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Optoelectronic resistive random access memory for neuromorphic vision sensors

Nature Nanotechnology volume 14, pages 776–782 (2019)Cite this article

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Abstract

Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumption. Here we show simple two-terminal optoelectronic resistive random access memory (ORRAM) synaptic devices for an efficient neuromorphic visual system that exhibit non-volatile optical resistive switching and light-tunable synaptic behaviours. The ORRAM arrays enable image sensing and memory functions as well as neuromorphic visual pre-processing with an improved processing efficiency and image recognition rate in the subsequent processing tasks. The proof-of-concept device provides the potential to simplify the circuitry of a neuromorphic visual system and contribute to the development of applications in edge computing and the internet of things.

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Fig. 1: Non-volatile switching characteristics of ORRAM.
Fig. 2: Light-tunable synaptic characteristics.
Fig. 3: Image memorization and preprocessing.
Fig. 4: Simulations of image recognition in a neuromorphic visual system with ORRAM.

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Data availability

The data that support the plots within these paper and other findings of this study are available from the corresponding author upon reasonable request.

Code availability

The simulation codes used for this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This work was supported by the Research Grants Council of Hong Kong (PolyU 152053/18E), the Hong Kong Polytechnic University (G-YBPS, 1-ZVGH, 1-ZE25 and G-SB79) and the National Natural Science Foundation of China (61851402 and 61421005). F.Z. thanks Y. Liu, Y. Zhang and M. Wang for helpful discussions, S. H. Cheung and S. K. So for the photothermal deflection spectroscopy test and J. Zhang for the ultraviolet photoelectron spectroscopy test.

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Authors and Affiliations

  1. Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China

    Feichi Zhou, Jiewei Chen, Tsz Hin Choy, Jingli Wang, Ning Zhang, Ziyuan Lin & Yang Chai

  2. Institute of Microelectronics, Peking University, Beijing, China

    Zheng Zhou & Jinfeng Kang

  3. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA

    Shimeng Yu

  4. Department of Electrical Engineering, Stanford University, Stanford, CA, USA

    H.-S. Philip Wong

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  1. Feichi Zhou
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Contributions

Y.C. and F.Z. conceived and designed the project. Y.C. supervised the project. F.Z., T.H.C., J.W. and Z.L. performed the experiments, including both fabrication and characterization. Z.Z., F.Z., J.C., S.Y. and J.K. performed the simulations. J.C. performed the density functional theory calculations. F.Z., N.Z., Y.C., S.Y., J.K. and H.-S.P.W. analysed the data. F.Z. and Y.C. co-wrote the paper. All the authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Yang Chai.

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Peer review information: Nature Nanotechnology thanks Dae-Hyeong Kim and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Zhou, F., Zhou, Z., Chen, J. et al. Optoelectronic resistive random access memory for neuromorphic vision sensors. Nat. Nanotechnol. 14, 776–782 (2019). https://doi.org/10.1038/s41565-019-0501-3

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