France



&lt;i&gt;Introduction&lt;/i&gt;&lt;br/&gt;Rogowski coils (RC) are used for the measurement of large alternating current, particularly as a short circuit detector in electric substations. Another application is in electricity meters. A regular, air-core RC cannot be saturated and therefore its dynamic range is limited only by noise voltage and supply voltage of the accompanying integrator or ADC [1]. An RC used for precise current measurement should have a consistent cross-sectional area and turn-to-turn spacing, limiting the winding arrangement to a single layer. The sensitivity of such coils is poor, causing a low signal-to-noise ratio [2].&lt;br/&gt;Our proposed design adds a low-permeability ferromagnetic core to improve the sensitivity and thus reduce the required number of turns. Ferromagnetic core has been already tested for different types of RC, e.g. self-integrating RCs which are used for measurement of short current pulses. In this case increasing the core permeability decreases the low frequency limit of self-integrating operation [3]. Contrary to that, our target application is precise current sensing at the mains frequency and its harmonics. Such a sensor should be able to work with high accuracy (typical requirement is 0.5% or 0.2%) in the nominal range, as well as above this range with reduced accuracy with partly saturated core as a fault current detector [4]. Because the coil does not require a load resistor on its winding, there is no concern about overheating during overload conditions.However, there are some open questions, how will the ferromagnetic core affect the frequency characteristics of the RC, its ability to suppress external currents and resistance against the position deviations of the measured (primary) conductor.&lt;br/&gt;Several different materials, either in the form of a finished toroidal core or a 3-D printer filament filled with magnetic particles were tested, both theoretically by a FEM simulation and practically by measurement.&lt;br/&gt;&lt;br/&gt;&lt;i&gt;FEM Simulation&lt;/i&gt;&lt;br/&gt;We have made a series of 3D FEM simulations to evaluate the effect of the core permeability on rejection of external currents and position of the measured conductor. In both cases the perfectly homogenous coil would be absolutely immune against both these influences. Practical coil always has uneven winding density, in particular between the first and last turn [5]. Also the cross-sectional area of individual turns varies slightly. We simulated the role of these imperfections in crosstalk from an external conductor as a function of its position and core permeability. In general, the error is diminishing with increasing permeability due to demagnetization effect. However, for practical permeability of 20 the error reduction is only very small (from 0.23 % to 0.15 %). The permeability effect on the resistance against the position deviations of the measured (primary) conductor is even lower and for permeability of 20 it is negligible. The effect of nonuniformity of the core permeability along its circumference was found to be insignificant as well.&lt;br/&gt;&lt;br/&gt;&lt;i&gt;Samples used for measurement&lt;/i&gt;&lt;br/&gt;The first batch of test specimens (labeled A, B, C) are toroidal powder cores with an outer diameter of 79 mm and rated relative permeability of 26 (Kool Mju and Sendust materials) or 14 (Sendust). The winding is electrostatically shielded by a copper adhesive tape, care was taken to avoid the creation of a short-circuited turn.&lt;br/&gt;We also tested 3D printed cores from two types of plastic filament filled with magnetic particles and for the full paper we plan to test resin-based cores of various sizes.&lt;br/&gt;&lt;br/&gt;&lt;i&gt;Measurement procedure&lt;/i&gt;&lt;br/&gt;Two important sensor characteristics were measured: linearity and frequency response. Test current was provided by a Techron 7548 power amplifier with an additional step-down transformer. Reference current measurement was done by a LEM Ultrastab current sensor (IT60S for frequency response, IT1000S for linearity). Two different measurement approaches were tested: either integrating the induced voltage with a Lakeshore 480 fluxmeter in AC mode, or measuring the voltage directly with a HF2LI lock-in amplifier. Both methods give similar results in amplitude, but the phase can only be measured by a lock-in amplifier. A primary conductor with a loop length of 10 meters was passed once through the measured coil to minimize the influence of the return current.&lt;br/&gt;Fig. 1 shows the frequency dependence: there is no observable sensitivity drop due to frequency dependence of the permeability. The sensitivity increase at high frequencies is due to the resonance with parasitic coil capacitance and its amplitude could be reduced by a parallel damping resistor [6] at the expense of heat being generated in the associated circuitry.&lt;br/&gt;Fig. 2 shows the measured linearity error at 93 Hz, which is in a good agreement with the catalogue values of permeability vs. flux density in the core. A nominal flux line length of 0.196 m was used to convert flux density to primary current.&lt;br/&gt;&lt;br/&gt;&lt;i&gt;Conclusion&lt;/i&gt;&lt;br/&gt;We have demonstrated that adding a ferromagnetic core to a RC of the classical dI/dt type is beneficial for its sensitivity, which would allow the design of very precise RCs for lower currents. The RC linearity is decreased, but remains acceptable for most applications. The amplitude error caused by self-resonance can be reduced by standard methods such as a damping resistor, or by using a different material with high core loss.&lt;br/&gt;&lt;br/&gt;&lt;i&gt;Acknowledgement&lt;/i&gt;&lt;br/&gt;This study was supported by the Grant Agency of the Czech Republic within the Nanofluxgate project (GACR GA20-27150S).

**References:**

[1] S. Tumanski, &lt;i&gt;Meas. Sci. Technol.&lt;/i&gt; 18, p. R31, 2007&lt;br/&gt;[2] J. D. Ramboz, &lt;i&gt;IEEE Trans. Instrum. Meas.&lt;/i&gt; 45, p. 515, 1996.&lt;br/&gt;[3] J. D. Zhu, Q. G. Zhang, J. B. Jia&lt;i&gt; et al.&lt;/i&gt;, &lt;i&gt;Plasma Sci. Tech. &lt;/i&gt;8, p. 457l, 2006.&lt;br/&gt;[4] L. A. Kojovic, M. T. Bishop, and D. Sharma, &lt;i&gt;IEEE Trans. Ind. Appl.&lt;/i&gt; 49, pp. 8, 2013.&lt;br/&gt;[5] L. Ferkovic, D. Ilic, and R. Malaric, &lt;i&gt;IEEE Trans. Instr. Meas. &lt;/i&gt; 58, p. 122, 2009.&lt;br/&gt;[6] M. H. Samimi, A. Mahari, M. A. Farahnakian&lt;i&gt; et al.&lt;/i&gt;, &lt;i&gt;IEEE Sens. J. &lt;/i&gt;15, p. 651 (2015).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/b316cd355ace0c3db4ef22e26ec8fa2a.jpg)
Fig. 1 Frequency response

![](https://assets.underline.io/uploads/markdown_image/1/image/fd59bddadd4847af0a850bbd099da4d6.jpg)
Fig. 2 Linearity

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 Rogowski Coil with Ferromagnetic Core

