The use of time-varying magnetic field sources is indispensable in numerous applications, such as magnetic resonance imaging, sensors, motors, actuators, magnetometers or magnetic
refrigerators. Halbach cylinders have been used as an alternative to electromagnets, since they have no losses by the Joule effect. However, rod mangle systems are cheap and promising
alternatives to the currently used Halbach cylinders [1-3]. The use of rotation patterns has potential for application in several innovative áreas [4].
In this work, we modeled rod mangle structures with different number of rods, aiming to control the magnitude, direction and homogeneity of the magnetic field. Figure 1 (a) shows the
modeled system for 3 rods. After determining the configuration with the maximum magnetic flux density at the center of each system, it was possible to generate a homogeneous magnetic
field. The homogeneity increases with the number of rods and for a large number of rods, the rod mangle structure begins to resemble an ideal Halbach. We also analyzed two different
rotation patterns to generate a decreasing magnetic field over time. For the first pattern only the direction of the magnetic field of the odd configurations remained constant. For the second
rotation pattern, after the magnetic field is reduced to zero, it starts to increase in the opposite direction and then decreases to zero again. If we rotate all rods counterclockwise, the
magnetic field will rotate clockwise, keeping the magnitude fairly constant. Finally, we validated the results experimentally with structures of 3 and 4 rods (Fig 1 (b)). 

**References:** 

[1] J. M. D. Coey, Permanent magnet applications, Journal of Magnetism and Magnetic Materials 248 (3) (2002) 441–456. 
[2] O. Cugat, P. Hansson, J. M. D.Coey, Permanent magnet variable flux sources, IEEE Transactions on Magnetics 30 (6) (1994) 4602–4604. 
[3] F. Hiptmair, Z. Major, R. Haßlacher, S. Hild, Design and application of permanent magnet flux sources for mechanical testing of magnetoactive elastomers at variable field directions,
Review of Scientific Instruments 86 (8) (2015) 085107. 
[4] H. Sakuma, T. Nakagawara, Optimization of rotation patterns of a mangle-type magnetic field source using covariance matrix adaptation evolution strategy, Journal of Magnetism and
Magnetic Materials 527 (2021) 167752. 

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Rod mangle rotation patterns for magnetic field generation

Magnetorheological fluids (MRFs) can change their viscosity in response to applied magnetic field. Magnetorheological energy absorbers (MREAs) are being investigated for adaptive shock isolation because MREAs can adjust their stroking load to severity of impact when magnetic field is used to control MRF viscosity. Employing MRFs in MREAs requires a highly stable suspension to maintain a uniform concentration, because MREAs would be used only in the event of an impact or crash event, that is, rarely. Suspension stability of MRFs can be studied using an automated vertical axis inductance monitoring system (AVAIMS), where an inductance sensor is translated vertically along a column of MRF to measure particle concentration as a function of column height and time [1,2]. The AVAIMS allows for tracking discontinuities in density or shocks including: the mud-line (boundary between the topmost supernatant (clear fluid) zone and the original concentration zone), the gel-line (boundary between the original concentration zone below mud-line and variable concentration zone), and the cake-line (boundary between the variable concentration zone and the sediment zone at the bottom of the column). MRF sedimentation can be evaluated comprehensively analyzing these boundaries. The AVAIMS developed here (Fig. 1) seeks to improve sedimentation zone boundary localization using an optimized inductance sensor to measure concentration gradient as a function of time. The inductance sensor design, material selection, and geometry were optimized and permalloy and plastic were used advantageously to improve sensor sensitivity. The calibration curve of the sensor was obtained by measuring samples with different particle volume fractions. The sensor design was validated by examining a uniformly mixed MRF column for seven consecutive days after preparation of an MRF with an Fe solids loading of 20 vol%. These tests show that the AVAIMS developed here was able to better localize sedimentation zone boundaries using concentration gradient profile method (Fig. 2).

