France



Transcranial magnetic stimulation (TMS) is a neuromodulation therapy that can be used to treat neurological and psychiatric conditions and has been approved by the FDA for certain disorders [1]–[4]. Since TMS trials with humans are not always feasible, brain phantoms have been developed as ways of testing without actually stimulating the patient.&lt;br/&gt;Although a brain phantom has been developed for humans, a comparable brain phantom for rats or mice has not been created specifically for TMS or other neuromodulation techniques. An individualized brain phantom for rats is needed to accelerate the study of neuromodulation techniques, especially the measurement of induced electric field and voltages in the brain regions when stimulated by a time-varying magnetic field. The main objective of this paper is to develop an individualized, anatomically-accurate rat brain model for finite element simulation and a physical model for experimental measurement of stimulation strengths.&lt;br/&gt;We initially obtained magnetic resonance images (MRIs) from public databases to create the anatomically accurate brain models. The Waxholm Space Atlas of the Sprague Dawley rat brain was chosen as the MRI to be created into the preliminary phantom. Using the Skull Stripping tool from the BrainSuite software package, the brain was separated from the surrounding skull and skin. Both the original and skull-stripped brain NIFTI files were downsampled using AFNI software tools. The skull-stripped brain was then inputted as a reference mask into the Skull Stripper Python program, along with the downsampled original MRI [5]. The output was the final file, containing 3D information of the chosen rat brain.&lt;br/&gt;Using the 3D Slicer program, the final brain file was converted into a 3-dimensional STL file. The program Meshmixer was then used to reduce the file size and fix any model errors. The anatomically accurate individualized brain model was combined with a TMS coil designed for small animals in SolidWorks. An enclosure was also made that surrounded the coil and brain (serving as air in the simulation). The Maxwell 3D module in ANSYS finite element simulation software was then used to simulate the magnetic flux density and induced electric fields in the rat brain models. Fig. 1 inset shows the orientation of the brain and coil in the simulation. Fig. 1 and Fig. 2 show preliminary results of what is predicted for the physical phantom, with all the layers (skin, skull, and other tissues) hidden except the brain. We had assigned uniform conductivity of 0.2 S/m for the entire brain, a relative permeability of 1, and a relative permittivity of 12,000. A figure of eight coil was used on the top of the rat’s head with 1000A current supplied to the coil. The peak magnetic field of 1.22 T and 2.5 ×10&lt;sup&gt;-6&lt;/sup&gt;A/m&lt;sup&gt;2&lt;/sup&gt; occurs on the surface of the brain below the center of the coil.&lt;br/&gt;We are currently in the process of developing a physical individualized, anatomically-accurate physical brain phantom using the above computation models. Work to consider white an grey matter separately in the model is currently in progress. We will use similar techniques as used in the development of our existing human brain phantoms [6], [7]. Using the phantom, we will systematically measure the stimulations strengths in different regions of the brain using several coils types.&lt;br/&gt;&lt;br/&gt;Acknowledgement: Authors would like to thank funding from Dean&#39;s Early Researcher Initiative (DERI) program at College of Engineering of Virginia Commonwealth University, Richmond, VA, USA.

**References:**

[1] E. M. Wassermann and S. H. Lisanby, “Therapeutic application of repetitive transcranial magnetic stimulation: a review,” &lt;i&gt;Clin. Neurophysiol.&lt;/i&gt;, vol. 112, no. 8, pp. 1367–1377, Aug. 2001, doi: 10.1016/S1388-2457(01)00585-5.&lt;br/&gt;[2] L. Carmi, U. Alyagon, N. Barnea-Ygael, J. Zohar, R. Dar, and A. Zangen, “Clinical and electrophysiological outcomes of deep TMS over the medial prefrontal and anterior cingulate cortices in OCD patients.,” &lt;i&gt;Brain Stimulat.&lt;/i&gt;, vol. 11, no. 1, pp. 158–165, Sep. 2017, doi: 10.1016/j.brs.2017.09.004.&lt;br/&gt;[3] R. B. Lipton &lt;i&gt;et al.&lt;/i&gt;, “Single-pulse transcranial magnetic stimulation for acute treatment of migraine with aura: a randomised, double-blind, parallel-group, sham-controlled trial.,” &lt;i&gt;Lancet Neurol.&lt;/i&gt;, vol. 9, no. 4, pp. 373–80, Apr. 2010, doi: 10.1016/S1474-4422(10)70054-5.&lt;br/&gt;[4] M. S. George and R. H. Belmaker, &lt;i&gt;Transcranial Magnetic Stimulation in Clinical Psychiatry&lt;/i&gt;. American Psychiatric Pub, 2007.&lt;br/&gt;[5] A. Delora &lt;i&gt;et al.&lt;/i&gt;, “A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head,” &lt;i&gt;J. Neurosci. Methods&lt;/i&gt;, vol. 257, pp. 185–193, Jan. 2016, doi: 10.1016/j.jneumeth.2015.09.031.&lt;br/&gt;[6] H. Magsood and R. L. Hadimani, “Development of anatomically accurate brain phantom for experimental validation of stimulation strengths during TMS,” &lt;i&gt;Mater. Sci. Eng. C&lt;/i&gt;, p. 111705, Nov. 2020, doi: 10.1016/j.msec.2020.111705.&lt;br/&gt;[7] H. Magsood, F. Syeda, K. Holloway, I. C. Carmona, and R. L. Hadimani, “Safety Study of Combination Treatment: Deep Brain Stimulation and Transcranial Magnetic Stimulation,” &lt;i&gt;Front. Hum. Neurosci.&lt;/i&gt;, vol. 14, p. 123, Apr. 2020, doi: 10.3389/FNHUM.2020.00123.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/3c260949a0c73b00d1141a7be71b9817.jpg)
&lt;i&gt;Figure 1. Magnetic flux density (B) plot of rat brain surface. Inset: Coil and rat brain orientation (scalp, skull and cerebrospinal fluid layers are hidden)&lt;/i&gt;

![](https://assets.underline.io/uploads/markdown_image/1/image/eb56630d580e5595f2d0ddbe23bac3d2.jpg)
&lt;i&gt;Figure 2. Electric current density (J) plot of rat brain surface. Inset: Coil and rat brain orientation (scalp, skull and cerebrospinal fluid layers are hidden)&lt;/i&gt;

INTERMAG 2021

 Development of individualized brain model and physical phantom of small animals for experimental verification of transcranial magnetic stimulation