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Introduction Rogowski coils (RC) are used for the measurement of large alternating current, particularly as a short circuit detector in electric substations. Another application is in electricity meters. A regular, air-core RC cannot be saturated and therefore its dynamic range is limited only by noise voltage and supply voltage of the accompanying integrator or ADC [1]. An RC used for precise current measurement should have a consistent cross-sectional area and turn-to-turn spacing, limiting the winding arrangement to a single layer. The sensitivity of such coils is poor, causing a low signal-to-noise ratio [2]. Our proposed design adds a low-permeability ferromagnetic core to improve the sensitivity and thus reduce the required number of turns. Ferromagnetic core has been already tested for different types of RC, e.g. self-integrating RCs which are used for measurement of short current pulses. In this case increasing the core permeability decreases the low frequency limit of self-integrating operation [3]. Contrary to that, our target application is precise current sensing at the mains frequency and its harmonics. Such a sensor should be able to work with high accuracy (typical requirement is 0.5% or 0.2%) in the nominal range, as well as above this range with reduced accuracy with partly saturated core as a fault current detector [4]. Because the coil does not require a load resistor on its winding, there is no concern about overheating during overload conditions.However, there are some open questions, how will the ferromagnetic core affect the frequency characteristics of the RC, its ability to suppress external currents and resistance against the position deviations of the measured (primary) conductor. Several different materials, either in the form of a finished toroidal core or a 3-D printer filament filled with magnetic particles were tested, both theoretically by a FEM simulation and practically by measurement. FEM Simulation We have made a series of 3D FEM simulations to evaluate the effect of the core permeability on rejection of external currents and position of the measured conductor. In both cases the perfectly homogenous coil would be absolutely immune against both these influences. Practical coil always has uneven winding density, in particular between the first and last turn [5]. Also the cross-sectional area of individual turns varies slightly. We simulated the role of these imperfections in crosstalk from an external conductor as a function of its position and core permeability. In general, the error is diminishing with increasing permeability due to demagnetization effect. However, for practical permeability of 20 the error reduction is only very small (from 0.23 % to 0.15 %). The permeability effect on the resistance against the position deviations of the measured (primary) conductor is even lower and for permeability of 20 it is negligible. The effect of nonuniformity of the core permeability along its circumference was found to be insignificant as well. Samples used for measurement The first batch of test specimens (labeled A, B, C) are toroidal powder cores with an outer diameter of 79 mm and rated relative permeability of 26 (Kool Mju and Sendust materials) or 14 (Sendust). The winding is electrostatically shielded by a copper adhesive tape, care was taken to avoid the creation of a short-circuited turn. We also tested 3D printed cores from two types of plastic filament filled with magnetic particles and for the full paper we plan to test resin-based cores of various sizes. Measurement procedure Two important sensor characteristics were measured: linearity and frequency response. Test current was provided by a Techron 7548 power amplifier with an additional step-down transformer. Reference current measurement was done by a LEM Ultrastab current sensor (IT60S for frequency response, IT1000S for linearity). Two different measurement approaches were tested: either integrating the induced voltage with a Lakeshore 480 fluxmeter in AC mode, or measuring the voltage directly with a HF2LI lock-in amplifier. Both methods give similar results in amplitude, but the phase can only be measured by a lock-in amplifier. A primary conductor with a loop length of 10 meters was passed once through the measured coil to minimize the influence of the return current. Fig. 1 shows the frequency dependence: there is no observable sensitivity drop due to frequency dependence of the permeability. The sensitivity increase at high frequencies is due to the resonance with parasitic coil capacitance and its amplitude could be reduced by a parallel damping resistor [6] at the expense of heat being generated in the associated circuitry. Fig. 2 shows the measured linearity error at 93 Hz, which is in a good agreement with the catalogue values of permeability vs. flux density in the core. A nominal flux line length of 0.196 m was used to convert flux density to primary current. Conclusion We have demonstrated that adding a ferromagnetic core to a RC of the classical dI/dt type is beneficial for its sensitivity, which would allow the design of very precise RCs for lower currents. The RC linearity is decreased, but remains acceptable for most applications. The amplitude error caused by self-resonance can be reduced by standard methods such as a damping resistor, or by using a different material with high core loss. Acknowledgement This study was supported by the Grant Agency of the Czech Republic within the Nanofluxgate project (GACR GA20-27150S).

**References:**

[1] S. Tumanski, Meas. Sci. Technol. 18, p. R31, 2007 [2] J. D. Ramboz, IEEE Trans. Instrum. Meas. 45, p. 515, 1996. [3] J. D. Zhu, Q. G. Zhang, J. B. Jia et al., Plasma Sci. Tech. 8, p. 457l, 2006. [4] L. A. Kojovic, M. T. Bishop, and D. Sharma, IEEE Trans. Ind. Appl. 49, pp. 8, 2013. [5] L. Ferkovic, D. Ilic, and R. Malaric, IEEE Trans. Instr. Meas. 58, p. 122, 2009. [6] M. H. Samimi, A. Mahari, M. A. Farahnakian et al., IEEE Sens. J. 15, p. 651 (2015).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/b316cd355ace0c3db4ef22e26ec8fa2a.jpg)
Fig. 1 Frequency response

![](https://assets.underline.io/uploads/markdown_image/1/image/fd59bddadd4847af0a850bbd099da4d6.jpg)
Fig. 2 Linearity

