United States

The real time non-destructive monitoring of stresses and temperature is one of the most demanded solutions in the field of sensor technologies.&lt;br/&gt;One of the most prospective technologies addressing this problem is a novel sensing technique for non-destructive monitoring utilizing ferromagnetic wire inclusions presenting the high frequency magnetoimpedance, MI, effect quite sensitive to tensile stress and magnetic field [1]. One of the advantages of this technology is that proposed free space microwave spectroscopy allows remote monitoring of external stimuli, like stress, magnetic field or temperature.&lt;br/&gt;The glass-coated microwires with typical diameters from 1 to 50 Î¼m can provide new functionalities such as improved mechanical and corrosive properties, adherence with polymeric matrices and biocompatibility [2].&lt;br/&gt;In the present paper a novel sensing technique for direct non-destructive and non-contact monitoring of the composite polymerization utilizing ferromagnetic glass-coated microwire inclusions with magnetic properties sensitive to tensile stress and temperature is described. We provide in-situ studies of the evolution of the hysteresis loop of arrays consisting of Co- rich (Fe&lt;sub&gt;3.8&lt;/sub&gt;Co&lt;sub&gt;65.4&lt;/sub&gt;Ni&lt;sub&gt;1&lt;/sub&gt;B&lt;sub&gt;13.8&lt;/sub&gt;Si&lt;sub&gt;13&lt;/sub&gt;Mo&lt;sub&gt;1.35&lt;/sub&gt;C&lt;sub&gt;1.65&lt;/sub&gt;) microwires during the composites matrix polymerization. We observed remarkable change of the hysteresis loops upon matrix polymerization: remarkable coercivity change and transformation of linear hysteresis loop into rectangular in the arrays with Co-rich microwires placed inside the matrix (see Fig.1a). Using the free space technique we observed considerable variation of the Transmission parameter of the microwires array in the range of 4-7 GHz upon the matrix polymerization (see Fig.1b).&lt;br/&gt;Observed dependencies are discussed considering heating during the matrix polymerization measured using a standard thermocouple (Fig.1c) and the matrix shrinkage and their influence on magnetic properties and MI effect of glass-coated microwires.

MMM 2022

Novel Sensing Technique for Non Destructive Composites Monitoring

The real time non-destructive monitoring of stresses and temperature is one of the most demanded solutions in the field of sensor technologies. One of the most prospective technologies addressing this problem is a novel sensing technique for non-destructive monitoring utilizing ferromagnetic wire inclusions presenting the high frequency magnetoimpedance, MI, effect quite sensitive to tensile stress and magnetic field [1]. One of the advantages of this technology is that proposed free space microwave spectroscopy allows remote monitoring of external stimuli, like stress, magnetic field or temperature. The glass-coated microwires with typical diameters from 1 to 50 Î¼m can provide new functionalities such as improved mechanical and corrosive properties, adherence with polymeric matrices and biocompatibility [2]. In the present paper a novel sensing technique for direct non-destructive and non-contact monitoring of the composite polymerization utilizing ferromagnetic glass-coated microwire inclusions with magnetic properties sensitive to tensile stress and temperature is described. We provide in-situ studies of the evolution of the hysteresis loop of arrays consisting of Co- rich (Fe3.8Co65.4Ni1B13.8Si13Mo1.35C1.65) microwires during the composites matrix polymerization. We observed remarkable change of the hysteresis loops upon matrix polymerization: remarkable coercivity change and transformation of linear hysteresis loop into rectangular in the arrays with Co-rich microwires placed inside the matrix (see Fig.1a). Using the free space technique we observed considerable variation of the Transmission parameter of the microwires array in the range of 4-7 GHz upon the matrix polymerization (see Fig.1b). Observed dependencies are discussed considering heating during the matrix polymerization measured using a standard thermocouple (Fig.1c) and the matrix shrinkage and their influence on magnetic properties and MI effect of glass-coated microwires.

poster

#### Welcome to the 67th Annual Conference on Magnetism and Magnetic Materials, MMM 2022!

The Conference was held from October 31 to November 4 and offers both in-person and on-demand content.

