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An optoelectronic synapse based on α-In2Se3 with controllable temporal dynamics for multimode and multiscale reservoir computing

Nature Electronics volume 5, pages 761–773 (2022)Cite this article

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Abstract

Neuromorphic computing based on emerging devices could overcome the von Neumann bottleneck—the restriction created by having to transfer data between memory and processing units—and help deliver energy-efficient data processing. The van der Waals semiconductor α-phase indium selenide (α-In2Se3) offers ferroelectric, optoelectronic and semiconducting properties and is potentially an ideal substrate for information processing, but its physical properties are not well exploited. Here we report an optoelectronic synapse that is based on α-In2Se3 and has controllable temporal dynamics under electrical and optical stimuli. Tight coupling between ferroelectric and optoelectronic processes in the synapse can be used to realize heterosynaptic plasticity, with relaxation timescales that are tunable via light intensity or back-gate voltage. We use the synapses to create a multimode reservoir computing system with adjustable nonlinear transformation and multisensory fusion, which is demonstrated using a multimode handwritten digit-recognition task and a QR code recognition task. We also create a multiscale reservoir computing system via the tunable relaxation timescale of the α-In2Se3 synapse, which is tested using a temporal signal prediction task.

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Fig. 1: Schematic and characterization of ferroelectric van der Waals α-In2Se3.
Fig. 2: Electrical synapse based on ferroelectric α-In2Se3.
Fig. 3: Optoelectronic synapse based on the optical response of α-In2Se3.
Fig. 4: Heterosynaptic plasticity of the α-In2Se3 device with light/back-gate as modulating terminal.
Fig. 5: Multimode handwritten digit recognition with mixed-input reservoir computing.
Fig. 6: Multiple-timescale reservoir computing using memristors with tunable relaxation time.

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Data availability

The data that support the findings of this study are available on Zenodo (https://zenodo.org/record/7120149#.YzRSL0xBw2w). All other data are available from the corresponding author upon reasonable request.

Code availability

The codes used for simulation and data plotting are available from the corresponding authors upon reasonable request.

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Acknowledgements

This work was supported by the National Key R&D Program of China (2017YFA0207600, to Y.Y.), the National Natural Science Foundation of China (61925401, to Y.Y.; 92064004, to Y.Y.; 61927901, to R.H.; 92164302, to Y.Y.), Project 2020BD010 was supported by the PKU-Baidu Fund and the 111 Project (B18001, to R.H.). Y.Y. acknowledges support from the Fok Ying-Tong Education Foundation and the Tencent Foundation through the XPLORER PRIZE. We acknowledge the Electron Microscopy Laboratory of Peking University, China for use of the Cs-corrected Titan Cubed Themis G2 300 transmission electron microscope.

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Authors and Affiliations

  1. Beijing Advanced Innovation Center for Integrated Circuits, School of Integrated Circuits, Peking University, Beijing, China

    Keqin Liu, Teng Zhang, Bingjie Dang, Lin Bao, Liying Xu, Caidie Cheng, Zhen Yang, Ru Huang & Yuchao Yang

  2. Center for Brain Inspired Chips, Institute for Artificial Intelligence, Frontiers Science Center for Nano-optoelectronics, Peking University, Beijing, China

    Ru Huang & Yuchao Yang

  3. Center for Brain Inspired Intelligence, Chinese Institute for Brain Research (CIBR), Beijing, China

    Ru Huang & Yuchao Yang

  4. Beijing Academy of Artificial Intelligence, Beijing, China

    Yuchao Yang

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  1. Keqin Liu
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Contributions

K.L. and Y.Y. designed the experiments. K.L. and L.B. fabricated the devices. K.L. performed PFM measurements. K.L., L.X., C.C. and Z.Y. performed electrical measurements. K.L. and T.Z. performed the simulations. K.L., B.D. and Y.Y. prepared the manuscript. Y.Y. and R.H. directed all the research and supervised the work. All authors analysed the results and implications and commented on the manuscript at all stages.

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Correspondence to Ru Huang or Yuchao Yang.

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Nature Electronics thanks Matthew Dale, Matthew Marinella and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Figs. 1–23, Notes 1–3, Table 1 and references 1–23.

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Liu, K., Zhang, T., Dang, B. et al. An optoelectronic synapse based on α-In2Se3 with controllable temporal dynamics for multimode and multiscale reservoir computing. Nat Electron 5, 761–773 (2022). https://doi.org/10.1038/s41928-022-00847-2

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