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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.&lt;br/&gt;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.

MMM 2022

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

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.

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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Please register for the MMM 2022 conference to join the event.

This Conference provides an outstanding opportunity for worldwide participants to meet their colleagues and collaborators and discuss developments in all areas of magnetism research.

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.

A Novel Fault Tolerant Multi

I. Introduction Flux-switching permanent-magnet (FSPM) machine has been received much attention due to its advantages of high torque density and easy heat management, etc. [1]. In order to enhance the torque/power capability, FSPM machine with multi-tooth structure (MFSPM) has been proposed [2]. However, not only high power density but also high reliability and good fault-tolerance capability are required for PM machine and hence three novel fault-tolerant MFSPM (FT-MFSPM) machines are proposed in this paper based on the MFSPM machine in [2]. The topologies of proposed machines are shown in Fig. 1. To increase the torque density, a new outer rotor FT-MFSPM (Model I) shown in Fig. 1 (a) is proposed based on [2]. To further increase the output torque, a middle PM is added in each dummy slot (Model II) as shown in Fig. 1 (b). Employing more PMs is an effective method to improve the toque without consuming the operating energy and thus the dual PM modulated FT-MFSPM machine (Model III) is proposed and shown in Fig. 1 (c). II. Performance comparisons The electromagnetic performances of three FT-MFSPM machines are presented in Fig. 2. It can be seen that though Model III exhibits the highest value of flux linkage, back-EMF and electromagnetic torque, it also exhibits the highest value of cogging torque and torque ripple and the most distorted back-EMF. In terms of the fault-tolerant capability, it can be observed from Fig. 2 (e) that the self-inductance of Model I and Model II is almost the same, which is higher than that of Model III. Overall, Model II is superior to Model I and Model III since Model II has greater output torque and smaller torque ripple than Model I with a few increase of PMs and has greater short-circuit current restrained capability due to higher self-inductance and smaller torque ripple with less PMs. The machine optimization and more detailed comparisons including the losses and efficiency will be further discussed in the full paper.

Comparative Analysis of Three Novel Fault Tolerant Multi

Permanent magnet synchronous motors (PMSMs) having high power density and high efficiency are rigorously researched in various premium applications. Among PMSMs, many studies have been conducted on interior permanent magnet synchronous motors (IPMSMs) to improve torque ripple [1-3], but its accurate estimation is not straightforward. Therefore, a six-pole nine-slot IPMSM is adopted as a base model due to its popularity in academia and industries. Other two pole/slot combinations (8p/12s, 10p/15s) having the same winding factor of 0.866 are additionally selected to investigate mainly the influence of a pole/slot combination on torque performance. Air gap force is separated into its radial and tangential components, and the tangential force density (Ft) is determined by two magnetic flux densities in air gap [4]. Due to proportional relation between Ft and the torque [4], torque performance is easily identified by analyzing. In case of maximum and minimum torque at the instant of tmax and tmin, respectively, the distribution of Ft along air gap is illustrated in Fig. 1 to analyze torque ripple. The biggest gap between Ft(Î¸m, Ï‰tmax)and Ft(Î¸m, Ï‰tmin) as indicated in red and blue, respectively, occurs around the right side of a stator pole surface as shaded in yellow in case of anticlockwise rotation. Since Ft is proportional to the product of Br and Bt [4], magnetic flux densities in air gap have to be examined to analyze the variation of Ft. The moment of maximum torque is given in Fig. 2, and it is noted that the change of Bt in increasing a pole number is much greater than that of Br. Compared to Bt of 6p/9s, in particular, that of 10p/15s is significantly reduced by 46% around the right side of a stator pole, and hence, torque ripple is improved in the 10p/15s combination. In conclusion, in varying pole and slot numbers, the impact of Bt is dominant on torque ripple. Especially, the change of Br and Bt with respect to a pole/slot combination will be meticulously analyzed and explained in terms of its reason and relationship with torque ripple.

Torque Analysis of a Permanent Magnet Synchronous Motor using Flux Densities in Air Gap

The increase of power density in permanent magnet synchronous motors(PMSMs) has been getting more crucial these days, and there are two methods to improve the power of a PMSM. One is the increase of magnetic loading(ML) by changing the grade and/or size of permanent magnets [1]. The other is the change of electric loading(EL) by modifying winding design and/or current [2]. ML and EL leading to magnetic flux density in air gap affect electromagnetic and mechanical performance at the same time. Thus, Balance between ML and EL should be examined in terms of efficiency and vibration. In this paper, a sixteen-pole eighteen-slot PMSM for a vertical articulated robot is chosen as a reference model [3], and other two pole/slot combinations (20p/18s, 20p/24s) are together compared in terms of electrical and mechanical performance. In the electric motor, electromagnetic vibration is generated by air gap radial force(Pr) whose density is determined by radial and tangential magnetic flux densities. At a given instant of time, the flux densities are spatially distributed along air gap with respect to mechanical angle, and their spatial distribution changes by spinning the rotor. Pr distributed in a three-dimensional manner is decomposed into harmonics as Fig.1. In the case of 16p18s, the 16th radial force is dominant on the x-axis of a temporal harmonic order. Regarding the y-axis of a spatial harmonic order, the 2nd and 16th are important. The vibration displacement is calculated by the harmonics of Pr as Fig.2. At the frequency of 533.3Hz, the RMS of vibration acceleration of the 16th temporal order on the x-axis is 1.14m/s2, and the 2nd and 16th spatial harmonics have the portion of 83% and 9%, respectively, in vibration acceleration. The influence of ML and EL on the radial force density of the 2nd and 16th spatial harmonics is significantly different each other. In conclusion, balance between magnetic and electric loading has to be examined in terms of efficiency and vibration. Especially, trade-off between efficiency and vibration will be meticulously analyzed and explained during the increase of power in PMSMs.

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