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Memristive control of mutual spin Hall nano-oscillator synchronization for neuromorphic computing

Abstract

Synchronization of large spin Hall nano-oscillator (SHNO) arrays is an appealing approach toward ultrafast non-conventional computing. However, interfacing to the array, tuning its individual oscillators and providing built-in memory units remain substantial challenges. Here, we address these challenges using memristive gating of W/CoFeB/MgO/AlOx-based SHNOs. In its high resistance state, the memristor modulates the perpendicular magnetic anisotropy at the CoFeB/MgO interface by the applied electric field. In its low resistance state the memristor adds or subtracts current to the SHNO drive. Both electric field and current control affect the SHNO auto-oscillation mode and frequency, allowing us to reversibly turn on/off mutual synchronization in chains of four SHNOs. We also demonstrate that two individually controlled memristors can be used to tune a four-SHNO chain into differently synchronized states. Memristor gating is therefore an efficient approach to input, tune and store the state of SHNO arrays for non-conventional computing models.

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Fig. 1: Device schematic and multi-level resistive switching of the memristor gate.
Fig. 2: Memristive control of SHNO AOs.
Fig. 3: A chain of two SHNOs with two memristive gates.
Fig. 4: VCMA dominant control of synchronization in a chain of four SHNOs with two memristive gates.
Fig. 5: Memristive dominant control of synchronization in a chain of four SHNOs with two memristive gates.
Fig. 6: Pattern matching using a memristive SHNO chain.

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Data availability

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

Code availability

The MATLAB and MuMax codes used in this study are available from the corresponding author on reasonable request.

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Acknowledgements

This work was partially supported by the Swedish Research Council (VR grant no. 2016-05980) and the Horizon 2020 research and innovation programmes grant nos. 835068 ‘TOPSPIN’ and 899559 ‘SpinAge’. The work at Tohoku University was supported by the Japan Society for the Promotion of Science Kakenhi grant nos. 17H06093 and 19H05622, JST-CREST grant no. JPMJCR19K3, and RIEC Cooperative Research Projects.

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S.F., S.K. and H.O. developed the material stacks. M.Z. designed and fabricated the devices, and carried out all measurements and data analysis. H.F. and A.H contributed to the data analysis. R.K. and M.D. carried out all micromagnetic simulations. J.Å. led the project. All authors contributed to the interpretation of the results and cowrote the paper.

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Correspondence to Johan Åkerman.

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Peer review information Nature Materials thanks Sergej Demokritov, Jianhua Yang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Zahedinejad, M., Fulara, H., Khymyn, R. et al. Memristive control of mutual spin Hall nano-oscillator synchronization for neuromorphic computing. Nat. Mater. 21, 81–87 (2022). https://doi.org/10.1038/s41563-021-01153-6

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