MMM 2022 is sponsored jointly by AIP Publishing and the IEEE Magnetics Society. Members of the international scientific and engineering communities interested in recent developments in fundamental and applied magnetism are invited to attend and contribute to the technical sessions. The technical program will include invited and contributed papers in oral and poster sessions, invited symposia, a tutorial, and several special sessions. This Conference provides an outstanding opportunity for worldwide participants to meet their colleagues and collaborators and discuss developments in all areas of magnetism research.

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This Conference provides an outstanding opportunity for worldwide participants to meet their colleagues and collaborators and discuss developments in all areas of magnetism research.

The amorphous magnetic wires are widely used as magnetic or magneto-mechanical sensors due to their very soft magnetic properties and high sensitivity to stress. [1-4]. A new design of a high sensitivity sensor with high capability to measure applied forces or load is proposed by this paper. The sensor consists in four pieces of high permeability Co68.18Fe4.32Si12.5B15 amorphous magnetic wire, 120 Î¼m in diameter, 20 mm in length, glued prestressed on a pcb board having 0.3 mm in thickness, 7 mm in width and 30 mm in length (Figure 1). The ends of each wire is soldered on the PCB to form a Wheatstone bridge circuit. The opposite arms of the bridge are placed on the same side of the pcb to increase the bridge unbalance when stressed. Also, all wires forming the bridge arms are parallel and close one to another to minimize the effect of the surrounding magnetic field. By using different PCB support for the bridge, it is possible to tailor the sensitivity and force measuring range. A special designed electronic device was built to power the bridge using a high frequency sinusoidal signal and to extract and amplify the unbalanced voltage of the bridge. The dependence of the output voltage/gain versus applied force, for a signal excitation frequency of 1 MHz, is shown is showin figure 2. The sensor shows linear behavior between Â± 0.15N and sensitivity of 43.7 mV/N, without gain, in the linear region. Financial support by the NUCLEU Program (PN 19 28 01 01) is gratefully acknowledged.

Tailorable force sensor based on stress magneto

With the rapid advancement in electronics systems, there is a high demand for components that achieve size, weight, power, and cost reductions (SWaP+C). This need for greater miniaturization has contributed to a dramatic increase in heat generation within these systems, resulting in compromised performance, sacrificed reliability, and reduced device lifecycle.1 In addition, with ever-increasing spectral congestion and since electronic products incorporate faster components operating at higher frequencies than ever before, electromagnetic interference is becoming challenging to mitigate, posing a major concern for human health and the environment.2 It is therefore highly critical to develop high-performance material systems that can concurrently mitigate the detrimental effects of thermal and EM radiation while maintaining the highly desired SWaP+C configurations. To this effect, we have developed an innovative synthesis strategy involving melt blending, vacuum impregnation, and magnetic-field assisted spin coating to fabricate flexible multicomposite films comprising of FeSi particles (~30-50 Î¼m) and graphene nanoflakes (200-300 nm) confined in a shape-stabilized phase change material (PCM) matrix. In this multifunctional material, the PCM enables efficient heat absorption via the phase change process, the graphene flakes enhance the thermal conductivity to facilitate heat dissipation, and the FeSi particles enhance electromagnetic absorption in the X and Ku bands due to their high magnetization and magnetic anisotropy. With the synergistic effect of graphene and FeSi, the resulting composite displays a thermal conductivity of 0.60-0.75 W/mK, latent heat of 110-120 J/g at 70 Â°C, and excellent EM shielding effectiveness (SE) in the range of 10-60 dB depending on thickness in the range 200 Î¼m to 2 mm (an example is shown in Fig 1). Processing-structure-property correlations of the multifunctional films will be discussed in the context of their percolation threshold. Research supported by the Commonwealth Cyber Initiative (Grants HV-2Q22-003 and HV-4Q21-002).