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Transcranial magnetic stimulation (TMS) is a neuromodulation therapy that can be used to treat neurological and psychiatric conditions and has been approved by the FDA for certain disorders [1]–[4]. Since TMS trials with humans are not always feasible, brain phantoms have been developed as ways of testing without actually stimulating the patient. Although a brain phantom has been developed for humans, a comparable brain phantom for rats or mice has not been created specifically for TMS or other neuromodulation techniques. An individualized brain phantom for rats is needed to accelerate the study of neuromodulation techniques, especially the measurement of induced electric field and voltages in the brain regions when stimulated by a time-varying magnetic field. The main objective of this paper is to develop an individualized, anatomically-accurate rat brain model for finite element simulation and a physical model for experimental measurement of stimulation strengths. We initially obtained magnetic resonance images (MRIs) from public databases to create the anatomically accurate brain models. The Waxholm Space Atlas of the Sprague Dawley rat brain was chosen as the MRI to be created into the preliminary phantom. Using the Skull Stripping tool from the BrainSuite software package, the brain was separated from the surrounding skull and skin. Both the original and skull-stripped brain NIFTI files were downsampled using AFNI software tools. The skull-stripped brain was then inputted as a reference mask into the Skull Stripper Python program, along with the downsampled original MRI [5]. The output was the final file, containing 3D information of the chosen rat brain. Using the 3D Slicer program, the final brain file was converted into a 3-dimensional STL file. The program Meshmixer was then used to reduce the file size and fix any model errors. The anatomically accurate individualized brain model was combined with a TMS coil designed for small animals in SolidWorks. An enclosure was also made that surrounded the coil and brain (serving as air in the simulation). The Maxwell 3D module in ANSYS finite element simulation software was then used to simulate the magnetic flux density and induced electric fields in the rat brain models. Fig. 1 inset shows the orientation of the brain and coil in the simulation. Fig. 1 and Fig. 2 show preliminary results of what is predicted for the physical phantom, with all the layers (skin, skull, and other tissues) hidden except the brain. We had assigned uniform conductivity of 0.2 S/m for the entire brain, a relative permeability of 1, and a relative permittivity of 12,000. A figure of eight coil was used on the top of the rat’s head with 1000A current supplied to the coil. The peak magnetic field of 1.22 T and 2.5 ×10-6A/m2 occurs on the surface of the brain below the center of the coil. We are currently in the process of developing a physical individualized, anatomically-accurate physical brain phantom using the above computation models. Work to consider white an grey matter separately in the model is currently in progress. We will use similar techniques as used in the development of our existing human brain phantoms [6], [7]. Using the phantom, we will systematically measure the stimulations strengths in different regions of the brain using several coils types. Acknowledgement: Authors would like to thank funding from Dean's Early Researcher Initiative (DERI) program at College of Engineering of Virginia Commonwealth University, Richmond, VA, USA.

**References:**

[1] E. M. Wassermann and S. H. Lisanby, “Therapeutic application of repetitive transcranial magnetic stimulation: a review,” Clin. Neurophysiol., vol. 112, no. 8, pp. 1367–1377, Aug. 2001, doi: 10.1016/S1388-2457(01)00585-5. [2] L. Carmi, U. Alyagon, N. Barnea-Ygael, J. Zohar, R. Dar, and A. Zangen, “Clinical and electrophysiological outcomes of deep TMS over the medial prefrontal and anterior cingulate cortices in OCD patients.,” Brain Stimulat., vol. 11, no. 1, pp. 158–165, Sep. 2017, doi: 10.1016/j.brs.2017.09.004. [3] R. B. Lipton et al., “Single-pulse transcranial magnetic stimulation for acute treatment of migraine with aura: a randomised, double-blind, parallel-group, sham-controlled trial.,” Lancet Neurol., vol. 9, no. 4, pp. 373–80, Apr. 2010, doi: 10.1016/S1474-4422(10)70054-5. [4] M. S. George and R. H. Belmaker, Transcranial Magnetic Stimulation in Clinical Psychiatry. American Psychiatric Pub, 2007. [5] A. Delora et al., “A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head,” J. Neurosci. Methods, vol. 257, pp. 185–193, Jan. 2016, doi: 10.1016/j.jneumeth.2015.09.031. [6] H. Magsood and R. L. Hadimani, “Development of anatomically accurate brain phantom for experimental validation of stimulation strengths during TMS,” Mater. Sci. Eng. C, p. 111705, Nov. 2020, doi: 10.1016/j.msec.2020.111705. [7] H. Magsood, F. Syeda, K. Holloway, I. C. Carmona, and R. L. Hadimani, “Safety Study of Combination Treatment: Deep Brain Stimulation and Transcranial Magnetic Stimulation,” Front. Hum. Neurosci., vol. 14, p. 123, Apr. 2020, doi: 10.3389/FNHUM.2020.00123.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/3c260949a0c73b00d1141a7be71b9817.jpg)
Figure 1. Magnetic flux density (B) plot of rat brain surface. Inset: Coil and rat brain orientation (scalp, skull and cerebrospinal fluid layers are hidden)

![](https://assets.underline.io/uploads/markdown_image/1/image/eb56630d580e5595f2d0ddbe23bac3d2.jpg)
Figure 2. Electric current density (J) plot of rat brain surface. Inset: Coil and rat brain orientation (scalp, skull and cerebrospinal fluid layers are hidden)

poster

Transcranial Magnetic Stimulation (TMS) is a non-invasive technique that is approved by the U.S. Food and Drug Administration (FDA) for the treatment of certain neurological disorders [1]. When comparing TMS to techniques with similar desired outcomes such as conventional brain surgery, TMS has far fewer risks due to its non-invasive nature. TMS works by inducing an electric field that polarizes or depolarizes brain tissues depending on treatment mode. TMS researchers have proposed different coil designs to achieve higher focality and increased depth of penetration of the induced electric field [2]. The Quadruple Butterfly Coil (QBC) is a novel coil design with increased focality when compared to the commercially available Figure-of-eight (FOE) coil [3]. The human brain reaches 90% of its adult volume at age six and does not reach full maturity until approximately the age of 25, and throughout adolescence, the brain is still maturing [4]. The differences in the brain from adolescents to adults could affect the effectiveness of TMS, mainly because the coils have been designed for use on adult patients [5], [6]. Comparing the efficacy of TMS coils across age groups to determine if the difference in brain volume is enough to warrant specific TMS treatment protocols for adolescents is of the essence in advancing TMS research [7]. In this research, the authors compare the use of the Quadruple Butterfly Coil (QBC) across different age groups to test the effectiveness of the coil on various stages of brain development. Simulations were run using a finite element analysis software, Sim4Life. The models used in this study were sourced from the Computable Virtual Population Models from the IT’IS Foundation. The models have well defined anatomy and were selected to each represent a different age group. The adult models used as the control are 34 years old male (34M) and 26 years old female (26F), as they both fall in the typical age range of models (25 to 35 years) used for TMS studies. The models used to represent the pediatric population are 14 years old male (14M), 11 years old female (11F), 8 years old female (8F), 8 years old male (8M), 6 years old male (6M), and 5 years old female (5F) [8]. Fig. 1 presents the distribution of the induced electric field intensity with depth across the different models. Besides age and brain volume, other factors such as the brain – scalp distance (BSD), cerebrospinal fluid (CSF) thickness, scalp thickness, and skull thickness of the models were also considered in the analysis. This study provides an understanding of the various factors contributing to the response from TMS. The maximum electric field intensity on the scalp (E-Max scalp), maximum electric field intensity on the brain (E-Max brain) and the proportion of the E-Max scalp to E-Max brain are parameters considered in this analysis.

