Sensitivity enhancement of magnetoelectric sensors through frequency-conversion

Sensors and Actuators A 183 (2012) 16–21

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Sensors and Actuators A: Physical journal homepage: www.elsevier.com/locate/sna

Sensitivity enhancement of magnetoelectric sensors through frequency-conversion Robert Jahns a,∗ , Henry Greve b , Eric Woltermann b , Eckhard Quandt b , Reinhard Knöchel a a b

Microwave Laboratory, Institute of Electrical and Information Engineering, University of Kiel, Kaiserstrasse 2, D-24143 Kiel, Germany Inorganic Functional Materials, Institute of Materials Science, University of Kiel, Kaiserstrasse 2, D-24143 Kiel, Germany

a r t i c l e

i n f o

Article history: Received 22 February 2012 Received in revised form 29 May 2012 Accepted 29 May 2012 Available online 7 June 2012 Keywords: Modulation Magnetic field measurement Magnetoelectric sensors Magnetometers

a b s t r a c t √ Thin film magnetoelectric (ME) sensors show sensitivity levels as low as 7.1 pT/ Hz over narrow bandwidths at bandwidths of some Hz around their mechanical resonance frequency. The high sensitivity is making the sensors – in principle – suitable for biomagnetic measurements like magnetoencephalography (MEG) and magnetocardiography (MCG). Biomagnetic measurements, however, usually require high sensitivity over a wide frequency band of 0.1–100 Hz. Unfortunately, at such low frequencies far from resonance the ME coefficient decreases dramatically and the noise level increases; this leads to a significant reduction in sensitivity. This work proposes and demonstrates a novel frequency-conversion-approach, which represents a remedy to the sensitivity decay. It allows wideband measurements at low frequencies by utilizing the nonlinear characteristics of the magnetostriction curve. The new technique offers the possibility to achieve resonance enhanced sensitivities at virtually arbitrary frequencies outside and therefore also far below resonance. Measurements show that sensitivity at 1 Hz can be enhanced by a factor of ∼1000 compared to the non-resonant case using the proposed modulation technique. The new technique also offers advantages for the increase of the sensor slew rate, the suppression of mechanical noise and for the operation of such sensors in arrays. © 2012 Elsevier B.V. All rights reserved.

1. Introduction SENSORS made from magnetoelectric (ME) composite materials generate voltages that are proportional to applied magnetic fields over a wide range of field strengths. They can show sensitivity levels in the picotesla range at their mechanical resonance frequencies [1]. As a major advantage, such sensors can be operated at room temperature in contrast to the nowadays used superconducting quantum interference devices (SQUIDs). Nevertheless operation at resonance is only possible at fixed resonance frequencies over narrow bandwidths within a limited frequency range. It becomes increasingly difficult to achieve resonances below, e.g. 100 Hz. Wideband sensing of magnetic fields would require an array of such resonators, each tuned to a distinct frequency. These drawbacks can be removed and converted to the opposite by applying a novel frequency-conversion technique which will be presented in this paper. This technique allows wideband operation of sensors with high sensitivity at low frequencies. Such features are, e.g. required for the measurement of biomagnetic signals. The technique was already disclosed in a patent application [2], and will

∗ Corresponding author. Tel.: +49 4318806168; fax: +49 4318806152. E-mail address: [email protected] (R. Jahns). 0924-4247/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.sna.2012.05.049

be described in detail in the following. A similar magnetostriction modulation technique for ME sensors [3] was recently published, but shows a lower sensitivity enhancement than the one presented here. 2. Thin film ME sensor The direct ME effect describes an electric field E caused by a magnetic field H. A very useful figure of merit for magnetoelectric sensors is the ME voltage coefficient [4]: ˛ME =

∂E ∂ ∂ ∂E = · · ∂H ∂ ∂ ∂H

(1)

In Eq. (1)  is the mechanical stress and  is the magnetostriction. Due to the plate capacitor like structure of the sensor, the following ME voltage VME is generated by a ME laminate sensor with thickness L of the piezoelectric phase: VME = ˛ME · L · HAC

(2)

Fig. 1 shows the design of the investigated sensor which consists of several stacked layers. A 140 ␮m thick silicon (1 0 0) substrate (Si) with an area of 20 mm × 3 mm mainly determines the resonance frequency [5]. It is covered by a 0.3 ␮m thick molybdenum