Multifunctional Phase Change Composites for Passive Thermal Management and Electromagnetic Shielding of High Frequency Devices

Positioning systems with high resolution are in a high demand for robotics, operating in a wide scales of positioning ranges from tens of meters in heavy machine industry, down to few nanometers in high-precision electronics. A promising approach for a robust positioning at nanoscale is integration of magnetic field sensors into the positioning electronics and detection of magnetized objects by their induced magnetic fields. In this work, we introduce an approach for magnetic-based positioning, in which the displacement of a magnetized micro-object is detected by magnetic field sensor, as a variation of magnetic field, associated with this displacement. For the purpose to have higher resolution in positioning, magnetic sensor was composed of an array of magnetic tunnel junctions, having magnetoresistance of ~ 170 percent, whereas the geometry of the magnetized object was optimized to have a higher gradient of magnetic field along the positioning direction. The magnet-sensor configuration was optimized as follows: i) magnetization direction in the magnetized object, as well as the displacement direction were varied in respect to field sensing direction of the MTJ sensor, to achieve high linearity of the sensor signal variations with the displacements of the object, ii) the shape of the magnetized object was optimized to improve sensitivity of the MTJ sensor array to positioning displacements of this object, iii) the distance between the MTJ sensor array and the magnetized object was optimized to have largest dynamic range of MTJ output voltage variations, without oversaturating the sensor, iv) the lateral and transversal dimensions of the MTJ sensor array were optimized to improve sensitivity to gradient of magnetic field, induced by the micromagnet. With the optimized configuration the positioning sensitivity of the sensor platform was tested with a micromagnet, placed on a nano-positioning piezo-stage, operating in a closed-loop feedback mode with 10 nm step resolution. The tests in open environment demonstrate robust operation of the magnetic tunnel junction sensor-based platform as a positioning sensor for displacements of magnetized objects with a resolution down to 100 nm.

Magnetic tunnel junctions for positioning systems with down to 100 nm resolution

Airborne particulate matter (PM) have been significantly increasing over the past two decades carrying significant health risks such as premature death, damage to the lungs, heart tissue, and even cancer. PM2.5 is the main concern as it has the most harmful health effects while being more difficult to detect [1]. Moreover, these magnetic nanoparticles are readily absorbed into the bloodstream causing neurodegenerative diseases such as Alzheimerâ€™s and cancerous tumors [2]. Therefore, it is essential to monitor the magnetic portion of PM and its adverse effects on health [3], [4]. This work focuses on developing, modeling, and simulation of a new kind of magnetic sensor that can count and localize these magnetic nanoparticles. Additionally, we have fabricated a novel low-noise and high-precision readout circuit for tunneling magnetoresistive (TMR) array to evaluate the bio-magnetic measurement platformâ€™s suitability for detecting weak bio-magnetic fields. The proposed sensors could help to prevent these nanoparticles from the polluted environment and undoubtedly reduce their adverse risks to humans. The modeled magnetic system consists of a TMR sensor array, a conducting line, and the detected magnetite nanoparticles as shown in Fig. 1(a). The localization and quantization of these Fe3O4 nanoparticles (characterized in Fig. 1(b)) can be achieved by analyzing total output voltages from the TMR sensor array. The Fe3O4 magnetite is injected inside the small closed chamber and they are exerting an external magnetic field that is aligned or opposed to the pinning field, which results in shifting the MTJ curve as seen in Fig. 1(c). After applying a current in the conducting line and creating an external field, the magnetite gets polarized and approaches the MTJ sensors. This technique can detect 50-200 nm magnetic particles compared to existing commercial monitoring solutions that are limited to 1-3Âµm particles.

High performance MTJ

Early cancer detection greatly enhances the prognosis and allows for higher treatment success. Cancer metastasis, which occurs in later stages, is believed to cause more than 90% of cancer-related deaths [1]. In earlier cancer stages, circulating tumor cells (CTCs) may be detected in the blood of cancer patients, which can correlate with patient survival rate. Accurate, non-invasive separation of these cells allows for early detection of cancer and aids in increasing therapeutic efficacy [2]. This work provides an integrated on-chip quantitative cell sorting platform that separates and counts magnetically labeled cells through a microfluidic channel. First, an immunomagnetic assay is utilized to label CTCs with highly selective magnetic nanoparticles. Then, magnetically labeled cells are separated and guided through the microfluidic channel by electromagnetics and ferromagnetic strips [3]. After cell separation, magnetically labeled biomarkers are detected by the magnetic tunnel junction (MTJ) sensor that measures stray fields surrounding the labeled CTCs, generating an electrical signal for each passing particle. Additionally, biomarkers with different sizes, such as CTCs and protein-based cancer biomarkers, can be detected and quantified as they move through the microfluidic channel at different speeds, yielding distinct peaks at the MTJ output [3][4]. This work demonstrates a highly selective platform that actively sorts magnetically labeled biomarkers by combining magnetophoresis-based cell sorting and MTJ-based flow cytometry allowing for highly sensitive quantitative on-chip cell sorting.