**References:**

[1] M. Hallett, "Transcranial magnetic stimulation and the human brain", Nature, vol. 406, no. 6792, pp. 147-150, 2000. Available: https://www.nature.com/articles/35018000. [2] M. Hallett, "Transcranial Magnetic Stimulation: A Primer", Neuron, vol. 55, no. 2, pp. 187-199, 2007. Available: https://www.sciencedirect.com/science/article/pii/S0896627307004606. [3] P. Rastogi, E. G. Lee, R. L. Hadimani, and D. C. Jiles, “Transcranial Magnetic Stimulation-coil design with improved focality,” AIP Adv., vol. 7, no. 5, p. 056705, May 2017, doi: 10.1063/1.4973604. [4] J. Stiles and T. Jernigan, "The Basics of Brain Development", Neuropsychology Review, vol. 20, no. 4, pp. 327-348, 2010. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2989000/. [5] L. Crowther, R. Hadimani and D. Jiles, "A numerical dosimetry study for pediatric transcranial magnetic stimulation", 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), 2013. Available: https://ieeexplore.ieee.org/abstract/document/6695916/authors#authors. [Accessed 10 September 2020]. [6] J. Weissman, C. Epstein and K. Davey, "Magnetic brain stimulation and brain size: relevance to animal studies", Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section, vol. 85, no. 3, pp. 215-219, 1992. Available: https://www.sciencedirect.com/science/article/pii/016855979290135X. [7] M. Garvey and V. Mall, "Transcranial magnetic stimulation in children", Clinical Neurophysiology, vol. 119, no. 5, pp. 973-984, 2008. Available: https://www.sciencedirect.com/science/article/pii/S1388245707007353. [8] M. Gosselin et al., "Development of a new generation of high-resolution anatomical models for medical device evaluation: The Virtual Population 3.0", Physics in Medicine and Biology, vol. 59, no. 18, pp. 5287-5303, 2014. Available: 10.1088/0031-9155/59/18/5287.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/27f067807ad62659e1f06d16031a63f5.jpg)
Fig. 1. Variation of the Induced Electric Field (V/m) with depth across the different subjects.

 Transcranial Magnetic Stimulation: The Effect of Age and Other Factors on the Intensity of the Quadruple Butterfly Coil

Nuclear magnetic resonance imaging is the most used technique for investigating human tissue. This is a noninvasive technique for the patient, based on the use of an intense magnetic field and radiofrequency pulses applied at certain angles. The application of the radiofrequency pulse has the effect disruption of the equilibrium state of nuclear atomic moments of atoms, induced signals being described by longitudinal relaxation time (T1) and transverse relaxation time (T2). For a better view of tumor tissues, there are used contrast agents; a dose of contrast agent distributed throughout the body can be used to quickly view extensive areas of anatomy. Most of the NMR contrast agents are either complex paramagnetic ions or superparamagnetic loadstone particles (iron oxide). However, the most used agents in NMR investigations are based on Gadolinium chelates. These are less toxic and present positive contrast in the T1 sequence. Superparamagnetic loadstone particles (iron oxide) are at an experimental stage; the sensitivity of these techniques is currently not suitable for clinical applications, new significant relaxation agents targeted to specific tissues or disease processes being required. In this study, the CoZnFe2O4Ag nanoparticle series was dispersed in distilled water, thus forming dilutions, and the same amounts of ferrite were stabilized in agar gels. The obtained dilutions and agar fantoms were scanned with the MRI medical facilities with the intensity of the magnetic field of 1.5 T and 0.4 T respectively. For these, the basic sequences, T1 and T2, were obtained. The contribution of CoZnFe2O4Ag nanoparticles on the contrast of nuclear magnetic resonance images obtained from scanning of two medical MRI installations as compared to images obtained by scanning several commercial contrast agents used in medical imaging. The resulting images were analyzed using a commercial graphics program to highlight the influence of particles on the contrast of the images. The analyzed images indicate that the CoZnFe2O4Ag ferries show positive contrast in the T1 sequence. Small ferrite concentrations (0.05, 0.08, 0.1) have better contrast compared to higher concentrations (0.5, 1). Large concentrations of ferrite have the effect of decreasing magnetization and, implicitly, of lowering the signal (contrast). The CoZnFe2O4Ag series could be used as a possible contrast agent for MRI investigations, only if they are compatible by coating with polymers compatible with the human body. In this respect, severe toxicity tests should be carried out.

**References:**

Rinck, Peter A MAGNETIC RESONANCE IN MEDICINE - A Critical Introduction. 12th edition (2018) Chrysikopoulos, Haris S, Clinical MR Imaging and Physics., (2009) J. Lohrke, T. Frenzel 25 Years of Contrast-Enhanced MRI: Developments, Current Challenges, and Future Perspectives, (2016) Yu-Dong Xiao, Ramchandra Paudel, MRI contrast agents: Classification and application., Vol. 38 (2016) Perry Sprawls, Magnetic Resonance Imaging- Principles, Methods, and Techniques. (2000) Alshowiman, Sami S, MRI Contrast Agents: Developments, Challenges, and Future Trends., Vol. 8 (2018) C. P. Constantin, A. Iordana, O. F. Caltun, CoxZnx-1Fe2O4 nanoparticles ferrite series as magnetic resonance imaging contrast agents. (2012)

**Images:**

 The series study of the CoZnFe2O4Ag in the MRI contrast

Over the past decade, superparamagnetic iron oxide (Fe3O4) nanoparticles have drawn significant attention for different applications such as contrast agents for magnetic resonance imaging (MRI), drug delivery or magnetic hyperthermia(MRI) [1-3]. Due to their negative contrast enhancement effect on T2 and T2* weighted images, they have played a role as contrast agents in MRI [4]. They provide the most change in signal per unit of metal particularly on T2* weighted images as each particle is composed of thousands of iron atoms and defeats the inherent low contrast agent sensitivity of MRI [5]. However, the contrast enhancing effectiveness of a superparamagnetic nanoparticle depends on size of the iron oxide crystal, the composition, the charge, the nature of the coating, the hydrodynamic size of the coated nanoparticle, magnetization and aggregation state in the biological environment as these parameters influence the longitudinal and transverse proton relaxivities [6, 7]. The surface properties of the magnetic NPs play an important role in their efficiency as MRI contrast agents. Therefore, they require a surface coating in order to improve their dispersion and stability in aqueous media. This work was related to the effect of silica shell thickness on proton relaxivities and magnetic properties of superparamagnetic iron oxide nanoparticles. It is possible to predict and finely tune the silica shell thickness by varying the amount of TEOS used to adjust the magnetic properties and proton relaxometric properties. Core-shell structures of the form Fe3O4@mSiO2 with different silica shell thicknesses i.e 45, 63 nm and 73 nm were synthesized by a surfactant template sol-gel method. The silica-coated magnetic iron oxide nanoparticles were found to be spherical in TEM images with a core shell structure with average diameters of 136, 155, and 175 nm for 45, 63 nm and 73 nm shell thickness coatings, respectively. A decrease in Ms value was found with decreasing silica shell thickness. Both r1 and r2 proton relaxivities inversely correlated with the increasing silica shell thickness and size of the particles. The r2 relaxivities were found to be much higher than the r1 relaxivities, which reflects the fact that the T2 proton relaxation is mainly influenced by outer sphere processes. All the Fe3O4@mSiO2 particles are relatively weak T1 contrast agents. While, as T2 contrast agents, they showed higher relaxivity with decreasing silica coating of the magnetic core. It is interesting to note that the changes in r1 and r2 due to silica shell thickness indicate that it is an important factor to take into consideration when designing magnetic nanoparticle probes for molecular imaging applications using MRI. It is crucial to develop an understanding of the structure and properties of the nanoparticle since the different silica shell thicknesses around magnetite have an effect on the proton transverse relaxivity.