poster

1. INTRODUCTION The non-destructive testing technology is appropriate to inspect high-priced product because it can inspect while maintaining the shape of the structure. And as the structure of the inspection body becomes complex and diversified with the development of the industrial society, the demand for non-destructive inspection is increasing mainly in developed countries. These techniques investigate structures of inspection by detecting energy deformation caused by the defects or constitution of products using specific physical energy to the target. Depending on the type of energy used for investigation, non-destructive testing is divided into technologies such as magnetic-particle testing, eddy-current testing, ultrasonic testing, radiation transmission testing, liquid-penetration testing and is applied to a wide range of application such as automobiles, nuclear power, steel structures, and pipelines [1]. Oil and gas pipes are mostly buried underground, so it is necessary to regularly manage corrosion or internal defects in pipes. Non-destructive testing is mainly used for safe long-distance transportation of oil and gas, among which Eddy-Current Testing (ECT), which does not have direct contact with the test object, is widely used. In ECT, operating frequencies have a significant impact on detecting faults. Traditional ECT mostly operates within the frequency range of a few kHz to MHz [2]. When the following high frequencies applied at the structure of the inspection, there is some difficulty to detect defects under pipe because eddy current does not flow to the bottom of the pipe due to the skin effect. In order to compensate for these limitations, the industry recently started to use the Magnetic Eddy Current technique that combines the principle of eddy current testing and magnetic flux leakage testing. The principle of this technology is based on the change in the pipe permeability due to defects by applying a certain amount of magnetic flux to the pipe using a permanent magnet or an electromagnet. In this technique, the magnetic flux used here does not need to go to the saturation point like MFL. In general, the magnetic field size required for MFL is at least 10 KA/m, but in MEC, a magnetic field of 3 KA/m is sufficient [3]. In the MEC technique, the value of magnetization level applied to the structure of the inspection has a significant influence on the defect determination performance. If the magnetic field is too small, it is impossible to determine the defects on the outer part of the pipe, and if the magnetic field is too large, defects of various sizes cannot be distinguished. Therefore, it is important to properly apply magnetic flux to the pipe so that defects can be found with high resolution in a given driving condition and the defect position can be distinguished. However, it has not been long since MEC technology has been introduced and researched, so there are insufficient papers on what driving conditions the sensor should operate under for optimal defect detection performance. For this reason, in this paper, a study was conducted to compare the defect detection performance according to the applied magnetic field point and to find the optimal applied magnetic field under a given driving condition. In order to analyze the distribution of the magnetic field around the defect according to the applied magnetic field value, a 3D model is set as shown in Fig.1-(a) and analyzed using 3D FEM. The defect underneath the pipe increases the density of magnetic flux in the pipe, thereby the permeability of pipe decreases and the impedance of the coil changes accordingly to generate a defect signal. The thickness of the defect used in the simulation is fixed at 1.5mm, which is 30% of the pipe thickness, and the diameter of the defect is fixed at 20mm. The value of magnetic field applied within the pipe was changed by changing the current value using an electromagnet. Fig.1-(b) show the respective magnetic field point of the pipe when 1A, 2A, 3A, 4A current is applied to the electromagnet coil. When a current of 1A is passed, it is difficult to determine the defects outside the pipe due to the large permeability value, and at 3A and 4A, the magnetic field applied to the pipe reaches almost saturation and the magnetic permeability is close to 1, making it inappropriate for detection of various size of defects. However, at 2A, it has a permeability, which is the middle value of the previous values, so it can detect various size of defects. Thus, using MEC techniques allows optimal defect detection performance at lower magnetic flux than MFL. In order to compare the defect detection performance in a real situation according to the applied magnetic field value, a prototype was made as shown in Fig.2-(a) and the experiments were conducted to verify compare to the simulated values. As shown in Fig.2-(b_Above), a specimen with artificial defects was produced and an actual MEC driving experiment was conducted. The specimens consist of defects of 10%, 30%, and 50% depth of the pipe thickness, where the solid line represents the external defect of the pipe and the dotted line represents the internal defect of the pipe. And defects werer detected by using coils as shown in Fig.2-(b_Below). The setting and procedures of experiments and the discussion of the results will be covered in the manuscript.

**References:**

[1] Seung-Seok Lee, Ki-Bok Kim, Journal of the korean society for nondestructive testing, vol. 24, pp. 64-85 (2015) [2] K.Reber, A.Boenisch, Stefanie Asher, PPSA Seminar in Scotland, pp.1-12 (2015) [3] Mohd Aufa Hadi Putera Zaini, Mohd Mawradi Saari, Nurul Ain Nadzri, 2020 11th IEEE Control and System Graduate Research Colloquium(ICSGRC 2020), Malaysia, pp.1-4 (2020)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/77bba74437caf3ebf9387a3d20c9fd21.jpg)
Fig. 1. (a) MEC simulation models. (b) Magnetic field points according to the applied magnetic flux.

![](https://assets.underline.io/uploads/markdown_image/1/image/f9a621e0e02b8adcb115167ec3f92c7a.jpg)
Fig.2. (a) MEC prototype. (b) specimen with artificial defects(Above) and MEC coil(Below).

 Selection of Applied Magnetic Field for Optimal Detectability in Eddy Current Testing with DC bias

Introduction Induction hardening treatment is used for a variety of steels because of its short hardening time and ability to hardened steel with complex shapes. In this research, the non-destructive inspection method for the hardened depth in surface of the induction hardened steel plate by an electromagnetic sensor is investigated. The hardened depth in surface of the steel plate is measured by detecting the difference in the permeability and the conductivity between the hardened and the non-hardened layers inside the steel plate by the electromagnetic sensor [1,2]. On the other hand, the detection signal in the electromagnetic sensor is also affected by the changing in the distance (Lo: Lift-off) between the surface of the induction hardened steel plate and the sensor. Therefore, the method for simultaneously measuring the surface hardened depth in the hardened steel plate and the lift-off is proposed. The model and the evaluation method Fig.1 shows the 1/2 region of the proposal inspection model for detecting the surface hardened depth in the surface hardened steel plate of SCM440 steel material. The proposal electromagnetic sensor is consisted of an electromagnetic yoke made of laminated silicon steel plate, an alternating excitation coil, and two types of detection coils. The z-direction of the flux density (Bz) inside the magnetic yoke is detected by the z-direction detection coil on one leg of the yoke, and the x-direction magnetic field distributed (Bx) between the two legs of the yoke is detected by the x-direction detection coil. Since the permeability and conductivity in the hardened layer are lower than that of the non-hardened layer, the flux density in the x- and z- direction of these detection coils is changed when the hardened depth is changed. However, even if the depth of the hardened layer is constant, their detected magnetic flux in these detection coils is changed when the lift-off is changed. Therefore, both the lift-off and the surface hardened depth are estimated by the Bx and Bz. 3-D electromagnetic FEM considering the nonlinearity of magnetic properties The flux density and eddy current inside the surface hardened steel plate are calculated by 3-D nonlinear finite element method (FEM) taking account of the initial magnetization curve and conductivity of the hardened and non-hardened layers in the steel. In an induction hardened steel plate, there is an intermediate layer called a heat-affected zone between the hardened and non-hardened layers. Therefore, in this analysis, the initial magnetization curves and conductivity inside the intermediate layer are calculated by linear interpolation of the initial magnetization curves and conductivity of the hardened and non-hardened layers. Measurements results and estimates Fig.2 shows the obtained values of Bx and Bz in the two detection coils when the hardened depth (D) and Lo are changed, respectively. This figure denotes that if Lo is constant, Bx is increased and Bz is decreased when D is increased. This is, because the flux density Bz inside the magnetic yoke is decreased, and the Bx distributed between both feet of the yoke is increased, since the permeability and conductivity in surface domain of the steel plate is decreased when the D is increased. On the other hand, if D is constant, Bx is increased and Bz is decreased when Lo is increased. This is, because the flux density Bz in the closed magnetic path between the sensor and the steel plate is reduced when the Lo is increased, and the magnetic flux Bx distributed between both feet of the yoke is increased. The figure shows that the signals of Bx and Bz due to the changes of D and Lo are distinguished. Therefore, Both D and Lo are inspected by the linear interpolation using measured Bx and Bz. Table I shows the interpolated results of D and Lo using the Bx - Bz plane of Fig.2. The measured values are almost in agreement with the obtained ones. The table illustrates that both D and Lo can be detected from the Bx and Bz in two detection coils. Conclusions The results obtained are summarized as follows: (1)It is possible to estimate the depth (D) of surface hardened steel plate by detecting the change of flux density in two detection coils due to the difference of the permeability and the conductivity in the steel with and without hardened layers. However, the flux density detected by the search coil is influenced by the change of both lift-off and depth of surface hardened steel. (2)The flux density (Bx) in the detection coil of x-direction is increased and the flux density (Bz) in the detection coil of z-direction is decreased when the surface hardened depth (D) of the induction hardened steel or the lift-off (Lo) are increased. However, the signals of Bx and Bz in two detection coils due to the changes of D and Lo are distinguished. Therefore, it is possible to inspect the D of the surface hardened steel without the influence of Lo by detecting both the Bx and Bz of two detection coils in the proposed inspection sensor.