On chip Quantitative Cell sorting based on High Performance Magnetic Tunnel Junction

Flow cytometry is a powerful technique that enables cell quantification and analysis. As a result, it has become an essential instrument in biomedical research and clinical testing for disease diagnosis or treatment monitoring. However, the current technique is large and expensive, driving research into smaller, cheaper, and more efficient flow cytometers [1]. One approach to tackle this problem can be with the application of spintronic sensors such as giant magnetoresistance sensors for cell quantification [1][2]. In this work, we report a highly sensitive flow cytometer based on magnetic tunnel junction (MTJ) technology. After external labeling of cells with magnetized beads placed above the MTJ sensor to measure stray magnetic field surrounding the beads. When labeled cells pass through the sensitive area, a signal peak will be generated at the output of the MTJ sensor [3]. Alternatively, magnetic flow cytometers can evaluate the efficacy of certain cancer immunotherapies where cancer cell membranes coat magnetic nanoparticles to activate a specific natural killer (KT) cell response [4]. One of the cytometer applications is Live/dead cancer cells discrimination. This cytometer can detect the presence of these magnetic nanoparticles to ensure proper activation of KT cells and thorough removal of the modified magnetic particles. This result demonstrates a novel MTJ-based, highly sensitive flow cytometer design for quantifying magnetically labeled cells and cancer therapy involving magnetic nanoparticles. Using our suggested device, we can distinguish and separate between cancer cells and prove Live/dead cancer cells discrimination.

An Integrated and Highly Sensitive Magnetic Tunnel Junction based Cytometer

The AC two-pole generator proposed in this study has two forms, one is a non-cover (NC) naked motor, and the other is an iron-based amorphous alloy material as the outer casing of the generator (No Cover, NC). Cover with amorphous slice) for coating. Due to the change of magnetic pole and space magnetic field, different permanent magnet motors have magnetic material shell and no shell structure, as shown in Figure 1. Magnetic field distribution In the demagnetization area, the power and magnetic field changes are tested by order wave analysis and the surface magnetic flux density tester of amorphous materials. The order wave measurement results of different shell shapes can show the magnetic flux density node in the magnetized direction of the demagnetization area. cover. In the experimental measurement of the surface of the amorphous shell, the magnetic flux at the inner and outer center points is about 1.2-2.4 (mT), which is relatively strong, while the magnetic flux distribution at the four corners is about 0.6-1.0 (mT), which is relatively weak. The experimental goal is to set the effect of demagnetization on the electromagnetic parameters, and it is concluded that the permanent magnet salient pole motor has better generator power characteristics in the cladding demagnetization and the magnetic flux distribution of the amorphous shell. In addition, the experiment is also carried out and a local flame is proposed. The annealing process method is used as the coating of the generator and the measurement of the magnetic properties. The experimental verification is that the magnetic flux density of the material surface at the local center point of the high temperature is close to the Curie temperature. The above, but the order wave and power performance of the generator of the flame partial annealing process are poor, as shown in Figure 2.

Electromagnetic Alternators with Composite Amorphous Alloy Housing for Improving Characteristics

1. Study Objective The vibration measurement is mainly used natural frequency and resonance frequency to predict the magnetic device operation status. These categories are the value of the predicted frequency. There are applicable the smart device induced as the motor, transformer, robot integration platform [1]. This common feature is focused the electric motor device where is made by the electromagnetic silicon steel sheet. This study is used the magnetostrictive variation induced by the electromagnetic silicon steel sheet through the exciting power of the current and magnetic field which is to accelerate the vibration and noise variation. It is caused by the excitation of the core and coil. It can intercept the required characteristic signal, analyze the performance of dynamic magnetostrictive of ESS under DC bias and its complex dynamic anisotropy. The motors running under high-frequency conditions cause noise and vibration due to the interaction between magnetomotive forces (MMF) is concerned. 2. Experiment Results and Discussion Regarding to the vibration frequency prediction as a multi-type classification problem, it uses the neural network features of deep learning to combine the input signal, as shown in Figure 1. That is classified into different categories. To use an optimized method with feedforward convolutional neural network, it can predict the frequency and analyze the AC and DC vibration frequency of the power motor and the non-fixed periodicity of the mechanical robot arm belong to different spectrum models. The sound pressure level is related to the sound intensity level (SIL). The conversion of voltage signal, current signal, and time domain and frequency domain FFT. As shown in Figure 2, to predict the vibration and sound module by using artificial intelligence method, it is verified the operating system through by measurement, numerical analysis and optimal calculation of NN method to identify the vibration and noise of the motor.