**References:**

[1] R. Qiao, C. Yang, M. Gao, Superparamagnetic iron oxide nanoparticles: from preparations to in vivo MRI applications, Journal of Materials Chemistry, , 19 (2009) 6274-6293. [2] M. Mahmoudi, S. Sant, B. Wang, S. Laurent, T. Sen, Superparamagnetic iron oxide nanoparticles (SPIONs): development, surface modification and applications in chemotherapy, Adv Drug Deliv Rev, 63 (2011) 24-46. [3] Q.A. Pankhurst, J. Connolly, S.K. Jones, J. Dobson, Applications of magnetic nanoparticles in biomedicine, Journal of Physics D: Applied Physics, 36 (2003). [4] D.-X. Chen, N. Sun, Z.-J. Huang, C.-M. Cheng, H. Xu, H.-C. Gu, Experimental study on T2 relaxation time of protons in water suspensions of iron-oxide nanoparticles: Effects of polymer coating thickness and over-low 1/T2, Journal of Magnetism and Magnetic Materials, 322 (2010) 548-556. [5] D.W. McRobbie, E.A. Moore, M.J. Graves, M.R. Prince, MRI From picture to proton, Second ed., Cambridge University Press, UK, 2003. [6] S.H. Koenig, K.E. Kellar, Theory of 1/T1 and 1/T2 NMRD profiles of solutions of magnetic nanoparticles, Magn Reson Med, 34 (1995) 227-233. [7] P.H. Qiu, C. Jensen, N. Charity, R. Towner, C.B. Mao, Oil Phase Evaporation-Induced Self-Assembly of Hydrophobic Nanoparticles into Spherical Clusters with Controlled Surface Chemistry in an Oil-in-Water Dispersion and Comparison of Behaviors of Individual and Clustered Iron Oxide Nanoparticles, Journal of the American Chemical Society, 132 (2010) 17724-17732.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/1d51332af5f385219245ab0c3ce7dfcb.jpg)
Fig. 1. Plot of transverse relaxation rates (1/T2), at different iron oxide concentrations for Fe3O4@mSiO2 with different silica shell thickness, measured at 25 °C and 60 MHz; number in the brackets indicate the thickness of the silica shell.

![](https://assets.underline.io/uploads/markdown_image/1/image/efe5f149c36e526b04ec9386da5543ea.jpg)
Fig. 2. Plot of longitudinal relaxation rates (1/T1) at different iron oxide concentrations for Fe3O4@mSiO2 with different silica shell thickness, measured at 25 °C and 60 MHz; number in the brackets indicate the thickness of the silica shell.

 The Effect of Silica Shell Thickness on Magnetic and Proton Relaxometric Properties: Fe3O4@mSiO2 Nanoparticles

Magnetic hyperthermia is a promising cancer therapy gaining great interest in recent years using heat generation ascribed to magnetic particles subjected to a high-frequency magnetic field. To make this therapy feasible in clinical settings, in addition to magnetic particles, important elements include techniques for detecting their position and temperature in a tumor region in determining the effectiveness of therapeutic heating. In previous studies, we developed thermosensitive magnetic micro/nanoparticles with high heating efficiency and considerable permeability change around the therapeutic temperature range of 42-45°C [1]. We also proposed a wireless temperature measurement method for monitoring the tumor temperature using pickup coils to detect the temperature-dependent stray magnetic field caused by the magnetic particles [2]. A challenge remains when the particles injected into the tumor region deviate from the longitudinal axis of drive coil (heating coil). As a result, the heating generation of the particles and the accuracy of the proposed thermometry are decreased. To solve this problem, by taking the advantage of the fact that the induced voltage in pickup coil depends on the position of the particles, we developed a localization system using three pickup coils symmetrically installed inside drive coil. The position of particles could be automatically localized by using a robot arm to operate the unit composed of drive coil and pickup coils in two modes of coarse adjustment (rotary scanning) and fine adjustment (linear scanning) [3]. In this study, we propose a simpler, faster and more cost-effective localization method by using only figure-8 coil instead of three pickup coils (loop type coils) and operating the unit of drive coil and figure-8 coil (hereafter the unit) only in linear scanning mode. Fig. 1 shows the conceptual diagram of the proposed localization method using figure-8 coil. Figure-8 coil consists of two reverse-winding loop coils and is adjusted so that its initial bias (the voltage without sample) close to 0 V and fixed to the center of drive coil. As a result, the induced voltage changes depending on the relative position of the implant (i.e., magnetic particles) as seen from the unit when the implant moves along the longitudinal axis of figure-8 coil (x-axis) on xz-plane. Here, xyz and x’y’z’ are the coordinate systems of the unit (known) and the implant (unknown), respectively. That is, in actual localization, by monitoring the voltage during moving the unit linearly over the existence possibility area of the implant, it is possible to specify the symmetry plane of the implant (e.g., y’z’-plane which is perpendicular to the moving x-axis when the voltage is at the inflection point). Similarly, as shown in Fig. 1(b), by simply rotating the unit 90° counter-clockwise on xy-plane, and then moving the unit along the longitudinal axis of figure-8 coil, it is possible to specify the symmetry plane x’z’. Finally, for specifying the symmetry plane x’y’, rotating the unit 90° around y-axis counter-clockwise, and the resulting three symmetry plane intersect at the position of the implant. Next, we verified the validity of the proposed method using the constructed experimental setup as shown in Fig. 2(a). The strength and frequency of magnetic field applied at the center of drive coil (pancake coil, 40 turns, internal diameter 28.1 mm, external diameter 113.5 mm) were 2.88 mT and 2 kHz, respectively. The induced voltage in figure-8 coil (each loop 1 turn, diameter 10 mm) without the sample was subtracted from the induced voltage with the sample. The sample (1 g of magnetic particles dispersed in 1mL of deionized water) used in the following experiments was our previously-developed micromagnetic particles with a Curie point of 45°C [1]. As shown in Fig. 2(b), when the sample moved manually along the x-axis (z = 10 mm; y= 0 mm or -10mm), the average voltage (all experiments were repeated three times) changed depending on the position of sample, and the voltage was at the inflection point when the sample was directly above the intersection of two loops of figure-8 coil. In Fig. 2(c), when the sample moved along the y-axis (z = 10 mm; x= 0 mm), the voltage (almost 0 V) was extremely small compared to the one when the sample moved along the x-axis around the intersection of two loops of figure-8 coil (z = 10 mm; y= 0 mm). This means that the symmetric plane of the implant can be specified with high accuracy by using figure-8 coil. As shown in Fig. 2(d), with our currently constructed experimental setup, it is possible to detect the sample up to 5 cm from the unit. Future studies are needed to investigate the optimal design of drive coil and figure-8 coil to extend the detectable distance for deeper tumor.

