Towards magnonic memory: reversal of nanomagnets on yttrium iron garnet by propagating spin waves

Dirk Grundler, EPFL

D. GRUNDLER1,2

1Institute of Materials (IMX), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
2Institute of Electrical and Micro Engineering (IEM), EPFL, 1015 Lausanne, Switzerland

Magnonics based computing has regained increasing interest when micromagnetic simulations showed that ferromagnetic nanoelements control the interference of spin waves (magnons) in low-damping yttrium iron garnet (YIG) and give rise to a neural network [1]. Magnonics-based in-memory computation would be even more promising if nonvolatile magnetic bits could store directly magnon signals. I will report on our experiments which show that magnons with wavelengths down to 99 nm in YIG induce the reversal of bistable nanomagnets assisted by a small bias field [2]. We combine broadband spin-wave spectroscopy, micro-focus Brillouin light scattering and magnetic force microscopy and study the magnon-induced reversal depending on the YIG thickness, interface properties, nanomagnet shape, the magnon amplitude and their propagation length over 100 m. The magnon-induced reversal is found to be a robust effect [2] and contributes to the progress of on-chip devices which combine the concept of a neural network with an embedded magnonic memory. The work was supported by SNSF via grant 197360.

References:
[1] Papp A., Porod W., Csaba G. (2021). Nat. Commun. 12, 6422.
[2] Baumgaertl K., Grundler D. (2023). Nat. Commun. 14, 1490; Joglekar S. et al. (2023). https://arxiv.org/abs/2312.09177; Mucchietto A. et al. (2023). https://arxiv.org/abs/2312.15107 .

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