R. Jahns et al. / Sensors and Actuators A 183 (2012) 16–21

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Fig. 1. Structure of the sensor. Fig. 3. Resonance curve.

metallization which forms the bottom electrode, and a 1.8 ␮m thick piezoelectric aluminum nitride layer. A 1.75 ␮m thick magnetostrictive FeCoSiB layer with an area of A = 33.5 mm2 is deposited on top. The sensor is clamped on an epoxy block. More detailed information about the sensor processing and its resonant behavior can be found in [5]. Usually the sensor is driven under a magnetic bias field which shifts the operating point of the magnetostrictive layer to the inflection point of the magnetostriction curve . There the derivative of the magnetostriction with respect to the magnetic field strength H and thus the ME voltage coefficient reaches its maximum (Fig. 2). Application of a magnetic bias field HBias together with an alternating magnetic field HAC to the long axis of the sensor (Fig. 1) will lead to a ME voltage VME between the Mo metallization layer and the FeCoSiB magnetostrictive layer. In Fig. 2 an alternating sinusoidal field with a rms amplitude of BAC = 1 ␮T and a frequency of fAC = 669 Hz was applied with varying bias field. The corresponding ME voltage VME was measured with a Stanford Research Systems Lock-In-Amplifier SRS 830. Fig. 3 shows the ME voltage versus frequency under application of an alternating magnetic field with a rms amplitude BAC = 1 ␮T and the optimal magnetic bias field of BBias,opt = 0.65 mT to reach the maximum ME voltage coefficient. The sensitivity S of the magnetoelectric sensor is constant for a given frequency (cp. Fig. 6) and can be calculated from the ME voltage as follows: S=

VME [V/T] BAC

Fig. 2. Dependence of VME on the magnetic bias field.

(3)

The measurement of Fig. 3 shows that the sensor has a mechanical resonance at fres = 669 Hz. Under the optimal magnetic bias field a sensitivity of Sres = 1050 V/T is obtained in resonance, which corresponds to a ME voltage coefficient of ˛ME = 583 V/cm Oe. Refs. [1,6] give detailed information about the noise and sensitivity behavior of the device. Using a charge amplifier with a “voltage gain” GCA of GCA =

VME,CA = 33 VME

(4)

and the measurement setup of Fig. 4, noise and sensitivity measurements of the device were carried out under well shielded conditions. Fig. 5 shows the measured and calculated noise voltage densities at the output of the charge amplifier. The calculation of the noise voltage density includes major contributing noise sources of sensor and amplifier, namely Johnson–Nyquist noise of the sensor and the feedback network, as well as voltage and current (shot) noise of the amplifier [1,6]. Fig. 6 shows the sensitivity and linearity measurement of the device at resonance. Herein the applied alternating magnetic flux density BAC was reduced from 10 ␮T to 10 pT and the corresponding charge amplified ME voltage was measured. √ Figs. 5 and 6 show a noise level of the sensor as low as 7.1 pT/ Hz in resonance. However, below resonance sensitivity decreases due to increasing noise level (Fig. 5) and decreasing ME coefficient (Fig. 3). Fig. 7 1 Hz input signal. Here the shows a sensitivity measurement for a √ noise level is already reached at 1 ␮T/ Hz. Below that value the output ME voltage no longer depends on the input alternating magnetic flux density.

Fig. 4. Measurement setup.

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R. Jahns et al. / Sensors and Actuators A 183 (2012) 16–21

Fig. 8. Magnetostriction curve.

3. Frequency conversion technique

Fig. 5. Noise voltage density at the amplifier output [1,6].

Fig. 6. Sensitivity of the sensor at resonance.

Eq. (1) suggests that the ME voltage depends on the derivative of the magnetostriction . The magnetostriction curve  is obtained through numerical integration of the measured voltage VME and is shown in Fig. 8. It is an even function of the magnetic field and shows a virtually quadratic behavior for small field amplitudes. As the magnetic field grows and the operating point travels along, the slope increases until a field of 0.65 mT is reached. At this value the magnetostriction curve has its deflection point and thus the steepest slope. Small variations of the applied magnetic field strength in the considered range lead to large variations in the shape of the magnetostrictive material and therefore to large variations in the ME voltage. The systematic utilization of the nonlinearity of  is now exploited for substantial improvement of the sensor sensitivity for frequencies outside the mechanical resonance and over wide bandwidths. Instead of the DC bias field BBias,opt , an alternating and thus time-varying bias field, better termed modulation field Bmod , is applied with a large amplitude. It causes a time periodic placement of the operating point on the magnetostriction curve with ωmod . This modulation field Bmod = Bˆ mod cos(ωmod t)

