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Recently, Delta-E effect magnetic field sensors based on exchange-biased magnetic multilayers have shown the potential of detecting low-frequency and small-amplitude magnetic fields. Their design is compatible with microelectromechanical system technology, potentially small, and therefore, suitable for arrays with a large number N of sensor elements. In this study, we explore the prospects and limitations for improving the detection limit by averaging the output of N sensor elements operated in parallel with a single oscillator and a single amplifier to avoid additional electronics and keep the setup compact. Measurements are performed on a two-element array of exchange-biased sensor elements to validate a signal and noise model. With the model, we estimate requirements and tolerances for sensor elements using larger N. It is found that the intrinsic noise of the sensor elements can be considered uncorrelated, and the signal amplitude is improved if the resonance frequencies differ by less than approximately half the bandwidth of the resonators. Under these conditions, the averaging results in a maximum improvement in the detection limit by a factor of N. A maximum N≈200 exists, which depends on the read-out electronics and the sensor intrinsic noise. Overall, the results indicate that significant improvement in the limit of detection is possible, and a model is presented for optimizing the design of delta-E effect sensor arrays in the future.

This article presents the frequency response of a surface acoustic wave (SAW) sensor for current measurements. The SAW sensor exploits the Love waves of a magnetostrictively coated delay line. The focus of this article lies on the frequency response of the sensor, which shows a very wide bandwidth. The delay time $\tau _D$ is the time an acoustic wave needs to traverse the delay line. Since the acoustic wave is modulated during the whole duration of the delay line crossing, $\tau _D$ is comparable to the integration time of a sample-and-hold device. The signal measured with the SAW sensor is averaged over the delay time. Therefore, undersampling behavior occurs for signal frequencies approaching $1/{\tau_D}$ . A mathematical model of their frequency response up to several megahertz was developed and compared with measurements of two SAW sensors with different delay line lengths.

International audience; Magnetoelastic sensors for the detection of low-frequency and low-amplitude magnetic fields are in the focus of research for more than 30 years. In order to minimize the limit of detection (LOD) of such sensor systems, it is of high importance to understand and to be able to quantify the relevant noise sources. In this contribution, cantilever-type electromechanical and magnetoelastic resonators, respectively, are comprehensively investigated and mathematically described not only with regard to their phase sensitivity but especially to the extent of the sensor-intrinsic phase noise. Both measurements and calculations reveal that the fundamental LOD is limited by additive phase noise due to thermal-mechanical noise of the resonator, i.e. by thermally induced random vibrations of the cantilever, and by thermal-electrical noise of the piezoelectric material. However, due to losses in the magnetic material parametric flicker phase noise arises, limiting the overall performance. In particular, it is shown that the LOD is virtually independent of the magnetic sensitivity but is solely determined by the magnetic losses. Instead of the sensitivity, the magnetic losses, represented by the material's effective complex permeability, should be considered as the most important parameter for the further improvement of such sensors in the future. This implication is not only valid for magnetoelastic cantilevers but also applies to any type of magnetoelastic resonator.

Thin-film magnetoelectric sensors are able to measure very low magnetic fields. As a consequence the hypothesis that magnetoelectric sensors could be used for biomagnetic measurements was often mentioned but never proven. In this contribution the first proof of this hypothesis will be given by the measurement of the (well-known) R-wave of the human heart. This will be achieved by closing the gap between the sensor sensitivity and the signal level by averaging. In order to guarantee a fast convergence of the averaging process even in very noisy (realistic) measurement environments, different adaptive averaging techniques in the time- and frequency-domain are pointed out. The evaluation by synthetic measurements shows an improvement of the averaging process by up to 20 dB in terms of signal-to-noise ratio for an instationary measurement scenario in comparison to the conventional averaging after 750 average periods. Finally, measurements of the R-wave of a human heart are performed.

To enable the measurement of low-frequency magnetic signals with cantilever type thin-film magnetoelectric sensors, magnetic frequency conversion transfers the frequency of the desired signal into the mechanical resonance of the cantilever. The system electronics for the realization of this approach and the approach itself introduce additional noise sources as compared with direct detection, which lowers the limit of detection. In this paper, the magnetic frequency conversion noise sources are reviewed, discussed, and evaluated for our setup. The model for the nonlinear transfer process is implemented in the time domain. This enables the consideration of the pump noise in a noise equivalent circuit. For the sensor type under investigation, the dominant noise near its optimal working point originates from the pump source. If the noise of the pump can be decreased and magnetic excess noise is not dominant, the noise limit is the thermal-mechanical noise of the sensor. The implementation of a filter after the excitation source decreases the limit of detection to 60 pT/ $\sqrt {\text {Hz}}$ at 10 Hz.