**References:**

[1] Y.Gotoh, S.Onita, T.Horino, and Y. Misaka,” Detecting Method of Hardened Depth in Surface Hardened Steel by Magnetic Field on Steel”, IEEE Transactions on Magnetics, vol.54, no.11, Article Sequence Number:6202404, 2018. [2] Y.Gotoh, K.Sakurai, N.Takaoka, Y.Misaka, K.Kawasaki, and N.Takahashi,” Proposal of Electromagnetic Inspection Method of Hardened Depth of Steel using 3-D Nonlinear FEM Taking Account of Hysteresis”, IEEE Transactions on Magnetics, vol.47, no.10, pp.3546-3549, 2011.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/e862db6def1a56d0093f74acb2e22a85.jpg)
Fig.1. Proposal inspection model (x-z plane 1/2 region).

![](https://assets.underline.io/uploads/markdown_image/1/image/c3974039805ce679ad07cfffd241dc00.jpg)
Fig.2. Experimental results for magnetic flux density (Bx,Bz) at each hardened depth (D) and lift-off (Lo). 
 
Table 1. The interpolated results of D and Lo.

 Proposal of Inspection Method for Lift-Off and Surface Hardened Depth of Induction Hardened Steel Plate Using by Alternating Magnetic Field

In recent years, the non-destructive inspection (NDI) method based on the eddy-current (EC) effect is increasingly playing an important role in many applications. The advancement in the EC NDI techniques with the miniature magnetic field sensors enables the size estimation of small magnetic particles and the detection of deep-lying defects, such as cracks, metal loss, and other mechanical damages, in highly conductive metals. Several solutions of the field-detection based EC NDI have been developed based on the combination of an excitation coil and magnetic sensors such as Hall, giant-magnetoresistance (GMR), or superconducting quantum interference device (SQUID) sensors. The high-sensitivity and cost-effect solutions are the technique with GMR sensors, which are suitable for many different applications, including the defect evaluation in the related industries [1]-[3] and the electronic compass in consumer electronics [4]. The reliability and capability of GMR sensors for defect detection have been demonstrated by using the eddy-current probe with packaged GMR sensor arrays [2] or a single chip having double-coil excitation [3]. However, the usage of the GMR sensor with a big excitation coil is not suitable for the applications for which the space for scanning the probe is small. Furthermore, the linear arrangement of elements in the array [3] makes it suitable only to the specimen with a flat surface. Further improvement in the design of the GMR EC probe should be made to enhance the sensitivity and accuracy in flaw characterization. In this work, we proposed a novel design of miniature differential EC probes consist of a GMR bare-die sensor and a tiny coil. The schematic diagram for the high spatial resolution GMR EC probe is shown in Fig. 1. This probe consists of a tiny excitation coil with a small feature size of less than 3 mm. The GMR sensor is the GF708 bare die from Sensitec GmbH. The chip layout is a Wheatstone bridge circuit with four spin-valve magnetoresistance elements, as shown in the inset of Fig. 1. The sensitivity of the two active elements, R1 and R2, are enhanced by the soft magnetic flux concentrator films, while the two reference elements, R0, are shielded by the same soft magnetic films. The output voltage of the GMR bridge sensor can be expressed as: Vab = Vcc{R0/[R(H)+R0]-R(H)/[R0+R(H)]} (1) where R(H) is the transfer curve modeled as a hyper-tangent function of the magnetic field H on R1 and R2 [4]. The GMR chip is 1 mm in width and 1.4 mm in length, and the sensing axis is along the width of the chip. It is mounted on the edge of a printed circuit board (PCB). A special aluminum wire bonding technique is developed to connect the terminals of the GMR sensor onto both sides of the PCB. With this technique, the distance from the chip surface to the sample surface can be reduced to within 0.2 mm. The sensor surface is perpendicular to the PCB and parallel to the sample surface. The sensing direction of the GMR chip is parallel to the specimen surface and perpendicular to the vertical excitation field. With this arrangement, the GMR chip acts like a gradiometer sensitive to the gradient of the defect field. The miniature chip-and-coil assembly and the short lift-off distance effectively enhance the spatial resolution in flaw detection with the GMR EC probe. To test the spatial resolution in the detection of the defect signal, the sample was placed on the translation stage controlled by the 08TMC-2 motor controller from Unice E-O Services Inc. To scan for the simulated defect in the sample. The GMR EC probe is driven by a 100-kHz sine wave voltage provided by a function generator. The differential output of the probe is measured by a low noise preamplifier and transmitted to the lock-in amplifier to analyze the amplitude and phase of the EC signal. The spatial distribution of the signals was digitized in real-time by a data acquisition (DAQ) module USB-6216 from National Instruments and recorded by the computer. An in-house developed C# program is used to set the scanning range, velocity, and step size as well as to receive the eddy-current signal taken by the DAQ device. The experiment is performed on an aluminum plate with machined slots to simulate the cracks of different depths of 0.1, 0.3, 0.5, 1.0, 1.5 and 1.8 mm and the same width of 0.2 mm. The B-scan image with a lift-off distance of 0.2 mm between the probe and the specimen is shown in Fig. 2. It can be seen that the cracks on the aluminum plate are detected and the position of cracks coincides with the change in the in-phase (Re) and quadrature (Im) of the output voltage (Vout). The amplitude for the integration of Vout over the spatial coordinate x is roughly proportional to the depth of cracks. The full width at half maximum of each peak near the crack is less than 2 mm, which has achieved the physical limit set by the lateral size of the probe. The phase plot shows that all of the surface cracks deeper than 0.1 mm can be clearly identified. The result shows that the developed EC probe is suitable for the quantitative evaluation of the geometrical characteristics, such as shapes, sizes and positions of the machined defects on the metallic sample, with a high-spatial resolution. This work is supported by the Ministry of Science and Technology of Taiwan under Grant Nos. MOST108-2221-E992-083MY2 and MOST 107-2221-E-992-094.

**References:**

[1] D. Rifai, A. N. Abdalla, K. Ali, & R. Razali, “Giant magnetoresistance sensors: A review on structures and non-destructive eddy current testing applications”, Sensors, 16(3), 298 (2016). [2] O. Postolache, A. L. Ribeiro, and H. G. Ramos, “GMR array uniform eddy current probe for defect detection in conductive specimens”, Measurement, 46(10), 4369-4378 (2013). [3] Andrea Bernieri, Luigi Ferrigno, Marco Laracca, and Antonio Rasile, “Eddy Current Testing Probe Based on Double-Coil Excitation and GMR Sensor”, IEEE Transactions on Instrumentation and measurement, vol. 68, no. 5, pp. 1533 – 1542(2019). [4] V. S. Luong, Y.-H. Su, C.-C. Lu, J.-T. Jeng, J.-H. Hsu, M.-H. Liao, J.-C. Wu, M.-H. Lai, C.-R. Chang, “Planarization, Fabrication and Characterization of Three-dimensional Magnetic Field Sensors”, IEEE Transactions on Nanotechnology, Vol. 17, no. 1, pp.11 - 25 (2018).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/8d751ab27f3f29e4e77bb5ac9747b6a8.jpg)
Fig. 1. High spatial resolution GMR EC probe.