(5)

is superimposed with the unknown and very small alternating field to be measured: BAC = Bˆ AC cos(ωAC t)

(6)

In Eq. (5) Bˆ mod is the peak amplitude and ωmod the angular frequency of the modulation signal. Mathematically the modulation of the slope of the magnetostriction curve can be described by a parametric approach [7]. For Bˆ mod  Bˆ AC the operating point on the magnetostriction curve is virtually exclusively determined by the modulation signal. The much smaller alternating field “perceives” the instantaneous slope of the magnetostriction curve. This leads to following time dependence of the magnetostriction:



(Bmod (t) + BAC (t)) = (Bmod (t)) +

Fig. 7. Sensitivity of the sensor at 1 Hz.

∂  ∂B 

· BAC (t)

(7)

Bmod (t)

Thus changes of  depend linearly on BAC . Furthermore (∂/∂B)(Bmod (t)) is a periodic function because Bmod is periodic. This allows the expansion of (∂/∂B)(Bmod (t)) into a Fourier series.

R. Jahns et al. / Sensors and Actuators A 183 (2012) 16–21

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The magnetostriction behavior at ωmod + ωAC can be calculated as follows, using Eqs. (7) and (10): (Bmod (t) + BAC (t))|ωmod ±ωAC = A1 cos(ωmod t) · Bˆ AC cos(ωAC t)

⎡

⎛

⎞

⎤

A1 · Bˆ AC = · ⎣cos ⎝(ωmod + ωAC )t ⎠ + cos((ωmod − ωAC )t)⎦ (11) 2    ωres

Fig. 9. Fourier coefficient A1 in dependence of Bmod .

Eqs. (1) and (2) suggest that the ME voltage VME is proportional to (∂/∂B) · HAC : VME ∝

∂ ∂ · HAC ∝ · BAC ∂B ∂B

(8)

VME (Fig. 8) can be easily approximated by a fifth order polynomial as a function of the applied magnetic flux density BBias : 2 VME (BBias ) = (a0 + a1 · BBias + a2 · BBias 3 4 5 + a3 · BBias + a4 · BBias + a5 · BBias )

(9)

with a0 = −0.0075 mV, a1 = 2.4813 mV/mT, a2 = 0.0263 mV/(mT)2 , a4 = −0.0152 mV/(mT)4 and a3 = −2.3131 mV/(mT)3 , a5 = 0.6305 mV/(mT)5 . The periodic excitation with Bmod (t) allows an expansion of VME and therefore d/dB into a Fourier series which can also be truncated after the 5th degree: ∂ (Bmod (t)) ∝ ∂B

 

a2 2 3 4 + a4 Bˆ mod Bˆ 2 mod 8

a0 +





A0

+ a1 Bˆ mod +

 a

+

2 + Bˆ mod

2

 a

+

A2

3 Bˆ mod +

4

 a

+

4

 

5 5 a5 Bˆ mod cos(3ωmod t) 16

(10)



16



5

5 Bˆ mod cos(5ωmod t)

 A5

The multiplication of ∂/∂B and BAC (t) in Eq. (7) leads to new frequency components at n · ωmod ± ωAC in the magnetostriction behaviour and thus in the ME output voltage. If ωmod is chosen, e.g. such that ωmod + ωAC = ωres , BAC is shifted to the mechanical resonance of the sensor. In this case the Fourier coefficient 3 5 A1 = (a1 Bˆ mod + (3/4)a3 Bˆ mod + (5/8)a5 Bˆ mod ) has to be maximized in order to obtain the maximum output voltage at ωmod + ωAC . The maximization of the Fourier coefficient occurs at an optimum modulation flux density of Bˆ mod,opt = 0.79 mT. Fig. 9 shows the theoretically determined dependence of the Fourier coefficient A1 on the flux density of the modulation field.

