Compact X- and Y-shaped dual-mode dielectric resonator filters of fourth and second order are presented, respectively. The dielectric rods are used in conventional TM010-mode. Different resonator structures can be build up by suitable combination of the rods. The X-shape dielectric resonator filter consists of two cavities, where dual-mode operation is achieved by orthogonal arrangement of the dielectric rods. Due to suitable design of the coupling aperture two transmission zeros are generated permitting the realization of a quasi-elliptic response. The filter is manufactured and measurement results are compared with simulation. Furthermore, a Y-shape dielectric resonator filter is investigated. This filter provides the possibility of a further reduction of dielectric material, while still quasi-elliptic filter responses can be realized. The filter structure of both filter types is described and measurement results are presented.

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/root Hz at 10 Hz.

A novel readout method for thin-film magnetoelectric sensors is discussed. A magnetoelectric cantilever-shaped sensor is integrated into a microwave resonator which is detuned by exposure to a desired magnetic field. With the readout method, a limit of detection of 50 pT/√Hz in the mechanical resonance frequency of the ME sensor is achieved which is comparable to conventional readout methods for magnetoelectric sensors.

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.

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.

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 (wellknown) 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.

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.

Composite magnetoelectrics implemented as thin film heterostructures are discussed in view of their applicability as highly sensitive magnetic field sensors. Here, either PZT or AlN served as piezoelectric component. The magnetostrictive phase consisted of layer systems based on FeCo or (Fe90Co10)(78)Si12B10. All functional layers were deposited with thicknesses of a few micrometers on Si cantilever structures with typical lateral dimensions of 25 mm by 2.2 mm. Magnetoelectric coefficients as large as 6900 V/cm Oe and a limit of detection as low as 1 pT/(Hz)(1/2) were measured. Currently, the best result demonstrates a detection limit of 500 fT/(Hz)(1/2) at 958 Hz frequency using a set of two sensors for external noise suppression. A frequency conversion technique is proposed to broaden the applicability of resonant magnetoelectric sensors to a wider frequency range. Finally, the achieved sensor performance is evaluated with regard to typical magnetic field amplitudes in medical applications.

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.

Sensors based on the magnetoelectric (ME) effect have the potential to be genuine alternatives for measuring bio-magnetic signals. Unfortunately, the sensor structure usually inhibits the problem that several non-magnetic types of noise couple mechanically into the sensor: in this contribution, we will focus on undesired acoustic coupling. Therefore, an adaptive cancellation approach based on a computationally efficient gradient estimation algorithm with a pseudo-optimally control scheme is proposed. The approach is using a microphone as a noise reference sensor and is implemented in real time. An evaluation in terms of measurements is performed inside a magnetically shielded chamber. For a particular scenario, which is characterized by double excitation, an algorithm with binary control-scheme improves the signal-to-noise ratio (SNR) only by around 4dB. If the proposed control scheme is used instead, an improvement of the SNR of around 13dB is achieved.

For magnetic field measurements with magnetoelectric sensors sensitivities for AC magnetic fields in the femto-Tesla range are desired. Important factors for the necessary signal/noise ratio are extrinsic noise sources such as vibrations and acoustics. In this paper a concept to reduce the noise contributions from these sources is suggested and investigated. It is shown that by connecting two magnetoelectric sensors with pico-Tesla sensitivity in a tuning fork structure the noise level caused by acoustic and vibrational coupling can be strongly reduced. (C) 2015 Elsevier B.V. All rights reserved.