Sedimentation of Magnetorheological Fluids Measured Using a Automated Vertical Axis Inductance Monitoring System

Magnetorheological fluids (MRFs) consist of micron-sized magnetic particles dispersed in a carrier fluid for which rheological properties can be tuned reversibly with
magnetic field.1 If an MRF is contained in a cellular elastomeric encapsulant (CEE), its mechanical properties, such as stiffness and damping, can be controlled via magnetic field. Such
tunability can be exploited for adaptive vibration control or energy absorption systems. A magnetorheological damper often uses an accumulator to modulate pressure injected by external
forces applied to the damper.2 An accumulator is implemented into the cellular encapsulant to enable essentially incompressible fluid to enter the accumulator and to allow compression of
the cellular material to take place, and also enables a mechanical bulge stiffness to the design.
Here, MRF was prepared with silicon oil (40% vol. fraction). Thermoplastic polyurethane (TPU) was 3-D printed as the CEE system. (Fig. 1 a). The MRF was injected into the TPU-CEE,
followed by the printing of a sealing layer. The wall adjacent to the sealing layer had a circular opening and a TPU membrane was bonded to its perimeter so that the pressurized MRF
could flow through the opening and be accumulated in the resulting pocket.
An external magnetic field (0 and 7 kG) was applied along the sample longitudinal axis at the time of uniaxial dynamic testing with 5% pre-strain. The TPU-CEE samples were
characterized via force-displacement tests at 1 Hz under strain amplitudes. The MR effect on the dynamic stiffness is defined as the ratio of the dynamic stiffness under the maximum
magnetic field to the dynamic stiffness in the absence of a magnetic field. Dynamic stiffness in the presence as opposed to the absence of magnetic field was 264%. (Fig.2a) The area of the
force-displacement curve of the system with an accumulator is about 41% greater than one without an accumulator. The accumulator enhanced the increase in damping (Fig. 2b). The
increase in damping capacity generally increased as strain amplitude increased. 

**References:** 

1. Ashtiani M, Hashemabadi SH, Ghaffari A. A review on the magnetorheological fluid preparation and stabilization. Journal of Magnetism and Magnetic Materials. 374, 716.
(2015) 
2. Yu, Jianqiang & Dong, Xiaomin & Wang, Xuhong & Pan, Chengwang & Zhou, Yaqin. Asymmetric Dynamic Model of Temperature-Dependent Magnetorheological Damper and
Application for Semi-active System. Frontiers in Materials. 6. 227. (2019) 

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Development of Magnetorheological Fluids within 3D Printed Elastomeric Cellular Structures with an Accumulator

Most research on remotely driven magnetic micro-robots focuses on their manipulation within fluids [1]. Actuating their motion in soft media and living tissue raises
challenges along with new opportunities for minimally invasive medicine. In contrast to fluids, moving solids in soft media irreversibly rearranges the material, leading to highly non-linear
and history dependent reaction forces. The present work demonstrates that this behavior enables solutions of certain long-standing problems. One problem stems from using magnetic field
gradients to generate forces which limits their range particularly for sub-millimeter size magnetic robots. Locomotion by the transfer of energy via a time varying uniform magnetic field
provides an alternative. In fluids where locomotion effectively occurs through swimming at low Reynolds numbers, this strategy can be costly, requiring more complex shapes (e.g. a screw
[2]) and control over a non-reciprocal motion gait [3]. In tissues, such complex shapes have difficulties in changing their trajectory direction over short distances. The novel finding in this
work is that soft media enables locomotion of simple solids, such as a pair of spheres (see Fig. 1), without requiring them to execute a complex motion gait. Using an external uniform
magnetic field to change the relative orientations of the magnetic moments, the disconnected spherical solids of slightly different diameters can locomote as one in a soft medium via
ratchet-like movements that are completely reciprocal. Such a configuration also allows the pair to change the direction of locomotion quickly. A demonstration is carried out in this work
via development of a theoretical model and its numerical simulation, although some experimental observations support these findings. 

**References:** 

[1] J. J. Abbott et al., "How should microrobots swim?," The international journal of Robotics Research, vol. 28, no. 11-12, pp. 1434-1447, 2009. 
[2] T. W. Fountain, P. V. Kailat, and J. J. Abbott, "Wireless control of magnetic helical microrobots using a rotating-permanent-magnet manipulator," in 2010 IEEE International
Conference on Robotics and Automation, 2010: IEEE, pp. 576-581. 
[3] E. Lauga, "Life around the scallop theorem," Soft Matter, vol. 7, no. 7, pp. 3060-3065, 2011. 