![](https://assets.underline.io/uploads/markdown_image/1/image/695ad452874753af7b4e1e084e179870.png)
Fig. 2. The integral phase for the output voltage of EC probe when scanning on the aluminum plate.

 High spatial resolution flaw detector based on the GMR eddy-current probe

Energy sources used in industries, such as gas and oil, are mainly transported through buried pipes. If an energy source leaks out from the pipe due to corrosion or cracks, an accident such as an explosion may occur, so it is very important to periodically inspect the buried pipes. Since cracks have the risk of the pipe being torn, it is important to look for cracks in pipe inspection. There are several methods for inspecting buried pipe, such as ultrasonic testing(UT), and magnetic flux leakage testing(MFL). UT method is often used for various inspections including pipe inspection due to their very high accuracy, but has the disadvantage of slow inspection speed and high battery consumption. Buried pipes are connected up to tens to hundreds of kilometers at a time, so long-distance inspections are required for pipe inspection. UT, which has a slow inspection speed and high battery consumption, has limitations in the inspection of buried pipes. On the other hand, the MFL method using MFL sensors has little battery consumption except for the power used for the sensor, the inspection speed is relatively fast, and the defect detection accuracy is high. However, because the width of the crack is very narrow, the crack in the same direction as the magnetic field direction hardly affects the flow of magnetic flux, and there is almost no leaked magnetic flux due to the crack in the same direction as the magnetic field direction. That is, conventional MFL inspection devices such as axial MFL(AMFL) and circumferential MFL(CMFL), which allow magnetic flux to flow in only one direction in the pipe, hardly find cracks in the same direction as the magnetic flux direction[1]-[2]. Fig.1 is here Conversely, if the MFL inspection device is used to allow magnetic flux to flow in various directions in the pipe, it has the advantage of MFL method and can find all cracks regardless of direction. This paper proposes an MFL inspection device that allows magnetic flux to flow through a pipe in various directions and can find all cracks regardless of the direction. Fig. 2 shows the comparison of the magnet placement and magnetic flux direction of the AMFL, CMFL, and the proposed MFL inspection device. Fig.2 is here As shown in Fig. 2(a) and (b), the magnetic flux flows only in the axial and circumferential directions of the conventional MFL inspection devices, AMFL and CMFL, respectively. In contrast, the proposed MFL inspection device arranges the magnets differently from the conventional MFL inspection device, so that the magnetic flux flows in the diagonal and circumferential directions. When the magnetic flux flows through the pipe in two directions using the proposed MFL inspection device, the cracks in the circumferential direction can be detected at the section where the magnetic flux flows in the diagonal direction, and the cracks in the diagonal direction can be detected at the section where the magnetic flux flows in the circumferential direction. In other words, even if there are cracks that can’t be found in the section where the magnetic flux flows in a specific direction, the cracks can be found in the section where the magnetic flux flows in the other direction. As a result, all cracks can be found regardless of the direction using the proposed MFL inspection device. The reason why the MFL method can’t find cracks in the same direction as the magnetic flux direction and details of the proposed MFL inspection device will be covered in full paper.

**References:**

[1] M. Rostami Kandroodi, B. Nadjar Araabi, and M. Nili Ahmadabadi, in IEEE Transactions on Magnetics, Vol. 53, No. 3, pp.1-10(2017) [2] H. M. Kim, C. G. Heo, and G. S. Park, in IEEE Transactions on Magnetics, Vol. 54, No. 11, pp.1-5(2018)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/6f08173f80a8dda7a8b08465cc9ce367.jpg)
Fig. 1. The magnetic flux leakage pipe inspection devices. (a) AMFL[1] (b) CMFL[2].

![](https://assets.underline.io/uploads/markdown_image/1/image/6b2c2db6cf2e1625096560ac4a8f79c2.jpg)
Fig. 2. The magnet placement and the magnetic flux direction of (a) AMFL. (b) CMFL. (c) the proposed MFL inspection device.

 Inspection Device Using MFL Sensors for Buried Pipe Inspection to Find all Cracks Regardless of Direction

Magnetic flux leakage (MFL) testing is a widely used method for detection of defects such as the metal loss due to the corrosion in steel bars located in reinforced concrete. The magnetic flux leak caused by the defect is then measured by a magnetic sensor, which gives information to the user of the presence of the defect [1]. For small defects, it is difficult for the sensor to determine the presence and location of the defects. Therefore, we propose a gradiometer measurement setup [2] using highly sensitive magnetic tunnel junction (MTJ) sensors, which is based on the tunnel magnetoresistance (TMR) effect, to increase the magnitude of the measured signal. In this work, 2 MTJ sensor modules were used to measure a gap of 0.1 mm between two steel bars (diameter = 20 mm, length = 500 mm). The length of the overall specimen is 1000 mm, where the gap is at the 500 mm mark (touching point of the two steel bars). The MTJ sensor modules consist of each sensor connected in a full-bridge circuit [3]. The signal is then passed through an amplifier circuit and low pass filter to further reduce noise in the measured signal. A robot is then used to move the sensor along the steel bars at a speed of 50 mm/s, measuring the magnetic flux signal. The lift-off value for the overall measurement is set at 50 mm. Before each measurement, the steel bars are magnetized using a solenoid (approximately 1.52 mT). A planar gradiometer setup was used, whereby the MTJ modules are placed in the same x-axis. The effect of the baseline (b), the distance between the first and second MTJ sensor module, was investigated (b = 50, 100, 150, 200 mm). From the results, the overall magnitude of the gradiometer sensor signal showed an increase, almost twice as large as the single sensor module signal (Figure 1). Furthermore, the gradiometer sensor signal produced a single peak response (gap is right above the peak), in contrast to the single sensor signal which produced a sine-like wave response (gap is between the peak and trough) (Figure 2). This is helpful in terms that the location of the gap can be determined in real time. For the estimated gap location, a loss in accuracy was observed in all the signals, with the most accurate location determined for b = 100 mm. We demonstrated that a planar gradiometer setup consisting of 2 MTJ sensors could improve the overall signal value of the measurement setup resulting in an easier way to determine the location of a 0.1 mm gap at 50 mm lift-off. The results obtained from this research are expected to contribute to the further application of MTJ sensors not only in MFL testing but in other fields of magnetic-based non-destructive testing. This work was partly supported by the Center of Innovative Integrated Electronic Systems (CIES) and the Center for Spintronics Research Network (CSRN). The sensors were provided by Mr. Kosuke Fujiwara from Spin Sensing Factory (SSF).