= −1.51 × 10−3

A1 |Bˆ

= +1.23

A2 |Bˆ

= +5.25 × 10−3

A3 |Bˆ

= −0.22

A4 |Bˆ

= −0.74 × 10−3

A5 |Bˆ

= +12.13 × 10−3

mod,opt mod,opt

mod,opt

4 cos(4ωmod t) Bˆ mod

8

 









mod,opt

mod,opt

1 4 cos(2ωmod t) a4 Bˆ mod 2

 A3

   a A4

+





3



A0 |Bˆ

mod,opt

3 5 3 5 a3 Bˆ mod + a5 Bˆ mod cos(ωmod t) 4 8 A1

2



The frequency of the unknown signal BAC will be upconverted to the mechanical resonance frequency of the sensor. The related magnetostriction component depends linearly on Bˆ AC . Thus the resonance enhanced detection of BAC at arbitrary frequencies becomes possible: amplitude, angular frequency and phase angle of the modulation signal are known quantities and can be adjusted at will and as desired. This technique not only allows the highly sensitive detection of cosine-shaped signals at single frequencies, but of arbitrary waveforms even with wide bandwidths. The signals can be detected by either shifting the whole spectrum into the mechanical resonance, which has to be wide enough, or by frequency sweeping the modulation signal, similar to a spectrum analyzer. The only premise is that the amplitude of the measurement signal is significantly smaller than that of the modulation signal. Eq. (10) equally allows the estimation of the conversion of noise components at different frequencies to the mechanical resonance of the sensor. Therefore the Fourier coefficients A0 –A5 (arb. units) have to be calculated at the optimum modulation peak amplitude Bˆ mod,opt = 0.79 mT

(12)

The Fourier coefficients A0 , A2 and A4 are 3 orders of magnitude smaller than A1 . Thus, as can be deduced from Eq. (10), magnetic AM noise of the modulation signal at ωmod + ωAC , ωmod − ωAC and 3ωmod − ωAC is suppressed by a factor of 1000 as compared to noise at ωAC . Magnetic AM noise at 2ωmod − ωAC and 4ωmod − ωAC is suppressed by a factor of at least 5. However, AM oscillator noise is generally very weak and much smaller in comparison to FM noise [7]. FM noise of the modulation signal can be kept low by state of the art stabilization methods. It can be suppressed further, if the same modulation signal is also used for subsequent down conversion. For further noise improvement the modulation signal should be band pass filtered in order to reduce noise components below and above ωmod . Besides of making resonance enhanced readout of arbitrary frequencies possible, the proposed modulation approach of the magnetostrictive phase also shows various other significant advantages. A first advantage is the possible improvement of the sensor slew rate. The quality factor Q and resonance frequency fres of the resonance curve (Fig. 3) determines the damping coefficient ı of the mechanical resonator: ı=

 · fres Q

(13)

An attempt of lowering the resonant frequency of the sensor would lead to an increase of the quality factor. The reduced damping coefficient would be accompanied by a decrease of the slew rate of the sensor. Using frequency conversion fres can be kept

20

R. Jahns et al. / Sensors and Actuators A 183 (2012) 16–21

Fig. 10. DDS system and modulation coil. Fig. 12. Sensitivity of the modulated sensor at 1 Hz.

high, thus facilitating a high slew rate and high sensitivity at low measurement frequencies. Another advantage is the possibility of using the modulation technique in sensor arrays. DC biasing of each sensor in the array will lead to a superposition of the bias fields and thus to distortions in each device. Under modulation, sensors can be driven at different resonance frequencies. Thus the superposition of the modulation fields will not lead to distortions at the devices. Yet another important advantage that should be mentioned is the decrease of sensitivity with respect to mechanical vibrations. At low resonance frequencies undesired mechanical vibrations may increasingly couple into the sensor. This may lead to strong distortions of the output voltage of the piezo phase. However, such low frequency mechanical distortions are not up-converted to the mechanical resonance at a higher frequency with the suggested frequency conversion approach, because they do not affect the magnetic signal but only the low frequency piezo output. 4. Experiment In the experimental setup the modulation signal Bmod was provided by the direct digital synthesizer (DDS) shown in Fig. 10. The numerically controlled oscillator AD9830 from Analog Devices was used. The measurement signal BAC was provided by a function generator HP 33120A. Fig. 11 shows the measured spectrum

Fig. 11. Modulation signal (middle) and up-converted measurement signal (left and right sideband) at the sensor output.

