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Lecture

A Multi-Mode Model for the Signal-to-Noise-Ratio in Magnetoelectric Sensors Limited by Thermal-Mechanical Noise

Thursday (08.06.2017)
12:10 - 12:30 Förde II
Part of:


Magnetoelectric (ME) sensors with cantilever geometry, based on laminated ME composites, are a viable way to detect magnetic fields in the pT range at room temperature with low-cost devices [1]. Like other resonating cantilevers employed e.g. as AFM tips, these ME sensors are found to have their total intrinsic noise contribution affected by thermal-mechanical noise [2]. This thermal-mechanical noise is a direct consequence of the fluctuation-dissipation theorem.

Using Euler–Bernoulli beam theory, a multi-mode model for the corresponding amplitude signal-to-noise ratio (SNR) in laminated cantilever structures is proposed and applied to the case of ME sensors. Routes to improving the SNR in resonance will be discussed and compared with experimental data. This includes the potential of using higher modes with dedicated geometries of the magnetostrictive phase, as well as general geometry dependencies. The model allows a prediction of the minimal detectable stress introduced by the magnetostrictive layer, compared to the state of the art, while the SNR is limited by thermal-mechanical noise.


Funding by the Collaborative Research Center SFB 1261 is gratefully acknowledged.


[1] Marauska, S., Jahns, R., Greve, H., Quandt, E., Knöchel, R., Wagner, B., MEMS magnetic field sensor based on magnetoelectric composites, J. Micromech. Microeng. 22, 065024 (2012)

[2] Durdaut, P., Salzer, S., Reermann, J., Röbisch, V., Hayes, P., Piorra, A., Quandt, E., Schmidt, G., Knöchel, R., Höft, M., Thermal-Mechanical Noise in Resonant Thin-Film Magnetoelectric Sensors, IEEE Sensors Journal, submitted

Speaker:
Simon Fichtner
Christian-Albrechts-University of Kiel
Additional Authors:
  • Phillip Durdaut
    Kiel University
  • Christine Kirchhof
    Kiel University
  • Fabian Lofink
    Fraunhofer Institute for Silicon Technology
  • Eckhard Quandt
    Kiel University
  • Michael Höft
    Kiel University
  • Bernhard Wagner
    Fraunhofer Institute for Silicon Technology