**References:**

[1] Hirose. M, Maeda. T, Matsuda. K, Yokota. M, Hattori. A, and Miyagawa. T, J. Stru. Eng., 58A, p.867-878 (2012). [2] W. Dehui, S. Lingxin, W. Xiaohong, and L. Zhitian, J Nondestruct Eval., 36, p.24 (2017). [3] J. Cao, and P.P Freitas, J. Appl. Phys., 107, 09E712 (2010).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/3227474d3e22de78e908e4d2ba9a7a6b.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/74835cefbcae5c802089d4aa85ecad44.jpg)

 Detection of Gap in Steel Bars by Magnetic Tunnel Junction Sensor Gradiometer based Magnetic Flux Leakage Testing Method

Non-destructive testing(NDT) is a method that detects discontinuous boundaries or defects that exist inside and outside of pipes without damaging or destroying pipe[1]. The magnetic flux leakage(MFL) method, one of the most representative NDT methods, uses permanent magnets to saturate the ferromagnetic pipe by applying a large magnetic field to the pipe and measure the leakage magnetic flux signal around the defect. Because the MFL signal contains information about the size and shape of the defect, an algorithm can be created to estimate the shape of the defect through analysis[2]-[3]. In general, many studies on non-destructive testing, including the MFL method, mainly focus on detecting defects or cracks in pipeline. However, not only defects but also metal objects outside the pipe affect the condition of the pipe. When external metal contact with the pipe wall, corrosion is more prone to the metal contact area on the pipe. In addition, pipes used in industry are coated with thick plastic to block contact with oxygen or external metal, However, the external metal damages the plastic coating. If a hole is made in the plastic coating of the pipe due to external metal, it is more prone to corrosion by contacting the pipe with oxygen as well as the external metal. Therefore, it is necessary to study not only defects but also detection of metal existing outside the pipe. Analysis of external metals requires research not only to prevent corrosion but also to prevent theft of energy sources in pipes such as oil and gas. People who steal energy sources eventually drill holes in pipes through which the energy source flows, and use metal pipes to steal the energy source. Metal pipe for theft can eventually be found through external metal analysis, so analysis of external metal also helps prevent theft of energy sources. Because the MFL method uses a large magnetic field, it is easier to detect and analyze external metals than other NDT methods. Fig.1 is here This paper analyzes the MFL sensor signals according to the shape and distance of external metal around underground pipeline, and presents an algorithm that estimates the shape and the distance of the external metal to the pipe using the MFL sensor signal. Fig. 2 shows the magnetic flux and the magnetic flux density distribution when there is a defect or external metal, respectively. Fig.2 is here When a defect occurs in the pipe, the cross-sectional area through which the magnetic flux passes decreases, and the magnetic flux flowing through the pipe leaks out of the pipe. In other words, when a defect occurs in the pipe, the magnitude of the signal detected by MFL sensors increases. Conversely, when external metal contacts the pipe, the cross-sectional area through which the magnetic flux passes increases, and the amount of magnetic flux leaking out of the pipe decreases. That is, when external metal contacts the pipe, the magnitude of the signal detected by MFL sensors decreases. In addition, like defects, when the shape or distance of the external metal changes, the size or shape of the signal detected by the MFL sensors also changes. As a result, the shape and distance of the external metal can be estimated by applying the signal change tendency and the defect shape estimation algorithm[2]-[3].

**References:**

[1] M. Rostami Kandroodi, B. Nadjar Araabi, and M. Nili Ahmadabadi, in IEEE Transactions on Magnetics, Vol. 53, No. 3, pp.1-10(2017) [2] H. M. Kim, C. G. Heo, and G. S. Park, in IEEE Transactions on Magnetics, Vol. 54, No. 11, pp.1-5(2018) [3] H. M. Kim, and G. S. Park, in IEEE Transactions on Magnetics, Vol. 50, No. 2, pp.109-112(2014)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/2b20fbd5d4eb98b21e434495c17d02dc.jpg)
Fig.1. Photographs of external metal and pipes

![](https://assets.underline.io/uploads/markdown_image/1/image/3c45be0487083f6756301fe5aa5bacd7.jpg)
Fig.2. Distribution of magnetic flux density around (a) the defect. (b) the external metal. Diagram of magnetic flux line around (c) the defect. (d) the external metal.

 A Study on the Estimation of the Shapes and Distance of External Metal around Underground Pipeline Using Magnetic Flux Leakage Sensors

Temperature measurements are vital in laboratory and industry settings. For that reason, many different measurement methods exist. Common temperature sensors are based on thermistors, resistance temperature detectors, thermocouples, semiconductors and fiber optics. Optical sensor technologies possess advantages for electrical measurements and analysis in high voltage applications like monitoring in smart grids, ranging from several Hz to some kHz in frequency. In general, in such systems current measurements are based on sensing the magnetic field generated by the electric current rather than the current itself. By this, possible electric hazards are eliminated, and a natural galvanic separation is built into the sensing system. Optical magnetic field or direct current measurement systems have been realized through fiber-optic current sensors, based on an optical fiber around a current conductor1, bulk magnetic garnet materials2, or single or stacked garnet thin films3. We demonstrate magnetooptical measurement schemes based on the Faraday effect for relating magnetic and micromagnetic features to magnetic field, electrical current and temperature4. For that, we use magnetooptical active only micrometer thin iron garnet film. The garnet film has a large Verdet constant (Faraday effect) together with a low absorption coefficient. The magnetooptical Faraday effect sensitivity of the magnetooptical indicator film is 1.8°/mT at room temperature. The polarimetric magnetooptical read-out is realized in a non-contact optical arrangement. For the measurements, the magnetic state of the garnet sensor is modulated through a low noise current amplifier and the magnetooptical response signal is acquired through a lock-in amplifier. The thin film sensor element has the ability for high sensitivity magnetic field and naturally electrical current sensing capabilities over a many magnitudes of field and current. High-resolution magnetic field sensitivities down to the nanotesla regime are demonstrated as shown in Fig. 1. For the micrometer thick garnet films we demonstrate a magnetic field detection limit of better than 20 nT/Hz0.5 and an electrical current detection limit of 3 mA/Hz0.5. These values are achieved over several orders of magnitude of magnetic field frequencies into the kHz regime. The magnetooptical response at small magnetic field amplitudes originates from small magnetic angle rotations inside the magnetic domain walls. Different schemes for the measurements of temperature are evaluated. In all cased the range of application is defined by the Néel temperature of the sensing garnet material5. Exemplary results of temperature sensing based on variations in the magnetic domain wall susceptibility with temperature, from analyzing the resulting magnetooptical signal amplitude in a magnetic modulation field, are shown in Fig. 2. Temperatures are derived with high accuracy of 0.1°C across a wide temperature range. Overall, we propose and demonstrate a multimode magnetooptical temperature sensor relying on combined magnetooptical Faraday effect amplitude variations with the related physical properties. The sensing range spans many orders of signal amplitude and a wide frequency range with equal sensitivity and a limit of detection. Temperatures are derived with high accuracy across a wide temperature range. The measurement schemes can be extended to the use of other magnetic sensing materials. These include ferromagnetic and ferromagnetic films with lower or higher Néel temperatures or Curie temperatures. The magnetooptical sensor allows for measuring magnetic field, direct electrical current, and temperature without electrical connection and will therefore be especially useful in applications requiring resistance to electrical noise. This work was funded by the German Research Foundation (DFG) through grant no. MC 9/20-1.