A New Approach to Identify the Motor Vibration and Noise Dependent on Harmonic and FFT Transform

This paper proposes the transmission and identification of energy sensing signals for IoT smart vehicles. The article proposes two research structures, including deep learning to detect abnormal sound signals of vehicle motors. The Internet of Things technology to collect vehicle sensing signals upload to the cloud system. A new approach of tunable FOPID (fractional-order proportional-integral-derivative) fuzzy controller for reduction of power losses on electric vehicle, which saving energy included as the AC generator, supercapacitors and Li-ion battery charging device etc., is proposed as shown in Figure 1. The energy consumption for power inverter, AC generator, transformer and supercapacitors battery was calculated. A modified switching pulse width-modulation (PWM) inverter, which a generator with signal AC/DC inverter FOPID controller is performed. A deep learning neural network method to solve motor unformal signal is proposed. Long short term memory (LSTM) have a higher accuracy of intercepting motor noise than conventional machine learning methods. Additionally, the disadvantage of deep learning algorithms is that they require large datasets to ensure an efficient performance. In this study, a combination of CNN and LSTM is proposed to prevent failure cause by the motor anomalous noise. This is applied to the CNN for noise image feature material. In addition, the LSTM is combined with the actual noise measurement spectrum data between 40 Hz â€“ 20 kHz to analyze the noise of the motor. The CNN-LSTM can be effectively analyzed substantial anomalous motor noises. This approach yields a reduction in the switching losses and an improvement in the converting efficiency evidenced by the numerical data, as shown in Figure 2. Finally, experimental results also show that FOPID with fuzzy controller in saving energy can improve power loss, compared with that of conventional PID controller around 35%.

Prediction of Abnormal Noise and Harmonic of Electromagnetic Motor on Electric Vehicle

I. Introduction Hybrid-excited (HE) machine and fault-tolerant (FT) machine have attracted wide attention due to their several advantages, such as easy adjustment of air-gap magnetic field, high power density and high efficiency in wide speed range of HE machine, and reliability of FT machine [1]-[2]. Nowadays, multi-tooth field modulated (MTFM) machines have become a research hotspot thanks to their capability of sufficiently utilizing harmonics to promote the average output torque [3]. In this paper, to apply the advantages of HE machine and FT machine to MTFM machine, a novel hybrid-excited fault-tolerant multi-tooth field modulated (HEFT-MTFM) machine is proposed. The topology of proposed machine is shown in Fig. 1. To have lower demagnetization risk, parallel-hybrid-excited structure is adopted in the machine. II. Electromagnetic Performance The electromagnetic performances of HEFT-MTFM machine are presented in Fig. 2. It can be seen that regulating the magnitude of air-gap field by excitation windings can change the magnitudes of flux linkage, back-EMF and electromagnetic torque, and keep flux linkage and back-EMF good sinusoidal and also keep the magnitude of cogging torque and torque ripple small. In terms of the fault-tolerant capability, It can be observed from Fig. 2 (e) that the self-inductance of HEFT-MTFM machine is larger than that of traditional fault-tolerant field modulated machine by same motor size. Overall, the proposed HEFT-MTFM machine exhibit good flux regulation capability, sinusoidal flux linkage and back-EMF, small cogging torque and torque ripple, short-circuit current restrained capability due to high self-inductance and magnetically isolated capability due to low mutual-inductance. The operation principle, machine optimization and more detailed performances including the loss of PMs and operation efficiency will be further discussed in the full paper.

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