature Electronics volume 5, pages 715–716 (2022)Cite this article

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Artificial synapses made of indium selenide can exhibit tunable temporal dynamics, which can be used to achieve multisensory fusion and multiple-timescale feature extraction in reservoir computing.

Conventional computers are based on a von Neumann architecture in which data are moved between separate memory and processing units. However, in applications such as artificial intelligence, this occurs frequently, which increases time and energy consumption. Neuromorphic computing is an alternative computing approach that takes inspiration from the human brain and can allow memory and processing to occur together. One category of neuromorphic computing is reservoir computing, which originates from echo state networks and liquid-state machines1.

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Fig. 1: Reservoir computing using In2Se3 synapses.

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Authors and Affiliations

  1. State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China

    Zhongming Wei

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  1. Zhongming Wei
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Correspondence to Zhongming Wei.

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Wei, Z. Reservoir computing with 2D materials. Nat Electron 5, 715–716 (2022). https://doi.org/10.1038/s41928-022-00872-1

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  • DOI: https://doi.org/10.1038/s41928-022-00872-1

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