**References:**

[1] L. Tonthat, Y. Yamamoto, F. Aki et al, IEEE Trans. Magn., Vol. 54(7), p. 5400506 (2018) [2] F. Aki, L. Tonthat, H. Saito et al, Electron. Comm. Jpn., Vol. 101 (6), p. 58–66 (2018) [3] L. Tonthat, K. Mitobe, S. Yabukami, IEEE Trans. Magn., Vol. 57(2), doi: 10.1109/TMAG.2020.3008490 (early access).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/eb9288a7a69c6bd175f360d34d4b58ed.jpg)
Fig. 1 The conceptual diagram of the proposed localization method for magnetic particles using a figure-8 coil. (a) The voltage changes depending on the relative position of the implant as seen from the unit when the implant moves along x-axis on xz-plane. (b) By simply rotating the unit 90° counter-clockwise on xy-plane, it is possible to specify the symmetry plane x’z’ and rotating the unit 90° around y-axis counter-clockwise for specifying the symmetry plane x’y’.

![](https://assets.underline.io/uploads/markdown_image/1/image/42c1dd14e9741c112ca8fe9f33ccc20e.png)
Fig. 2 (a) The constructed experimental setup and (b), (c), (d) the relationship between the average voltage (n=3) and the position of the sample when the sample moved manually above the fixed unit.

 A Simple Localization Method of Magnetic Particles for Hyperthermia Therapy using Figure-8 Coil

Introduction: Delivery of biological fluids and agents requires precision and can benefit from separation between substance and user for accurate results and safety, for example, in studies involving contagious organisms or viruses or when experimenting on sensitive cellular behaviors. Using a robot that contacts only the substance to be loaded and the unloading site provides that degree of separation needed for safety and study integrity. In this work, we demonstrate the use of optically powered diamagnetically levitated pyrolytic graphite robots with end effector micropipettes for a contact-free fluid delivery solution for use in biological studies. Specifically, we demonstrate loading, transporting, and releasing dyed water into agarose gel with autonomous control. Optical control of diamagnetically levitated PyG has been demonstrated in our previous work [1]. Using projector-based optical sources or independent control of laser beams, multiple samples may be controlled in parallel in an unsegmented workspace [2, 3]. An unsegmented workspace allows multiple robots to collaborate in a factory set-up with no extra circuitry or boundaries specific to each robot. All that is needed is a light source for each sample, which can be provided with a projector setup or a laser-splitting device. The alternative system design is the actuation of Neodymium-Iron Boron (NdFeB) magnets levitated on top of graphite [4, 5]. Control is achieved using active current traces in printed circuit boards under the graphite. This arrangement has segmented work surfaces, limited motion in close proximity, and requires extensive changes to expand the workspace. It also requires continuous power to ensure levitation and movement. In our work, the experimental setup includes PyG samples passively levitating on top of a checkerboard permanent magnet array. Instead of complicated circuitry, the displacement of the PyG robot is controlled using single laser sources for individual control. Given the low levitation height of the PyG, the load mass is constrained, which limits the end effectors and manipulands employed. With the contactless design, static end effectors, such as the micropipettes used in this study, are preferable. These micropipettes work on pressure differences, which keeps the system as autonomous as possible. The advantages that arise from a passively levitated, optically actuated platform are accompanied by loading and handling challenges and limitations. System Design: PyG, an artificial graphite, has the strongest known diamagnetism at room temperature, allowing it to levitate over an array of checkerboard permanent magnets at room temperature. Its large out-of-plane temperature-dependent diamagnetic susceptibility allows it to be actuated by localized temperature changes. Optical irradiation, such as that from a laser or projector, increases the local temperature, which decreases its local diamagnetic susceptibility, resulting in an in-plane force due to asymmetric out-of-plane forces and an induced tilting in the sample. In this study, a vision-based autonomously controlled laser source on a motorized stage irradiates the PyG sample, moving it towards the laser spot. The end effector micropipette is placed on the PyG sample, which is levitated on top of a magnet array, as shown in Fig. 1. The micropipette loads fluids from droplets placed on a glass slide via capillary action. A coefficient of penetration is used to determine the loadable fluids, while also considering adhesion between the glass slide and fluid to facilitate the retreat of the micropipette. To ensure liquid forces on the micropipette do not draw the PyG onto the droplet, a plastic barrier with holes that allow passage of the micropipette but not the PyG is placed at the edge of the magnet array. During the unloading process, the fluid diffuses when the micropipette penetrates an agarose gel. Experiment: Photographs taken during operation are shown in Fig. 2. In response to joystick user input, a motorized stage translates and moves the laser and levitated robot carrying a glass micropipette end effector (25-100µm dia.) fixed to the PyG with vacuum grease. The robot’s pipette approaches the fluid and loads within &lt;10 seconds for the liquid solutions tested (5% xylene cyanol, 1% bromophenol blue, 0.1M NaCl). To retreat, the stage for the fluid droplet is lowered mechanically, releasing the pipette. Laser power is insufficient to retreat the PyG from the fluid droplet after loading due to high surface tension forces. Once free of the droplet, the PyG is moved by the laser to the agarose at the unloading site. After penetration, diffusion of the fluid into the agarose is visible within 30s and takes several minutes to completely unload the pipette. The main focus for future work is process automation. Currently, the process is executed by a user with a joystick, but the future goal is to develop a single input program that will complete the whole process, including finding the robot and executing the loading and unloading procedure.

**References:**

 [1] M. Ewall-Wice, et al., IEEE Transactions on Magnetics 55.7 (2019): 1-6. [2] J. Young, et al. AIP Advances 9.12 (2019): 125038. [3] J. Young, et al. Proc. SPIE 112930S (2020). [4] E. E. Hunter, et al., IEEE Robotics and Automation Letters 4.2 (2019): 997-1004. [5] A. Hsu, et al., IEEE Robotics and Automation Letters 5.2 (2020): 2913-2920.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/b95426e192053b147205ba6b02cdb4cc.jpg)
Figure 1. Photograph of a micropipette (50µm inner diameter tip, overall length 10mm) placed on top of a levitated 15mmØ PyG sample.

![](https://assets.underline.io/uploads/markdown_image/1/image/6f2ee93f3564459652b63544d99b4958.jpg)
Figure 2. Photographs of the operation. The PyG sample is counterbalanced with a tip of toothpick. a) PyG approaches the fluid behind the wall. b) Micropipette loads the fluid, which is placed on a glass slide and a tilting stage. c) PyG retreats after the tilting stage is lowered. d) PyG moves towards agarose. e) Micropipette penetrates agarose. f) Fluid diffuses into agarose.