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On Locomotion of Magnetized Spherical Solids in Soft Media

Micro helical robots actuated by an external magnetic field have been investigated for a possible application to treat occlusive vascular disease. It requires a high-speed
rotating magnetic field (RMF) which generates fast drilling motion of the micro helical robot to tunnel the clogged lesions in blood vessels.1-3 The RMF is generated by the magnetic
navigation systems (MNSs) composed of multiple coils or electromagnets. However, as the frequency increases, the impedance from the inductance of the coils decreases the current and
the magnetic field. To overcome this problem, prior researchers utilized a resonance by including additional capacitance to their MNS.2,3 The electromagnets with magnetic cores generate
a large magnetic field.4 Unlike the MNS with coils only, the MNS with electromagnets has significant mutual-inductance due to the magnetic flux linkages between electromagnets, but
any resonance method suppressing the self and mutual inductances of the electromagnets of the MNS has not been reported.
We propose a method to suppress both the self and mutual-inductance effect of the 3-phase MNS with multiple electromagnets. First, we set the imaginary part and the real parts except the
resistance in the voltage equation to be zero to express the resonance. After solving the real part of the voltage equation and the actuation matrix equation which relates applied current with
flux density together, we can determine 3-phase currents and corresponding phases at resonance. The capacitance at resonance can be determined by solving the imaginary part in the
voltage equation. Fig. 1 shows the 3-phase MNS developed for the experiments and Fig. 2 shows the calculated and measured 3-phase currents and RMF with the application of the
proposed method to generate a magnetic flux density of 10 mT. It shows that the calculated current matches well with the measured one within 5 % discrepancy. The proposed method in
this research can contribute to improving the tunneling performance of micro helical robots by generating a high-speed RMF even in the MNS with the electromagnets. 

**References:** 

1Q. Wang, X. Du, and L. Zhang, “Real-time ultrasound Doppler tracking and autonomous navigation of a miniature helical robot for accelerating thrombolysis in dynamic
blood flow,” ACS Nano, vol. 16, no. 1 (2022). 
2K. T. Nguyen, B. Kang and J. Park, “High-frequency and High-powered electromagnetic actuation system utilizing Two-stage resonant effects,” IEEE/ASME Transactions on
Mechatronics, vol. 25, no. 5 (2020). 
3J. Nam, W. Lee, and G. Jang, “Magnetic navigation system utilizing resonant effect to enhance magnetic field applied to magnetic robots,” IEEE Transactions on Industrial Electronics,
vol. 64, no. 6 (2017). 
4J. Nam, W. Lee, E. Jung, and G. Jang, “Magnetic navigation system utilizing a closed magnetic circuit to maximize magnetic field and a mapping method to precisely control magnetic
field in real time,” IEEE Transactions on Industrial Electronics, vol. 65, no. 7 (2018). 

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Resonant Control Method to Suppress the Self and Mutual Inductances of a 3 phase Magnetic Navigation System for Fast Drilling Motion of Micro Helical Robots

Magnetic catheter (MC) controlled by a magnetic navigation system (MNS) and a feeding device have been developed to overcome the steerability and the pushability of
conventional catheters.1,2 External magnetic field (EMF) produced from the MNS generates magnetic torque at the magnets in the MC to remotely steer the MC’s distal end while the
feeding device pushes the proximal end of the MC to move the MC forward.3,4 Sometimes, it does not work effectively when buckling of a flexible catheter occurs in complex blood
vessels.
We propose a position control method (PCM) of the Robotically Assisted MAgnetic Navigation (RAMAN) system to improve the pushability of the MC by maximizing magnetic force
(MF). Fig 1(a). shows the developed RAMAN system in which the 7-axis stage robot can move the 8 electromagnets (EMs) and the workspace surrounded by them. Fig 1(b). shows the MF
in the region of interest (ROI) which is 80% of the workspace. The PCM takes advantage of the fact that the MF increases as the magnet moves close to the EM. When the MF generated at
the MC is not sufficient, the PCM compares the MF of each vertex in the ROI and controls the 7-axis stage robot to move the ROI in such a way that the MC is located close to one of the
EMs to generate maximum MF. Fig 2. shows calculated maximum MF at the center of the ROI and at the point selected by the PCM where an axially magnetized ring magnet (OD: 2 mm,
ID: 1 mm, Length: 10 mm) of NdFeB 52 is located along θ and Φ directions. It shows that the PCM generates larger MF in any directions and 5 times larger MF on average than the
maximum MF generated at the center. We performed a navigation experiment of the MC along the aorta to the right coronary artery in a cardiac vascular phantom model. We observed a
buckling of the MC, and the maximum MF of 2.61 mN at the center did not overcome the buckling. We applied the PCM which generated the MF of 20.1 mN to release the buckling of the
MC. The PCM may contribute to controlling of the MC for robotic endovascular intervention. 