A comprehensive noise model of a junction gate field-effect transistor (JFET) charge amplifier is presented for applications with piezoelectric sensors. Based on this previously reported amplifier structure, a noise equivalent circuit is derived and discussed. Universal noise gain expressions for each of the twelve considered noise sources are given. By means of an analytical description of the charge amplifier’s noise behavior, the design and optimization of such preamplifiers for various capacitive microelectromechanical sensor systems will be distinctly simplified. Calculations of the noise floor are compared with measurements with a cantilever-type magnetoelectric sensor and with the performance of a so far commonly utilized basic charge amplifier. With the JFET charge amplifier a noise reduction of approximately 22 dB is achieved in the vicinity of the utilized sensor’s resonance frequency of 7.45 kHz. The reported amplifier is the first which has no negative influence on the total noise level of a resonant magnetoelectric sensor system.

We present a comprehensive noise model for an electromechanical resonator that is utilized as a magnetic field sensor. The cantilever-type sensor is coated with a magnetostrictive film that exhibits a change in elastic modulus E with a magnetic field and therefore detunes the resonator—the so-called delta-E effect. The noise model contains all relevant noise sources from the operational electronics, the wiring, and the sensor itself. Measurements show good agreement up to a certain excitation voltage, where an additional dominant noise source appears. It is identified as originating from the magnetic film. With the results of the model, the operational parameters of such sensors are discussed. The model predicts that the limit of detection at 10 Hz for the present sensors can be improved to 60 pT/(Hz) $^{1/2}$ if the magnetic noise is eliminated.

Thin-film magnetoelectric sensors reach a sensitivity in the picotesla range around the resonance frequency of the mechanical structure. Using magnetic frequency conversion, a magnetic low-frequency signal can be transferred to the sensor's resonance frequency. However, the required additional large carrier signal leaks to the sensor's output with a large amplitude, requiring a wide dynamic range of the sensor electronics. In this paper, it is shown that the unbalance of the magnetostriction curve is responsible for this leakage and that a suppression approach is devised. After theoretical analysis of the nonlinear magnetostriction characteristic, a carrier suppression is achieved through balancing by an altered signal excitation. A suppression of the carrier signal of about three orders of magnitude is measured. Thus, the requirements regarding analog-to-digital conversion can be reduced.

Thin-film magnetoelectric sensors, i.e., composites of magnetostrictive and piezoelectric materials, are able to measure very low magnetic flux densities in the picotesla range. In order to further improve the limit of detection it is of high importance to understand and quantify the relevant noise sources. In this paper, a common model for the deflection noise in vibrational structures is applied to the cantilever structure of resonant magnetoelectric sensors. By means of deflection and noise measurements the existence of thermal-mechanical noise even in sensor structures with a size in the centimeter range is proven. Based on these findings a noise equivalent circuit is suggested which allows not only the distinction between the impact of different sensor-intrinsic noise sources and also the involvement of the preamplifier noise. We found that the thermal-mechanical noise is the dominant noise source if direct signal detection is performed at the first bending resonance frequency of the sensor. However, this kind of noise is not the limiting influence when applying magnetic frequency-conversion techniques.

Magnetic frequency conversion is a promising technique to enhance the limit of detection of magnetoelectric sensors detecting low-frequency magnetic signals. In comparison with the direct detection in the mechanical resonance of the sensor, this method shows a limit of detection increased, i.e., worsened, by approximately 2.5 decades. For the detection of bio-magnetic signal, frequencies ranging from 0.1 Hz up to approximately 100 Hz though the method yield a better limit of detection than direct detection. Still, it is worse than theoretically expected. The cause of the deterioration of the signal-to-noise ratio during magnetic frequency conversion is investigated. Besides the conversion loss, it is due to the arising magnetic noise during excitation of a magnetostrictive material with a pumping signal, which is also in the order of approximately 2.5 decades. The noise can be reduced by applying an additional dc-bias field, which simultaneously results in less output signal. Measurements are confirmed by a numerical model. An existing equivalent noise model for magnetoelectric sensors is extended accordingly.