 Optically Powered Diamagnetically Levitated Robots for Biomedical Applications

A major fraction of airborne particulate matter is magnetic. The origin of these magnetic particles is anthropogenic (industry, traffic), and often accompanied by traces of very toxic heavy metal pollutants. The magnetic fraction of airborne particulate matter is therefore a good indicator for the amount of air pollution, and can serve as a first indicator for toxicity. We collected airborne magnetic particulate matter directly onto silicon substrates by means of a stack of permanent NdFeB magnets (Figure 1). Collection was performed in open air along a campus road for a period of 2-4 weeks. For comparison, a control substrate was mounted in a similar fashion, nearby but not on a magnet. The silicon substrates can be readily used in a variety of surface analysis techniques. The morphology of the captured particles was analyzed by optical and electron microscopy, as well as by AFM. The substrate that was on the magnet stack showed an increased amount of particles. The particle size varied from 50 micrometer down to diameters below 100 nm. Many of the particles are perfectly round spheres with a diameter of a few up to tens of micrometers. SEM-EDX analysis showed that particles that are captured magnetically mainly consist of iron-oxide. VSM analysis showed that the substrate that was on the magnet has a magnetic moment that is six times higher than the substrate that was not in the magnetic field gradient (Figure 2). The average collection of magnetic particulate matter on the 5mm×5mm area is approximately 4 nAm2/day, which translates to 46 ng/day if the particles are made entirely of iron-oxide. These experiments show that one can collect magnetic particulate matter directly from the air, without using filters and complex post-treatment procedures that change the particle composition and cause clustering. Magnetic particulate matter sampling is therefore a promising complementary technique that can be applied in for instance air quality monitoring stations.

**References:**



**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/11c6c4c908f151e15109ac69ec88de7b.jpg)
Fig 1. A stack of NdFeB magnets ranging in diameter from 70 down to 4 mm is used to attract magnetic particulate matter onto a 5 mm x 5 mm silicon substrates. The substrate is shielded from rain by a tube, and the magnets are protected by a PVC enclosure.

![](https://assets.underline.io/uploads/markdown_image/1/image/7752478b701390e1c101a1464837f6ef.jpg)
Fig. 2. The magnetic moment of the substrate that was outside on the magnet stack for a month (red curve) is at least six times higher than that of a substrate that was outside for the same period, but not on a magnet (blue curve). The reference (black curve) is the signal of a substrate that was kept in a box.

 Capture of magnetic particulate matter directly from air on silicon substrates

Transcranial Magnetic Stimulation (TMS) has proven in recent years to be an effective method for neuromodulation without surgical interventions. Such non-invasive stimulation treatment has been approved by the U.S. Federal Drug Administration (FDA) for treating major depressive disorder (MDD), obsessive compulsive disorder (OCD) and certain types of migraine headaches [1]. Current research is investigating the use of TMS for treating Parkinson’s Disease (PD) and Post-Traumatic Stress Disorder (PTSD) [2][3]. Despite the promise that TMS offers for non-invasive neuromodulation, most commercial TMS coils deliver a uniform H field to the brain. In the process of delivering a sufficiently strong H field to the targeted region, surrounding areas of the brain can be stimulated unnecessarily. Stimulating non-target areas can result in side effects ranging from tingling sensations in the scalp to seizures [4]. Due to this, the ability for conventional TMS coils to treat a wider variety of systemic neurological disorders is limited. We have developed a novel hybrid coil design that incorporates a traditional single circular coil with a group of 8 solenoids. This design, shown in Fig. 1, allows for a shapeable H field HHH in order to target a specific area for stimulation through selective activation of the solenoid architecture. By activating the solenoids with either a clockwise or counter-clockwise current of varying intensity, the H field of the overall coil can be shaped in a non-uniform manner. This shapeable architecture allows localized stimulation of various neural structures with less risk of stimulating non-target regions. This coil design also presents the possibility for patient-specific customized focality of the H field.

**References:**

[1] “FDA permits marketing of transcranial magnetic stimulation for treatment of obsessive compulsive disorder | FDA.” [Online]. Available: https://www.fda.gov/news-events/press-announcements/fda-permits-marketing-transcranial-magnetic-stimulation-treatment-obsessive-compulsive-disorder. [Accessed: 010-Jun-2020]. [2] C. Fricke et al., “Dual-Site Transcranial Magnetic Stimulation for the Treatment of Parkinson’s Disease,” Front. Neurol., vol. 10, no. March, pp. 1–9, 2019, doi: 10.3389/fneur.2019.00174. [3] R. J. Koek et al., “Neuromodulatory treatments for post-traumatic stress disorder (PTSD),” Prog. Neuro-Psychopharmacology Biol. Psychiatry, vol. 92, no. December 2018, pp. 148–160, 2019, doi: 10.1016/j.pnpbp.2019.01.004. [4] S. Rossi et al., “Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research,” Clin. Neurophysiol., vol. 120, no. 12, pp. 2008–2039, 2009.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/de93a530b8971e509db30b6d60d8325b.jpg)
Fig. 1. Hybrid circular-solenoid coil and simulation head model in Sim4Life software.

 Hybrid Coil Design for Shapeable Magnetic Field for Transcranial Magnetic Stimulation