of VME at the sensor output for Bmod = 0.56 mT, fmod = 668 Hz, BAC = 1 ␮T and fAC = 1 Hz. Herein fmod has been chosen in a way that fmod + fAC = fres = 669 Hz. The spectrum was measured with Stanford Research Systems SR785 dynamic signal analyzer. By choosing Bmod = 0.56 mT or Bˆ mod = 0.79 mT, respectively, the output voltage at fmod + fAC reaches its maximum (cp. Fig. 9). The spectrum shows peaks at fmod − fAC , fmod and fmod + fAC . Corresponding to Eq. (7) the signal at fmod + fAC contains all the information about an unknown magnetic field at fAC = 1 Hz and allows a resonance enhanced readout. The corresponding sensitivity under modulation can be calculated from Fig. 11 for VME = 1 mV at fres = fmod + fAC = 669 Hz for BAC = 1 ␮T as shown in Eq. (3): Smod =

1 mV = 1000 V/T 1 T

(14)

In comparison to the original sensitivity of Sres = 1050 V/T for the direct measurement in resonance, it is observed that a resonance enhancement of the sensitivity has occurred also for measurement frequencies far below resonance. To allow a comparison of the modulated and unmodulated ME sensitivity, BAC was subsequently reduced from 10 ␮T down to 10 pT. The corresponding ME output voltage at fmod + fAC was recorded. The modulation signal remained unchanged at Bmod = 0.56 mT and fmod = 668 Hz. Fig. 12 shows the measured sensitivity curve. Fig. 7 already presented the sensitivity of the unmodulated sensor for fAC = 1 Hz. Comparison of Fig. 7 with a √ √ Fig. 12 demonstrates sensitivity level enhancement from 1 ␮T/ Hz down to 1 nT/ Hz by employing the frequency conversion technique. This is equivalent to a sensitivity improvement by a factor of 1000. The new technique allows the utilization of the resonance enhancement of the sensor for arbitrary frequencies. Especially for very low frequencies a sensitivity enhancement is essential if biomagnetic measurements are intended. Nevertheless the modulation technique currently does not yet allow the same sensitivity as for direct measurement in resonance. The reason for this is the undesired occurrence of additional noise under modulation. A noise increase for the modulated case towards resonance can be anticipated from Fig. 11. This additional noise is absent for the unmodulated measurement (Fig. 5) which permits √ the low noise level of 7.1 pT/ Hz shown in Fig. 6. One possible origin is Barkhausen noise but there is no proof for this assumption so far: The modulation signal changes the magnetization of the magnetostrictive material periodically, which leads to a periodic domain wall movement. Due to pinning of the domain walls at

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Institute of Materials Science, Christian-Albrechts-Universität Kiel, for the Kerr microscopy measurement shown in Fig. 13. References [1] R. Jahns, H. Greve, E. Woltermann, E. Lage, E. Quandt, R. Knoechel, Magnetoelectric sensors for biomagnetic measurements, in: Medical Measurements and Applications Proceedings (MeMeA), 2011, pp. 107–110. [2] R. Jahns, R. Knoechel, E. Quandt, Verfahren zur Magnetfeldmessung mit magnetoelektrischen Sensoren, Patent Application DPMA, DE 10 2011 008 866.0, January 18, 2011. [3] S.M. Gillette, A.L. Geiler, D. Gray, D. Viehland, C. Vittoria, V.G. Harris, Improved sensitivity and noise in magneto-electric magnetic field sensors by use of modulated AC magnetostriction, IEEE Magnetic Letters 2 (June) (2011) 2500104. [4] C. Nan, M.I. Bichurin, S. Dong, D. Viehland, G. Srinivasan, Multiferroic magnetoelectric composites: historical perspective, status and future directions, Journal of Applied Physics 103 (031101) (2008) 17–19. [5] H. Greve, E. Woltermann, H.-J. Quenzer, B. Wagner, E. Quandt, Giant magnetoelectric coefficients in (Fe90 Co10 )78 Si12 B10 -AlN thin film composites, Applied Physics Letters 96 (182501) (2010). [6] R. Jahns, H. Greve, E. Woltermann, E. Quandt, R. Knöchel, Noise performance of magnetometers with resonant thin film magnetoelectric sensors, IEEE Transactions on Instrumentation and Measurement 60 (August (8)) (2011) 2995–3001. [7] B. Schiek, I. Rolfes, H.-J. Siweris, Noise in High-Frequency Circuits and Oscillators, Wiley, Hoboken, New Jersey, 2006, pp. 163–172, 235–262.