Magnetoelectric (ME) thin film composites consisting of sputtered piezoelectric (PE) and magnetostrictive (MS) layers enable for measurements of magnetic fields passively, i.e. an AC magnetic field directly generates an ME voltage by mechanical coupling of the MS deformation to the PE phase. In order to achieve high field sensitivities a magnetic bias field is necessary to operate at the maximum piezomagnetic coefficient of the MS phase, harnessing mechanical resonances further enhances this direct ME effect size. Despite being able to detect very small AC field amplitudes, exploiting mechanical resonances directly, implies a limitation to available signal bandwidth along with the inherent inability to detect DC or very low frequency magnetic fields. The presented work demonstrates converse ME modulation of thin film Si cantilever composites of mesoscopic dimensions (25 mm × 2.45 mm × 0.35 mm), employing piezoelectric AlN and magnetostrictive FeCoSiB films of 2 µm thickness each. A high frequency mechanical resonance at about 515 kHz leads to strong induced voltages in a surrounding pickup coil with matched self-resonance, leading to field sensitivities up to 64 kV/T. A DC limit of detection of 210 pT/Hz1/2 as well as about 70 pT/Hz1/2 at 10 Hz, without the need for a magnetic bias field, pave the way towards biomagnetic applications.

International audience; Surface acoustic wave (SAW) sensors in the form of two-port resonators or delay lines are widely used in various fields of application. The readout of such sensors is achieved by electronic systems operating either in an open-loop or in a closed-loop configuration. The mode of operation of the sensor system is usually chosen based on requirements like, e.g., bandwidth, dynamic range, linearity, costs, and immunity against environmental influences. Because the limit of detection (LOD) at the output of a sensor system is often one of the most important figures of merit, both readout structures, i.e., open-loop and closed-loop systems, are analyzed in terms of the minimum achievable LOD. Based on a comprehensive phase noise analysis of these structures for both resonant sensors and delay line sensors, expressions for the various limits of detection are derived. Under generally valid conditions, the equivalence of open-loop and closed-loop operation is shown for both types of sensors. These results are not only valid for SAW devices, but are also applicable to all kinds of phase-sensitive sensors.

In this work surface acoustic Love wave delay line magnetic field sensors with varying magnetostrictive layer thicknesses are discussed. Amorphous FeCoSiB is used as the sensitive layer with a thickness variation in the range of 25-400 nm. Each sensor is analyzed both by magneto-optical methods as well as electrical signal and noise measurements. In accordance with previously reported simulation results, the impact on the acoustically propagating wave's velocity distinctly increased with thicker magnetostrictive layers leading to magnetic sensitivities as high as 35 rad/T for a delay line coated with 400 nm thick FeCoSiB. Measurements of the sensor-intrinsic phase noise revealed distinct flicker phase noise that scales proportionally with the increase in magnetic sensitivity, thus leading to virtually constant limits of detection (LOD). Assuming that the observed flicker noise is caused by magnetic hysteresis losses due to the high-frequency excitation of the magnetic material, the LOD's independence of the magnetic sensitivity can even be shown analytically. However, it also becomes clear that such sensors need a magnetostrictive coating with a minimum thickness of at least 50 nm such that the signal-to-noise ratio is dominated by the magnetic material and not by fundamental noise contributions of the substrate. On the contrary, layers with thickness above 300 nm lead to distinct higher hysteresis losses that outrun the simultaneous increase in sensitivity, thus leading to a worse overall performance.

Surface acoustic wave magnetic field sensors based on guided Love waves using the DE effect of a magnetostrictive thin film have been shown to be promising candidates for the measurement of weak fields at low frequencies as required for biomagnetic applications or as current sensors benefitting from the large dynamic range and bandwidth. The deposition of soft magnetic films with high magnetostriction is, however, more challenging on piezoelectric substrates such as quartz than on silicon. Thermally induced anisotropic expansion during the deposition process or during post-deposition magnetic field annealing leads to uniaxial stresses acting on the films, which makes the precise control of magnetic anisotropy difficult. Accordingly, this work analyzes the influence of the deposition process and heat treatment on the performance of Love wave devices. ST-cut quartz based delay line surface acoustic wave sensors with a SiO2 guiding layer are employed, and a 200 nm layer of amorphous magnetostrictive (Fe90Co10)78Si12B10 is used as the sensitive element. Magneto-optical imaging is performed for magnetic domain characterization, and the sensor performance is characterized in terms of bias field dependent phase sensitivity and frequency dependent phase noise. By performing a low temperature deposition in an external magnetic field, considerable improvement in limits of detection at biomagnetic relevant frequencies down to 70 pT/SRHz at 10 Hz and 25 pT/SRHz at 100 Hz is achieved.

