Sep 20 – 25, 2026
University of Graz
Europe/Vienna timezone

Identifying Loss Contributions in Spin-Wave Transducers

Sep 24, 2026, 4:30 PM
30m
HS 10.11 (University of Graz)

HS 10.11

University of Graz

10 - Chemistry, 1st floor
4) Invited talk M42 - Advances in Magnonics Mini-Colloquium

Speaker

Florian Bruckner

Description

Spin-wave-based signal processing devices are promising candidates for compact, energy-efficient components in future 5G systems, including delay lines [1] and power limiters [2]. However, further optimization requires a detailed understanding of where energy is lost during transduction and propagation.

In this work, we present a systematic approach to identifying and quantifying individual loss contributions in spin-wave transducer systems. We combine micromagnetic simulations [3] with experimental S-parameter measurements to decompose the total insertion loss into its constituent parts: reflection losses from impedance mismatch, ohmic losses in the transducer metallization, propagation losses due to magnetic damping, and directional losses from spin-wave emission opposite to the intended direction. Each contribution is extracted independently from the measured impedance matrix, enabling a direct comparison between predicted and observed total transmission.

Our analysis reveals that for typical geometries at short spin-wave wavelengths, ohmic losses represent the dominant loss mechanism, while reflection losses can be addressed through impedance matching by scaling the transducer length. Simulations show that the transducer impedance scales approximately linearly with length, allowing prediction of the
optimal geometry from a single reference measurement. We explore strategies to reduce ohmic losses, including modifications to transducer thickness and operation at longer wavelengths. Applying the loss separation to experimental data from YIG-based devices, we identify residual discrepancies between model predictions and measured losses, pointing toward additional loss channels not yet captured and guiding further optimization.

References
[1] K. Davídková et al., Phys. Rev. Appl. 23, 034026 (2025).
[2] K. Davídková et al., J. Appl. Phys. 138, 14 (2025).
[3] F. Bruckner et al., Sci. Rep. 15, 19993 (2025).

Author

Florian Bruckner

Co-authors

Andrii V. Chumak (University of Vienna) Claas Abert (University of Vienna) Dieter Suess (Faculty of Physics, University of Vienna, Austria) Iason-Konstantinos Douveas (Faculty of Physics, University of Vienna, Austria) Kristýna Davídková (Faculty of Physics, University of Vienna, Austria)

Presentation materials

There are no materials yet.