Biographies

Fig. 13. Domain walls in the magnetostrictive phase.

defects in the material the change in the magnetization occurs as jumps which can have an effect on the sensor output. The domain wall pinning of the investigated sensor was measured by using the magneto-optic Kerr effect. Fig. 13 includes a snap-shot of this measurement and shows strong domain wall pinning. If the additional noise can be reduced it is possible to improve the sensitivity further by two orders of magnitude. 5. Conclusions This paper suggests a novel frequency-conversion technique for magnetoelectric sensors. The proposed technique allows a resonance enhanced measurement of arbitrary input frequencies. For low input frequencies it was shown that the sensitivity can be enhanced by three orders of magnitude compared to the unmodulated case. Currently additional noise impairs the achievement of the same sensitivity as in resonance. Work is in progress to reduce these effects that may have their origin in Barkhausen noise. If the additional noise could be fully suppressed the sensitivity enhancement for an up-converted signal at 1 Hz would be 5 orders of magnitude higher compared to the unmodulated detection of the same signal. Acknowledgments The authors would like to thank the German Science Foundation (DFG) for financial support through the Collaborative Research Centre SFB 855 “Magnetoelectric Composite Materials–Biomagnetic Interfaces of the Future” and Prof. Dr.-Ing. Jeffrey McCord, Department of Nanoscale Magnetic Materials – Magnetic Domains,

Robert Jahns received the Dipl.-Ing. degree in Electrical and Information Engineering from the University of Kiel, Kiel, Germany, in 2009. He is currently working towards the PhD degree at the Chair of Microwave Engineering, University of Kiel. His research interests include magnetic field measurements, magnetoelectric sensors, noise measurements and low noise electronic system design. Henry Greve received his PhD and diploma degrees in materials science from the University of Kiel, Germany, in 2008 and 2003, respectively. Until the end of 2011 he was working as a research scientist in the Group for Inorganic Functional Materials of the University of Kiel. Here, his research and teaching interests included magnetoelectric thin film composites for sensor applications and functional ceramics. Since 2012 he is working for NXP Semiconductors in Hamburg, Germany. Eric Woltermann was born in 1984. He studied Materials Science at the ChristianAlbrechts-University of Kiel, Germany, where he received his diploma in 2009. Until 2011 he was a member of the Collaborative Research Centre 855: “Magnetoelectric Composites - Future Biomagnetic Interfaces” with his research focus on magnetoelectric thin film composites and thin film/micro systems technology. Since 2012 he is working for Robert Bosch GmbH in the automotive industry. Eckhard Quandt received his diploma in physics and his Dr.-Ing. at the Technical University Berlin in 1986 and 1990, respectively. Since 1991 he has worked on thin film smart materials and their applications at the Forschungszentrum Karlsruhe (1991–1999), at the Center of Advanced European Studies and Research (caesar) in Bonn (1999–2006) and at the Christian-Albrechts-Universität zu Kiel (since 2006) where he holds the Chair for Inorganic Functional Materials within the Institute for Materials Science at the Faculty of Engineering. Currently he is Speaker of the Advisory Board of the Deutsche Gesellschaft für Materialkunde (DGM), Speaker of the Research Focus “Kiel Nano Science” of the Christian-Albrechts-Universität zu Kiel, Member of the Materials Science and Engineering Expert Committee (MatSEEC) of the European Science Foundation (ESF), and Speaker of the DFG Collaborative Research Centre SFB 855 “Magnetoelectric Composites – Future Biomagnetic Interfaces”. Reinhard H. Knoechel received the Dipl.-Ing. in Electrical Engineering in 1975, and the Dr.-Ing. in 1980 from the Technical University of Braunschweig, Germany. From 1980 to 1986 he was a principal scientist at the Philips Research Laboratory, Hamburg, Germany. In 1986 he joined the Technical University Hamburg-Harburg, where he was a Full Professor in Microwave Electronics until November 1993. Since December 1993 he holds the Chair in Microwave Engineering with the University of Kiel, Kiel, Germany. Presently he is Dean of the Department. His research interests include active and passive microwave components, ultra-wideband technology, microwave and field measurement techniques, industrial microwave sensors, radar and magnetic field sensors. Dr. Knoechel is a Fellow of the IEEE “for contributions to microwave systems and sensors for industrial process control”.