In order to improve the spatial distribution characteristics of induced electromagnetic field, the eccentric trapezoidal magnetic coil (ETM coil) is designed based on the inspiration of special shaped magnets. And to overcome the overheat problem during repetitive stimulation, the inner cooling cycle is designed for the ETM coil as well. The proposed ETM coil consists of two identical coil units and each unit is in the shape of eccentric trapezoid when projected onto the plane parallel to stimulating target plane. The two coil units are placed adjacent or overlapped which is referred to as Type I-ETM coil and Type II-ETM coil in this paper, respectively. To limit the induced electromagnetic field within a smaller domain, the ETM coil is bent along the symmetrical axis at specific angles. Results show that the ETM coil can produce the same stimulation intensity as the traditional FOE coil with less driving current, and it can also significantly improve the intracranial stimulation focalization while reducing the risk of side effects. Because of the internal cooling design, the temperature of the ETM coil could be maintained at room temperature after 3000 effective pulses were applied, while the temperature rise of the FOE coil is over 40K. To verified our method, an anatomically realistic human head model with different electrical properties assigned to each tissue of the brain is employed in this paper. Index Terms- induced electromagnetic field, Magnetic Coil, stimulation intensity. Introduction Transcranial magnetic stimulation (TMS) has been proved to be an effective tool in medical researches[1], [2]. The stimulated volume or stimulated area within human brain need to be limited into a smaller domain to avoid unnecessary side effects [3]-[7]. Also, The geometry of the magnetic coil not only influences to the spatial distributions of induced field but also relates to the heating problem [8]. In order to provide reliable and efficient experimental conditions for scientific exploration, the eccentric trapezoidal magnetic coil (ETM coil) is introduced and optimized in this paper. Results prove that the ETM coil is superior to the traditional FOE coil in terms of stimulation performance and continuous working performance. Method A. The Geometry of ETM coil The ETM coil can be obtained by bending two eccentric trapezoidal coils along an axis of symmetry. When the two coil units are placed adjacent, the coil is referred as Type I-ETM coil and when the two coil units are placed overlapped, the coil is referred as Type II-ETM coil. In this paper, all ETM coil is described as a (mm), b (mm), θ° and φ°. a (mm) represents the length of upper side of the trapezoid. b represents the length of bottom side of the trapezoid. θ° represents the bottom corner of the trapezoid. φ° stands for the bending angle of the eccentric trapezoidal coil pair. The geometry the of Type I-ETM coil when projected to XY plane is shown in Fig. 1. The transparent red circle in Fig.1 represents the targeted plane below the ETM coil.The relative position between Type I-ETM coil and human head is shown in Fig.2. B. Real Human Head Model The real human head model used in this study is model numbered 101309 in the Population Head Model (PHM) Repository (https://itis.swiss/virtual-population/regional human-models/phm-repository/). The PHM repository was developed by Lee et al. using the SimNIBS pipeline, which was utilized to segment anatomical regions from Human Connectome Project MRI images. C．Optimization Steps Firstly, multiple Type I-ETM coil and Type II-ETM coils are construct under the power loss constraint. Both the Type I-ETM coil experimental group and Type II-ETM coil experimental group are divided into three sets including the a/b set, the θ° set and the φ° set. Secondly, the influence of coil geometry parameters on the spatial distribution of intracranial induced electromagnetic field was analyzed qualitatively. A mathematical model reflecting the mapping relationship between the geometric parameters of the coil and the spatial distribution characteristics of the intracranial induced electromagnetic field is established. Thirdly, the particle swarm optimization method (PSO) is adopted to obtain the optimized values of the ETM coil geometric parameters. Results prove that the overall performance of the optimum ETM coil is improved by about 40% comparing to the traditional FOE coil. Fourthly, the copper wire used in the optimum ETM coil is replaced with hollow copper wire and the central hollow part is used to circulate low-temperature deionized water. The pressure and temperature distribution on the cooling water channel is simulated based on non-isothermal water pipe model. Finally, the induced neurologic damage which may be caused during a typical treatment are calculated. Results In this paper, we have proposed and verified the ETM coil design for magnetic stimulation. Type I-ETM coil is advantageous in generating stronger induced field while the Type II-ETM coil is beneficial to improving the stimulation focalization. The bending structure of the ETM coil helps to reduce the risk of side effects. The overall performance of the optimum ETM coil is improved by about 40% comparing to the traditional FOE coil. And the inner cooling cycle of the optimum ETM coil makes it possible to work continuously without overheat. In conclusion, the proposed ETM coil is superior to the traditional FOE coil in terms of stimulation performance and continuous working performance which may bring more possibilities for the applications of TMS.

**References:**

References:: [1] B. J. Hand, G. M. Opie, S. K. Sidhu, et al. Brain Res., vol.1746, no.147027, July 2020. [2] C. C. Sanchez, M. R. Cabello, A. Q. Olozabal, J. Neural. Eng., vol. 17, no.016056, 2020. [3] Y. Wu, H. Yu, Z. Liu, IEEE Trans. Magn, vol. 54, no. 11, pp. 1–5, 2018. [4] Z. Zhang, W. Ai, B. Deng, IEEE Trans. Magn., vol. 53, no. 11, Nov. 2017, Art. no. 9100605 [5] S. Chang, et al. IEEE Trans. Magn, vol. 54, no. 11, pp. 1–5, 2018. [6] A.V. Peterchev, T.A. Wagner, Brain Stimul., vol. 5, pp.435–453, 2012. [7] G. Yi, J. Wang, X. Wei, Appl. Math. Comput. vol.231, pp.100-110, 2014. [8] V. Novickij, A. Grainys, J. Novickij, and A. Lucinskis, IEEE Trans. Magn., vol. 50, no. 11, Nov. 2014, Art. no. 5101004

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/5abd45ac41bd661b5723936f912f8c42.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/a79f51dfa70af3c9b5a3095eab239093.jpg)

 Optimum Design of the Eccentric Trapezoidal Magnetic Stimulation Coil with Trade-off between Stimulation Effect and Heat Dissipation

I. INTRODUCTION Magnetorheological (MR) fluids are suspensions of soft-magnetic particles dispersed in a non-magnetic liquid medium, such as silicone oil and mineral oil [1]. Their rheological behaviors can be tuned depending on either the presence or the absence of the applied magnetic field strength. Without an applied magnetic field, they behave like a Newtonian fluid while in the presence of the magnetic field, they become a solid-like a state [2], due to the fact that the dispersed magnetic particles are magnetically polarized and then form a chain structure [3]. When the external magnetic field is removed, they return to an original liquid-like state immediately. Based on this tunable and reversible characteristics, their potential applications cover the areas of robotics, haptic devices, and mechanical systems [4]. As for the MR material, carbonyl iron (CI) microspheres have been widely used because of their high saturation magnetization. However, their high density intrinsically possesses a sedimentation problem [5]. To improve this problem, several methods have been employed such as an introduction of additive particles and coating the CI with either polymers or inorganics [6]. In this work, as an additive material, zinc ferrite nanoparticles were synthesized by a surfactant-assistant solvothermal method and then added into CI-based MR fluid. By adding these particles with high magnetism to MR fluid consisting of fine CI particles, the MR effect is expected to be improved [7]. II. EXPERIMENT The ZnFe2O4 nanoparticles were synthesized by solvothermal synthesis method. Ferric chloride hexahydrate (5.4g) and zinc chloride (1.36g) were put into 200 ml ethylene glycol with stirring using a magnetic bar. After 45 min, the solution turned to be transparent yellow. Both sodium acetate (14.4g) and polyethylene glycol(4g) were then added, and reacted in an autoclave at 200°C for 12 h. The particles were separated using a magnet and washed several times with ethanol. Finally, the synthesized zinc ferrite nanoparticles were dried in a vacuum oven for a day. Morphology of nanoparticles was observed by scanning electron microscope. The CI particles (CM grade, BASF, average particle size: 4.5 m, density: 7.8 g/cm3) were then used as a main component for the MR fluids. The 0.5wt% of was added into 50wt% of CI based MR fluid, while CI-based MR fluid (50 wt%) dispersed in silicone oil (viscosity of 100cS) was also prepared for the comparison. Their MR characteristics were measured using a rotational rheometer under various magnetic field strengths. III. RESULT AND DISCUSSION Figure 1 presents SEM image of the morphology of particles, with a smooth surface and particle size distribution in 300-500nm range. The density of zinc ferrite particles was measured to be 4.8 g/cm3 by a pycnometer. Rheological response of shear stress as a function of shear rate of both MR fluids is presented in Figure 2 under a magnetic field strength range from 0 to 341 kA/m. Without a magnetic field, the MR fluid behaves like a Newtonian fluid. However when magnetic field strength was applied, the shear stress increased as the shear rate increased. MR properties of the CI/ZnFe2O4 based MR fluid (50/0.5wt %) showed a higher shear stress than that of CI-based MR fluid. Under the magnetic field applied, both MR fluids with and without an additive show similarly a wide plateau region which is attributed to the formed columns due to the strong dipole-dipole interaction among the magnetic particles. Additionally, we also measured the sedimentation ratio to confirm the role of zinc ferrite as an additive material for MR fluids through a Turbiscan optical analyser system. The CI-based MR fluid had a faster sedimentation rate than the CI/ZnFe2O4 based MR fluid, indicating that the dispersion stability of CI/ZnFe2O4 based MR fluids increased as compared to the CI based MR fluids. Improved dispersion stability is thought due to the fact that the nanoparticles fill the free space between the CI particles at the same time partially being coated on the surface of the CI particles, contributing to flow resistance. Therefore, in this work, the positive role of zinc ferrite as a proper additive for the CI based MR fluid is confirmed.