**References:** 

1B. J. Nelson, I. K. Kaliakatsos, and J. J. Abbott, Annual Review of Biomedical Engineering., Vol. 12, 55 (2010).
2N. Kim, S. Lee, W. Lee, and G. Jang, AIP Advances, Vol. 8, 056708 (2018).
3J. Nam, W. Lee, E. Jung, and G. Jang, IEEE Transactions on Industrial Electronics, Vol. 65, 5673 (2018)..
4E. Jung, W. Lee, N. Kim, J. Kim, J. Park, and G. Jang, AIP Advances, Vol 9, 125230 (2019). 

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Position Control Method of a Robotically Assisted Magnetic Navigation System to Improve the Pushability of a Magnetic Catheter by Maximizing Magnetic Force

Transcranial magnetic stimulation (TMS) is a non-invasive, effective, and safe neuromodulation technique used to diagnose and treat neurological disorders [1]-[2]. A key
challenge involved with TMS is to determine stimulation strength in critical regions of the brain accurately. The induced electric field is affected by complexity and heterogeneity of the
brain and numerical computation methods like finite element analysis (FEA) can be used to estimate electric field distribution. However, these methods need exceedingly high
computational resources and are time-consuming [3]-[6]. The purpose of this study was to develop and test a machine learning algorithm that can efficiently predict stimulation strength
based on neuroanatomy. Head models were developed from magnetic resonance images of eleven recruited subjects using SimNIBS pipeline [7]-[8]. We used Sim4Life, an FEA software
to compute induced electric fields due to simulated TMS; the induced electric fields served as training data. A deep convolutional neural network (DCNN) inspired encoder-decoder
network (Fig 1) was developed to predict induced electric fields from T1-weighted and T2-weighted magnetic resonance imaging (MRI) based anatomical slices. Three representative cases
of electric fields predicted by the DCNN algorithm, along with the corresponding reference electric fields are shown in Fig 2. For the trained network, the training data and the testing data
peak signal to noise ratios are 32.83dB and 28.01dB respectively. The key contribution of this study is the ability to predict the induced electric fields in real-time as well as accurately and
efficiently predicting TMS strength in the targeted brain regions saving both time and computational resources.
Acknowledgment: This work was supported by VCU CERSE. Further funding was provided by the CCI CVN (Proposal ID #: FP00010500). 

**References:** 

[1] D. J. Stultz, S. Osburn, T. Burns, S. Pawlowska-Wajswol, and R. Walton, Transcranial magnetic stimulation (TMS) safety with respect to seizures: A literature review,
Neuropsychiatric disease and treatment, vol. 16, p. 2989 (2020). 
[2] M. Kobayashi, and A. Pascual-Leone, 2003. Transcranial magnetic stimulation in neurology, The Lancet Neurology, vol. 2, no. 3, p. 145-156 (2003). 
[3] E. G. Lee, W. Duffy, R. L. Hadimani, M. Waris, W. Siddiqui, F. Islam, M. Rajamani, R. Nathan, and D. C. Jiles, Investigational effect of brain-scalp distance on the efficacy of
transcranial magnetic stimulation treatment in depression, IEEE Transactions on Magnetics, vol. 52, no. 7, p. 1–4 (2016). 
[4] L. J. Crowther, R. L. Hadimani, A. G. Kanthasamy, and D. C. Jiles, Transcranial magnetic stimulation of mouse brain using high-resolution anatomical models, Journal of Applied
Physics, vol. 115, no. 17, p. 17B303 (2014). 
[5] F. Syeda, H. Magsood, E. G. Lee, A. A. El-Gendy, D. C. Jiles, R. L. Hadimani, Effect of anatomical variability in brain on transcranial magnetic stimulation treatment, AIP Advances,
vol. 7, no. 5, p. 056711 (2017). 
[6] F. Syeda, K. Holloway, A. A. El-Gendy, and R. L. Hadimani, Computational analysis of transcranial magnetic stimulation in the presence of deep brain stimulation probes, AIP
Advances, vol. 7, no. 5, p. 056709 (2017). 
[7] N. Mittal, C. Lewis, Y. Cho, C. L. Peterson, and R. L. Hadimani, Effect of fiber tracts and depolarized brain volume on resting Motor thresholds during transcranial magnetic
stimulation, IEEE Transactions on Magnetics (2022). 
[8] N. Mittal, B. Thakkar, C. B. Hodges, C. Lewis, Y. Cho, R. L. Hadimani, and C. L. Peterson, Effect of neuroanatomy on corticomotor excitability during and after transcranial magnetic
stimulation and intermittent theta burst stimulation, Human Brain Mapping (2022). 