We present a comprehensive study of a magnetic sensor system that benefits from a new technique to substantially increase the magnetoelastic coupling of surface acoustic waves (SAW). The device uses shear horizontal acoustic surface waves that are guided by a fused silica layer with an amorphous magnetostrictive FeCoSiB thin film on top. The velocity of these so-called Love waves follows the magnetoelastically-induced changes of the shear modulus according to the magnetic field present. The SAW sensor is operated in a delay line configuration at approximately 150 MHz and translates the magnetic field to a time delay and a related phase shift. The fundamentals of this sensor concept are motivated by magnetic and mechanical simulations. They are experimentally verified using customized low-noise readout electronics. With an extremely low magnetic noise level of ≈100 pT/$$\sqrt{{\rm{Hz}}}$$ Hz , a bandwidth of 50 kHz and a dynamic range of 120 dB, this magnetic field sensor system shows outstanding characteristics. A range of additional measures to further increase the sensitivity are investigated with simulations.

Recently, there has been much interest in magnetoelectric magnetic field sensors utilizing the delta-E effect. Such sensors are fully integrable and combine the advantages of high sensitivity at low frequencies with broad bandwidth. Here, we report the influence of the quality factor Q on the signal-to-noise ratio of magnetoelectric magnetic field sensors utilizing the delta-E effect. The sensor consists of a silicon cantilever covered by a magnetostrictive and a piezoelectric thin film. The magnetization-dependent elasticity of the magnetostrictive film leads to detuning of the sensor's resonance, which is excited and read out via the piezoelectric layer. The signal-to-noise ratio is experimentally analyzed as a function of the quality factor, the excitation amplitude and the signal frequency. The results are compared with a signal and noise model to describe general tendencies. The model demonstrates that, in contrast to the conventional direct operation of magnetoelectric sensors, an improvement in the limit of detection proportional to Q3/2 can be achieved if thermal-mechanical noise is dominant. The relationship still holds for frequencies far away from the resonance frequency. This reveals the potential for improving the limit of detection significantly by increasing the quality factor, if magnetic and electronic noise can be suppressed.Recently, there has been much interest in magnetoelectric magnetic field sensors utilizing the delta-E effect. Such sensors are fully integrable and combine the advantages of high sensitivity at low frequencies with broad bandwidth. Here, we report the influence of the quality factor Q on the signal-to-noise ratio of magnetoelectric magnetic field sensors utilizing the delta-E effect. The sensor consists of a silicon cantilever covered by a magnetostrictive and a piezoelectric thin film. The magnetization-dependent elasticity of the magnetostrictive film leads to detuning of the sensor's resonance, which is excited and read out via the piezoelectric layer. The signal-to-noise ratio is experimentally analyzed as a function of the quality factor, the excitation amplitude and the signal frequency. The results are compared with a signal and noise model to describe general tendencies. The model demonstrates that, in contrast to the conventional direct operation of magnetoelectric sensors, an improvement in the...

Thin-film magnetoelectric (ME) sensors offer a promising potential to measure biomagnetic signals in the near future. Unfortunately, this sensor type shows usually a large cross-sensitivity to all kinds of mechanic distortion due to the resonant structure. In order to overcome this problem several sensor designs have been proposed. Beside these approaches adaptive noise cancellation techniques can be used to reduce the noise coupling while keeping the sensor setup simple. In this contribution reference sensors, realized as piezoelectric cantilevers, are presented and compared to microphones by means of their feasibility to improve the signal-to-noise ratio (SNR) using adaptive cancellation approaches. If a loudspeaker is used as noise source, no crucial differences are measured. But if a vibrator is used as noise source to generate structure-borne noise, the piezoelectric (PE) cantilevers are superior. As the difference of the resonance frequencies between ME and PE sensor is decreased the SNR improvement increases at low excitation levels. In total an SNR improvement over 30 dB can be achieved.

In electric vehicles, batteries with many cells are used to supply the high voltages needed for the power train. The battery is controlled by a battery management system (BMS) which needs measurement data from each individual cell. Up to now, wired solutions with specialized measurement controllers for battery modules are in use. Some of these communicate over data bus structures. Our group proposes as an alternative solution the use of wireless communication in the near RF field area. The basics of this solutions have already been published [1]. In this article we present more advanced functionality for the wireless sensors approach. A functional module has been developed for impedance spectroscopy of each individual cell in the battery stack during automotive operation. Electrochemical impedance spectroscopy is a powerful method to determine the battery state beyond common and simple models. This technique needs precise and synchronized measurements of the common current and the voltages of the individual cells. A communication and control protocol has been implemented in hard- and software, including a trigger-broadcast operating mode. This solution has to fulfill the time precision requirements of the distributed measurements in the range of a few μs. Therefore, proprietary protocol solutions have been developed. Additional modules in the sensor system allow other functions such as cell balancing and an energy saving wake-up function for the sensor modules. These sensor modules are designed as tailored hardware for integration inside the individual battery cells.