**References:**

 1. R. Silva, H. Martins, I.Nascimento et al., Applied Sciences, Vol. 2, p. 602-628(2012) 2. B.J.H. Stadler, and T. Mizumoto, IEEE Photonics Journal, Vol. 6, p.1-15(2014) 3. A. Garzarella, M.A. Shinn, and D.H. Wu, Appl. Phys. Lett., Vol. 108, p.241101 (2016) 4. F. Klingbeil,S. D. Stölting and J. McCord ,Appl. Phys. Lett.,(under review) 5. M. Kustov, R. Grechishkin, M. Gusev et al, Adv. Mater., Vol. 27, p.5017 (2015)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/ffc2beb949bb793dba35dd1aff13a879.jpg)
Fig. 1 Exemplary limit of detection plot for a base-to-peak magnetic field Hac amplitude with a frequency of fH = 1110 Hz.

![](https://assets.underline.io/uploads/markdown_image/1/image/ae6308b2c378f5878afb9133bee9a314.jpg)
Fig. 2 Magnetooptically measured temperature derivation with varying temperature. The inset shows the corresponding change of the magnetooptical signal amplitude versus a thermocouple temperature used for calibration.

 Multimodal Magnetooptic Sensing of Magnetic Field, Electric Current and Temperature

Due to their special features such as low background noise, high sensitivity, and the possibility of nanoscale fabrication, magnetoresistive (MR) sensors present a great interest for the scientific community, being used especially in biomedical applications [1]. Among MR sensors, those based on tunnel magnetoresistance (TMR) effect exhibit the highest magnetoresistance value, higher sensitivity, and lower power consumption [2, 3]. However, shortcomings as weak linearity in the variation of electric resistance with the applied magnetic field, high coercive field, or quite complicated fabrication process, make the TMR sensors less investigated for biosensing applications. The purpose of this work is to develop a model of TMR based sensor, with small size and high sensitivity, capable of real-time detection of magnetic particles, with possible applications in the detection of magnetic particles from tissues in hyperthermia. The operation of the sensor will be done without magnetic flux concentrators or permanent magnets, therefore no additional steps in the technological process are required. In order to obtain a TMR structure with high values of magnetoresistance and sensitivity, the thicknesses of the component layers were optimized reaching the final configuration: Ta (5 nm)/Ru (20nm)/Ta (5 nm)/CoFe (3 nm)/IrMn (20 nm)/CoFe (2.5 nm)/Ru (0.85 nm)/CoFeB (3 nm)/MgO (1.8 nm)/CoFeB (3 nm)/Ta (10 nm). The thin layers were deposited on Si/SiO2 support (18 x 18 mm2), using the ATC 2200 / AJA International deposition system, which allows both magnetron sputter deposition and electron beam evaporation. Excepting the MgO barrier layer, which was deposited by electron beam evaporation, all other thin layers were obtained by magnetron sputter deposition at a working pressure of 3 mTorr. To induce an in-plane easy axis in the ferromagnetic layers, a magnetic field (100 Oe) parallel to the plane of the thin films, was applied during the deposition. As a detection element, we proposed a structure with a low aspect ratio in the shape of a cylindrical pillar with 4 µm diameter. The total size of each device (sensor and contacts) is 400x250 μm2, as depicted in Fig. 1(a). These small dimensions allow the fabrication of 100 sensors onto single support of 18x18 mm2, leading to a simplification of the technological process. In the first step of the sensor microfabrication, rectangular structures of 40x80 μm2 (Fig. 1(b)) were patterned by e-beam lithography, then ion beam milling and removing of e-resist. The detection element (pillar) and contact surfaces, were defined by electron beam lithography and ion beam milling. In order to passivate the lateral sides of the pillar, 60 nm of insulating layer (SiO2) was sputter-deposited, then the resist and SiO2 from the top of the pillar and contact surfaces were removed by lift-off technique. For measurements, the CPP (“current perpendicular to plane”) configuration was used by passing the electric current perpendicular to the plane of the thin layers. For this step, the electrical contacts with coplanar waveguide geometry (ground-signal-ground), were defined by laser beam lithography followed by Ta (10 nm)/Cu (200 nm) deposition and then lift-off. The coplanar waveguide geometry consists of a middle pad which is the signal strip and two lateral pads that are used as ground lines. The middle pad is connected to the top of the pillar and the two outer pads are connected to the bottom part of the pillar. After microfabrication, TMR sensors were annealed at a temperature of 320 °C in an external magnetic field of 5 kOe, in the direction of anisotropy induced during the deposition. For the as-fabricated TMR sensor, we obtained a magnetoresistance value of 37.5 % and 0.26 %/Oe for the sensitivity. In order to test the TMR sensor, detection experiments were performed using FeCrNbB magnetic particles with a diameter of 50-500 nm obtained by high-energy ball milling from melt-spun ribbons (MSRs) precursors [4]. The magnetic nanoparticles were dispersed in cyanoacrylate adhesives in order to obtain solutions with concentrations of 20 % and 80 %. Then, a glass support was partially covered with these solutions and used to demonstrate the detection capability of the MR sensor. During the measurements, a magnetic field of 20 Oe was applied perpendicular to the direction of the sensor, in order to generate a dipole magnetic field of magnetic particles. The output voltage variation was measured for different concentrations of magnetic particles. As shown in Fig. 2, an output voltage variation of 0.044 mV was obtained for a magnetic particles concentration of 20 %. Increasing the particles concentration to 80%, the variation of the sensor output voltage also increased to 0.161 mV. We demonstrated a dependent relationship between the sensor output voltage and the concentration of magnetic particles. It should also be noted that the values of electrical resistances remain constant over time, indicating the stability of the sensor. Acknowledgment This work was supported by the Romanian Ministry of Research and Innovation (MCI) under the NUCLEU programme, Project PN 19 28 01 01.

**References:**

[1] D. Su, K. Wu, R. Saha et al., Micromachines, Vol. 11, p. 1 (2020) [2] D. D. Djayaprawira, K. Tsunekawa, M. Nagai et al., Applied Physics Letters, Vol. 86, p. 092502-1 (2005) [3] S. Cardoso Freitas, D. C. Leitao, L. Gameiro et al., Microsystem Technologies, Vol. 20, p. 793 (2014) [4] H. Chiriac, N. Lupu, M. Lostun et al., Journal of Applied Physics, Vol. 115, p.17B520-1 (2014)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/8bc6653b5ea2fe219e2b8925ce30340c.jpg)
Fig. 1. (a) Optical microscope image of a device with G-S-G type electrical contacts and (b) SEM image of a rectangular structure.

![](https://assets.underline.io/uploads/markdown_image/1/image/1b121658e4c6ea5578969a74a9676632.jpg)
Fig. 2. Real-time signal of the TMR sensor for different magnetic particles concentrations.