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Prediction of Stimulation Strength of Transcranial Magnetic Stimulation in the Brain with Deep Convolutional Neural Network based Encoder Decoder Network

There has been a need for rapid screening of people infected virus including with COVID-19 or influenza. Virus detection methods using magnetic harmonics of magnetic nanoparticles (MNPs) with superparamagnetism has been reported [1, 2]. In this study, we report the detection of influenza virus based on magnetic second harmonic signals [3], and the detection sensitivity was 100 pg/mL. Figure 1 shows the developed system for virus detection. The excitation coil generated AC magnetic fields of amplitude of 6.6 mT with 1 kHz and the detection coil detect the second harmonic signals of MNPs under DC magnetic field of 6.6 mT. The measurement of the magnetization response of MNPs completed in one minute. The samples contained MNPs (Nanomag-D, average diameter 20 nm, 5 mg/mL, 9.24Ã—1012 particles) coated with protein-A, with which antibodies (Nucleoprotein InA245). Antigens (Influenza A virus) bound to the antibodies by antigen-antibody reaction. Figure 2 shows the relation between the second harmonic signal normalized by the fundamental signal R2/R0 and the third harmonic signal normalized by the fundamental signal R3/R0 with five different antigen concentrations (0, 103, 105, 107, 109 antigens). R2/R0 was about 2.3 times larger than R3/R0. This result indicates that the detection of viruses using the second harmonic signal has a larger detectable range of the number of antigens. In addition, the value of R2/R0 significantly reduce at 104 antigens (Fig. 2(a)). This result indicate that we can detect 104 antigens (100 pg/mL). In the future, we aim to achieve detection sensitivity of the PCR method (1 pg/mL) by investigating the optimal detection coil shape, excitation frequency, and concentration of MNPs for virus detection.

Rapid Virus Detection using Magnetic Second Harmonics of Superparamagnetic Iron Oxide Nanoparticles

Body Magnetic particle imaging (MPI) is a technique to visualize magnetic nanoparticles with high spatial and temporal resolutions based on nonlinear magnetization response.1
One of major challenges toward clinical MPI system is how to implement low ac excitation fields. For brain MPI particularly,2 a 24 kHz excitation field intensity with amplitude over 3.5
mT may induce peripheral nerve stimulation on human head.3 However, low-field MPI scenario degrades spatial resolution since the detected signal has no harmonic components but high
contamination from the excitation fields. Previously, we applied 1 MHz excitation field to elevate signal-to-noise ratio of receive coil.4 To further decontaminate magnetization signal
spectrally, we used magnetoresistive (MR) sensor to transform monotone signal into harmonic-rich one and reconstructed phantom image from odd harmonic components.5 Extensively,
MR sensor can be used to map quasistatic stray field of magnetic nanoparticles.6
Here, we will report the use of a 6×6 channels array of TDK Nivio xMR sensors to detect sub-pT magnetic signal and obtain its spatial distribution. While each sensor is operated at 5 V,
signal processing circuit rises its sensitivity to 20 mV/ pT at 10 kHz with 0.25 pT noise level. We used a 40-turns coil with 1 mm diameter and 5 mm length to represent magnetic moment.
The distance between MR sensor and the coil (dx) was 250 mm [Fig. 1(a)]. From Fig. 1(b), MR sensor recognizes magnetic signal from mini coil fed with a 10 kHz ac current. Magnetic
field detected by the sensor (Hd) is linear with coil input current (i). Furthermore, we simultaneously recorded the signals from 36 sensor channels to map at 200 Hz. We set dx=50 mm to
obtain high contrast showing coil position relative to the array. From Fig. 2, the change in field polarity is observable from frames (i), (ii), (iii), and (iv) with channel c16 as reference. This
result highlights usability of MR sensor array for low-field MPI system. 