**References:**

[1] S. E. Premalatha, R. Chokkalingam and M. Mahendran, Am. J. Polym. Sci, 2, 50 (2012). [2] J. de Vicente, D. J. Klingenberg and R. H.Alvarez, Soft Matter, 7, 3701 (2011) [3] M. J. Hato, H. J. Choi and H. H. Sim, Colloids Surf. A-Physicochem. Eng. Asp, 377, 103 (2011) [4] C. Y. Gao, M. W. Kim, D. H. Bae, Polymer, 125, 21 (2017) [5] J. E. Kim, H. J. Choi, IEEE Trans. Magn, 47, 3173 (2011) [6] Y. Z. Dong, W. J. Han and H. J. Choi, J. Ind. Eng. Chem. 93, 210 (2021) [7] S. H. Piao, H. S. Chae, and H. J. Choi, IEEE Trans. Magn. 51,4600704 (2015)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/1f91e2fab6913903916978f67ff06c37.jpg)
Fig. 1 SEM images of ZnFe2O4 

![](https://assets.underline.io/uploads/markdown_image/1/image/3b0befb13c37f7fd19f325005c241177.jpg)
Fig. 2 Shear stress curves of both pure CI (closed) and CI/ZnFe2O4 (open) MR fluids at different magnetic field strengths

 Enhanced Magnetorheological Response of Particle Added Carbonyl Iron Suspension

I. INTRODUCTION Actively tunable smart magnetorheological (MR) fluids consisting of soft-magnetic particles suspended in nonmagnetic liquids like mineral oil or silicone oil [1], [2], have drawn extensive attentions with their many potential applications in mechanical engineering, biomedicine, pigments, and even in aerospace devices due to their controllable capability. They exhibit reverse and tunable rheological properties from Newtonian fluid-like to solid-like through applied magnetic field strengths employed within milliseconds order. Among extensive potential magnetic particles for their MR applications, soft-magnetic carbonyl iron (CI) microspheres possessing a large saturation magnetization value, proper size, and large permeability have brought lots of interests [3], [4]. However, CI particles are known to intrinsically possess the limitation of their usage with their much higher particle density than of the non-magnetic fluids, which may easily cause the sedimentation in the MR fluids. In this study, poly(2-methylaniline)(PMAN)-CI core-shell structured particles were synthesized by a chemical grafting method with dopamine hydrochloride as a grafting agent to enhance repulsive interaction or to decrease distance among CI microspheres. Dopamine was coordinated on the surface of magnetic particles by electro-donating bidentate enediol, combined with magnetic particles through a bidentate ligand reaction [5]. At this point, the amine groups of dopamine-modified CI particles can be further modified as functional groups. The morphology of the fabricated core-shell structured particles was examined by transmission electron microscopy and scanning electron microscopy. In addition, the rheological properties of MR fluids were measured by using a rotational rheometer under various magnetic field strengths. II. EXPERIMENT Before PMAN coating, the surface of CI particles was modified with dopamine hydrochloride to improve the affinity between magnetic CI particles and PMAN coated shell. At first, CI particles were dispersed in DI-water, and dopamine hydrochloride was mixed with ultrasonic stirring reaction solution for 12 h to promote dopamine coating. The unattached dopamine was then flushed with excess deionized water and hexane. The CI particles of the surface coating were dried in vacuum for 24 h. The dopamine-modified CI particles were dispersed in deionized water under ultrasonication for 30 min. PMAN was coated by polymerizing 2-methylaniline via a chemical oxidation process induced by ammonia peroxide in an acidic environment. We then added the mixture to poly(vinyl alcohol) dissolved in di-water, transfered the reaction solution to the reactor, and cooled it down. Aniline and ammonia peroxide were added to the reactor. The reaction was kept for 24 h and stirred at 300 rpm. When the reaction was complete, the resulting product was separated using a magnet and dried in a vacuum for 24 h. III. RESULTS AND DISCUSSION The SEM images of CI/PMAN core-shell particles are shown in Figure 1, in which the CI/PMAN particles exhibit a larger particle size because of the PMAN coated shell, compared to a smooth surface of the pristine CI particles. The MR behaviors of CI/PMAN based MR suspension were carried out using a rotational rheometer in a controlled shear rate mode under a series of applied magnetic field strengths from 0 to 342 kA/m. The shear stress increases with increasing shear rate, which implies that the MR fluid exhibits a Newtonian fluid-like behaviour without an external magnetic field as shown in Fig. 2. When the magnetic field was applied, the shear stress demonstrated a significant improvement because of the change from a liquid-like to solid-like behaviour of the MR fluid, followed by stepwise growth with the increase of magnetic field. For each magnetic field strength, the shear stress of MR suspension displayed a wide plateau region over the entire shear rate range. In addition, the shear stress with the external magnetic field of MR suspensions was also fitted with the Herschel-Bulkley model [6], [7] as follows: τ=τ0+KÝn where τ is the shear stress, τ0 represents the dynamic yield stress, is the shear rate, K and n represent the consistency index and power-law exponent, respectively. The relationship between the dynamic yield stressof PANI/CI and the magnetic field strength was observed by measuring the universal yield stress. Even though the saturation magnetization and density ofthe PMAN/CI particles were reduced by the introduction of a non-magnetic PMAN shell, their dispersion stability was observed to be improved according to the Turbiscan test by synthesizing the PMAN-coated CI particles. These results were attributed to the rough surface and low density of the core-shell structure PMAN/CI particles.

**References:**

[1] M. Mrlik, M. Ilcikova and V. Pavlinek, J. Colloid Interf. Sci., 396, 146 (2013). [2] D. J. Klingenberg and J. C. Ulicny, Int. J. Mod. Phys. B, 25, 911 (2011). [3] I. Bica, E. M. Anitas and L. Chirigiu, J. Ind. Eng. Chem. 56, 407 (2017). [4] F. F. Fang, Y. D. Liu and H. J. Choi, ACS Appl. Mater. Inter. 3, 3487 (2011). [5] C. J. Xu, K. M. Xu and H. W. Gu, J. Am. Chem. Soc. 126, 9938 (2004). [6] K. J. Son, Korea-Austral. Rheol. J. 30, 29 (2018). [7] Y. Seo and H. J. Choi, Korea-Austral. Rheol. J. 30, 317 (2018).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/bec31a3e9edbef50d5575e1aa353a6e2.jpg)
Fig.1 SEM images of CI (inset) and CI/PMAN core-shell particles

![](https://assets.underline.io/uploads/markdown_image/1/image/221c24a25d3c5b897f0ef4474fbb4ef1.jpg)
Fig.2 Flow curve of shear stress for CI-PMAN MR fluid under various magnetic field strengths as a function of shear rate

Development of individualized brain model and physical phantom of small animals for experimental verification of transcranial magnetic stimulation

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