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Influence of the piezoelectric material on the signal and noise of magnetoelectric magnetic field sensors based on the delta-E effect

Benjamin Spetzler, Jingxiang Su, Ron-Marco Friedrich, Florian Niekiel, Simon Fichtner, Fabian Lofink, Franz Faupel

2021APL Materials27 citationsDOIOpen Access PDF

Abstract

Magnetoelectric thin-film sensors based on the delta-E effect have widely been reported for the detection of low frequency and small amplitude magnetic fields. Such sensors are usually fabricated with microelectromechanical system technology, where aluminum nitride (AlN) is the established piezoelectric material. Here, we present aluminum scandium nitride (AlScN) for delta-E effect sensors instead and compare it with AlN using two sensors of identical design. The sensors are experimentally and theoretically analyzed regarding sensitivity, noise, limit of detection (LOD), and resonator linearity. We identify the influence of the dominating piezoelectric coefficients dij and other material parameters. Simulations and measurements demonstrate that, in contrast to the conventional direct operation of magnetoelectric sensors, a sensitivity increase ∝dij2 and a LOD improvement ∝dij−1 can be achieved if thermal–mechanical noise is dominant. In the present case, an 8× improved sensitivity and LOD are measured with AlScN at small excitation amplitudes. This factor decreases with increasing amplitude and resonator nonlinearities. The overall minimum LOD does not change due to an earlier onset of magnetic noise in the AlScN sensor. All in all, this study reveals the influence of the piezoelectric material on the signal and noise of delta-E effect sensors and the potential of AlScN to significantly improve sensitivity.

Topics & Concepts

Materials sciencePiezoelectricitySensitivity (control systems)ResonatorNoise (video)Magnetoelectric effectNitrideAmplitudeSIGNAL (programming language)Piezoelectric sensorOptoelectronicsAcousticsMagnetic fieldElectronic engineeringComposite materialOpticsPhysicsFerroelectricityImage (mathematics)Computer scienceEngineeringLayer (electronics)Artificial intelligenceProgramming languageQuantum mechanicsMultiferroicsDielectricMultiferroics and related materialsAcoustic Wave Resonator TechnologiesMagnetic and transport properties of perovskites and related materials