**References:** 

1. B. Gleich and J. Weizenecker, Nature, 435, 1214 (2005). 
2. M. Graeser, F. Thieben and T. Knopp, Nat. Commun., 10, 1936 (2019). 
3. A. A. Ozaslan, M. Utkur and E. U. Saritas, Int. J. Mag. Part. Imag., 8, 2203028 (2022). 
4. S. B. Trisnanto and Y. Takemura, Phys. Rev. Appl., 14, 064065 (2020). 
5. S. B. Trisnanto, T. Kasajima and Y. Takemura, Appl. Phys. Express, 14, 095001 (2021). 
6. S. B. Trisnanto, T. Kasajima and Y. Takemura, J. Appl. Phys. 131, 224902 (2022). 

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Sub pT oscillatory magnetometric system using magnetoresistive sensor array for a low

Magnetic Particle Imaging (MPI) is a novel medical imaging modality that is in a preclinical stage [1]. MPI scanners use rf magnetic fields to excite and measure oscillations in superparamagnetic iron oxide nanoparticles (SPIO) so that the signal is proportional to SPIO's concentration. Applying a gradient magnetic field allows an MPI scanner to spatially localize the signal. Our group has designed a single sided field-free line (FFL) scanner, which has all hardware on a single side of the device providing an open imaging volume, useful for imaging larger subjects such as humans. Compared to a field-free point scanner [2], our device promises higher sensitivity and robust image reconstruction. In the past, we demonstrated 1D imaging capabilities by implementing electronic scanning of field-free line (FFL) across a simple rod phantom [3] and simulated 2D image reconstruction with backprojection technique [4]. In this work we demonstrate the 2D imaging capability of our prototype scanner by imaging phantoms, which include a single rod and two rods in orthogonal orientation, i.e. "elbow". Each rod has a diameter of 1.2 mm and a length of 10 mm and filled with undiluted SynomagD SPIO. To excite the SPIO in our samples we applied an rf magnetic field created by a low noise sinusoidal current source at 25 kHz producing a magnetic field of 1.5 mT at the surface of the scanner. For image encoding the FFL is created and dynamically scanned across the sample by two programmed DC power supplies providing a gradient of 0.58 T/m. The signal is recorded at 0.5 mm step over 4 cm interval of a rotated sample at diffrent discrete angles. The resulted backprojection reconstruction images are shown in the Fig.1. The final images were also deconvoluted with the experimentally obtained point spread function providing a spatial resolution of 4 mm. At this relatively low field gradient this is a reasonable result and in the future we will incorporate higher field gradient and dynamic trajectory correction to improve the uniformity of the image. This work is a significant first step towards human MPI imaging that can be potentially used for diagnostics and biopsy of cancer.

Two Dimensional Imaging Using a Single Sided Field Free Line Magnetic Particle Imaging Scanner

Magnetic hyperthermia with magnetic nanoparticles (MNPs) has been introduced to selective treatment of tumor [1,2] and the MNPs also has demonstrated diagnosis [3, 4].
For non-invasive treatment, a therapeutic system with a temperature monitoring that can avoid overheating in normal tissues is of vital importance. We have developed a temperature
monitoring/control system with an optical fiber temperature probe in vivo [2]. However, the optical fiber involves an invasive measurement due to the contact with the body.
In this study, we have developed a wireless temperature monitoring system by utilizing the combination of magnetic harmonic signals of the MNPs for clinical trials. Figure 1 shows the
developed wireless monitoring system with Resovist® (a clinically approved MNP). Under the application of alternating magnetic fields, the detected harmonics were analyzed to extract
only temperature-dependent signals. Figure 2 shows the measured temperature of Resovist® phantom. We achieved an accurate measurement with an error of 0.18°C (Fig. 2(a)). For
practical use on breast/oral cancer, a detectable distance of 10 mm is required. We measured the accurate temperature at a 10 mm distance (Fig. 2(b)). To demonstrate the feasibility toward
clinical trials, we investigated the dependency on the detectable distance and the amount of Resovist®. The error is less than 0.5°C in a 10 mm distance (Fig. 2(c)). Resovist® travels to the
whole body from the injection site via the lymphatic system, resulting in a decrement of the amount at the injection site. Our system can measure the correct temperature regardless of
Resovist® amount (Fig. 2(d)). The results indicate that our system can apply to clinical trials. We will pursue further study of a temperature monitoring system under magnetic
hyperthermia treatment. 