 Tunnel Magnetoresistance Sensors for Real-Time Detection of Magnetic Nanoparticles

The aerospace industry has become increasingly reliant on carbon fibre composite (CFC) as a structural component in aircraft, due to his strength to weight ratio. One of the disadvantages of CFC are their vulnerability to impact damage and external environment changes during flight, which causes barely visible damage to the structure. One solution to this is structural health monitoring (SHM), which monitors the composite structure to provide early detection for damage. Previous work has found that magnetostriction ribbons used as sensors have good resolution to detect damage but are time consuming to attach to the composite surface [1]. To solve this issue, research has focused on additive layer manufacturing to produce 3D printed sensors, which can be directly attached to the surface of the composite. To evaluate the magnetic performance of the 3D printed sensors, this project focused on the design and development of 3D printed magnetostrictive materials using computer simulations in parallel with experimental research to measure the magnetic and mechanical performance. The design of the magnetostrictive sensors was simulated using COMSOL multiphysics, to determine how design parameters such as thickness, track length and gap changed the magnetic response with and without applied force. A desktop bound metal deposition printer at the Royce Translational Centre, was then used to print the metal with a polymer binder (polypropylene) to create the chosen 3D structures (Fig 1). The magnetic material chosen for this work was stainless steel 17/4ph. The initial work assessed the current performance of the printer at each stage. The designed structure goes through two stages of printing and heat treatment processes. The development of the feedstock to the heat treated structure could affect the final performance of the magnetostrictive material. For example, after printing the printed part (green body) goes through a debinder and a sintering stage which ultimately changes the microstructure and allows grain growth, which could affect the saturation magnetisation magnitude and direction. Using a MPMS3-SQUID magnetometer, in-plane magnetisation hysteresis loops were measured of different track lengths taken from structures at the different processing stages (green body and sintering). The results show that there is an increase in saturation magnetisation from green body to sintered sample. The sintered sample showed isotropic magnetisation within the track while the green body showed an anisotropic magnetisation. This may be due to the homogenous grain growth. To evaluate the grid design performance as a strain sensor, a weight was applied to the sintered structure and the change in magnetic flux density was measured. The COMSOL simulations were used to validate the results by using the in-built magnetostriction module. Both simulations and experimental works show comparable results (Fig 2). Demonstrating the larger the track gap the larger the response to an applied force. Future work will explore a range of printable magnetostrictive materials such as nickel and magnetite. The work will explore different designs based on COMSOL simulations including mechanical and magnetic performance. Acknowledgements: We wish to acknowledge the Henry Royce Institute for Advanced Materials, funded through EPSRC grants EP/R00661X/1, EP/S019367/1, EP/P02470X/1 and EP/P025285/1, for the financial support and the Desktop Metal Studio+ system and MPMS3-SQUID access at The University of Sheffield.

**References:**

[1] Z. Leong, W. Holmes, J. Clarke, A. Padki, S. Hayes, and N. A. Morley, IEEE Trans. Magn., 55, 7, 1–6, 2019.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/623f74f02e43c68a9449a77427f35558.jpg)
Fig 1. Additive manufacture sintered samples with track gap of 1.5mm, 3mm and 5mm (left to right)

![](https://assets.underline.io/uploads/markdown_image/1/image/d026f6ebdbd80cd984b1658195b9c6b0.jpg)
Fig 2. Comparison of COMSOL model and experimental data

 Modelling magnetostrictive materials for structural health monitoring of carbon fibre composite

A growing interest in electric vehicles challenges soft magnetic materials to improve efficiency and power density. Metal amorphous nanocomposites (MANCs) have lower coercivities and eddy current losses, allowing for greater efficiency and higher switching frequency. The later allows for high motor speeds and improved power density. However, commercially available and laboratory demonstrated MANCs have shortcomings. Fe-based MANCs, such as FINEMET have excellent magnetic properties, but mechanical properties limit their application in high speed electric motors (HSMs). Fe-Co based MANCs, such as HITPERM, have high saturation inductions and good mechanical properties, but elevated magnetostrictive losses. Co-based MANCs and more recent Fe-Ni based MANCs have low losses and good mechanical properties, but lower saturation inductions (1-1.2 T), that limit power density in HSMs. Recently, much work has explored improving saturation induction in MANCs by increasing the content of magnetic elements, which comes at the cost of glass-forming ability (GFA). These efforts where generally limited to trial and error testing. Additionally, all work to date has focused on Fe-based alloys. In this work, a method of using Thermocalc simulation to locate near-eutectic compositions has been applied to Fe-Ni based alloys. Minima in liquidus temperature and solidification range were found for a ternary composition range and used to identify compositions that retain good GFA as the percentage of magnetic elements is increased. The (Fe70 Ni30)x(B-Si-Nb)100-x alloy system for x=82% and x=85% was explored by Thermocalc simulations. This is an increase in magnetic element content compared to previously developed x=80% alloys. 3 compositions in the x=82% system, and 1 alloy in the x=85% system where identified and successfully cast as amorphous ribbon. The amorphous nature of the ribbon was confirmed by a bend test and XRD. Magnetic testing was performed by PPMS to measure saturation induction and Curie temperature of the amorphous material. The Curie temperatures increased to 407-438 °C for the x=82% alloys, and 462 °C for the x=85% alloy. Saturation induction increased to 1.28-1.36 T for the x=82% alloy and 1.48 T for the x=85% alloy, which is a significant improvement over the ~370 °C Curie temperature and 1.2 T saturation of previous Fe-Ni alloy. Crystallization behavior was studied by XRD for the x=85% alloy, showing that crystallization process follows a 2-step process of Amorphous → BCC+FCC+Amorphous → BCC+FCC+Fe3B+Fe23B6. Post annealing magnetic properties were studied by strip testing, and saturation induction as high as 1.48 T was seen after optimal annealing. TEM was used to study structure of as cast and annealed material. 2 alloys with x=82% compositions were identified with an optimal crystalline size of 10-20 nm, while the x=85% alloy had this structure in the as cast state. This opens the possibility of using the alloy in the as cast state, without requiring annealing. In conclusion, alloys with good GFA and improved magnetic properties were identified by Thermocalc simulation.

**References:**

 N. Aronhime, V. DeGeorge, V. Keylin, JOM. 69 (2017) 2164–2170 N. Aronhime, E. Zoghlin, V. Keylin, Scr. Mater. 142 (2018) 133–137 J.M. Silveyra, A. Leary, V. DeGeorge, J. Appl. Phys. 115 (2014) 17A319 J.M. Silveyra, P. Xu, V. Keylin, J. Electron. Mater. 45 (2015) 219–225 A. Urata, H. Matsumoto, S. Sato, J. Appl. Phys. 105 (2009) 2007–2010 C. Wang, A. He, A. Wang, J. Pang, Intermetallics. 84 (2017) 142–147 A. Wang, C. Zhao, A. He, J. Alloys Compd. 656 (2016) 729–734 Y. Krimer, N. Aronhime, P. Ohodnicki, J. Alloys Compd. 814 (2020) 1-9

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/1be95150355009fb148c6d8dd5009eca.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/46a90665e7662989fbfe624a29693a8d.png)

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