**References:** 

[1] D. Kouzoudis et al., frontiers in Materials 8, 638019 (2021) 
[2] A. Shikano et al., T. Magn. Soc. Jpn. (Special Issues) 6, 100-104 (2022). 
[3] M. Sekino et al., Scientific Reports 8, 1195 (2018) 
[4] K. Taruno et al., J. Surg. Oncol. 120, 1391 (2019) 

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Wireless temperature monitoring by using magnetic nanoparticles for clinical trials on magnetic hyperthermia treatment

For cancer therapy with magnetic hyperthermia by using magnetic nanoparticles (MNPs) [1, 2], alternating magnetic fields (AMF) HAC, typically sinusoidal wave, can deliver the magnetic energy into the deeper location in the body. In this study, we proposed a highly effective heat generation method for the MNPs by the application of an ultra-short pulse. We numerically evaluated the heating power with a variety of parameters, such as pulse width, field amplitude, and frequency [3]. Figure 1 shows effective magnetic hyperthermia with the ultra-short pulse magnetic field (Fig.1 (a)). The hysteresis curve and magnetization dynamics clearly indicate larger energy dissipation (Figs. 1 (b) and (c)). Figure 2 shows the energy dissipation and efficiency [4, 5] on the two-dimensional parameter space of field strength and duty ratio. Hysteresis loss and the input energy increases increasing with field strength and duty ratio (Figs. 2(a) and (b)) and there is a large efficiency power condition (Fig.2 (c)). To evaluate the effective heat generation and practical temperature increment, a larger imaginary part of magnetic susceptibility (Ï‡â€™â€™ &gt; 30) and specific loss power (SLP &gt; 105 W/kg) are required (Figs. 2 (d) and (e)). In addition, larger intrinsic loss power (100 nHm2/kg) is achieved (Fig. 2 (f)). Finally, we found the optimal condition of applied AMF (duty ratio = 1.2% and HAC = 16 kA/m) considering the practical uses. The results indicate that magnetic harmonics signals with a higher frequency range significantly enhance the heat generation of MNPs. We explore further studies of the development of an effective pulse generator for clinical applications and evaluation of the heating effect in animal experiments.

Underline digital video library

Rod mangle rotation patterns for magnetic field generation

Sedimentation of Magnetorheological Fluids Measured Using a Automated Vertical Axis Inductance Monitoring System

Development of Magnetorheological Fluids within 3D Printed Elastomeric Cellular Structures with an Accumulator

On Locomotion of Magnetized Spherical Solids in Soft Media

Resonant Control Method to Suppress the Self and Mutual Inductances of a 3 phase Magnetic Navigation System for Fast Drilling Motion of Micro Helical Robots

Position Control Method of a Robotically Assisted Magnetic Navigation System to Improve the Pushability of a Magnetic Catheter by Maximizing Magnetic Force

Prediction of Stimulation Strength of Transcranial Magnetic Stimulation in the Brain with Deep Convolutional Neural Network based Encoder Decoder Network

Rapid Virus Detection using Magnetic Second Harmonics of Superparamagnetic Iron Oxide Nanoparticles

Sub pT oscillatory magnetometric system using magnetoresistive sensor array for a low

Two Dimensional Imaging Using a Single Sided Field Free Line Magnetic Particle Imaging Scanner

Wireless temperature monitoring by using magnetic nanoparticles for clinical trials on magnetic hyperthermia treatment

Ultra short pulse magnetic fields on effective magnetic hyperthermia for cancer therapy

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