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12 pages, 4094 KiB  
Article
High-Frequency Magnetic Pulse Generator for Low-Intensity Transcranial Magnetic Stimulation
by Seungjae Shin, Hyungeun Kim and Jinho Jeong
Electronics 2024, 13(16), 3160; https://doi.org/10.3390/electronics13163160 - 10 Aug 2024
Viewed by 258
Abstract
This paper presents a high-frequency (HF) magnetic pulse generator designed for low-intensity transcranial magnetic stimulation (LI-TMS) applications. HF pulse stimulation can induce a strong electric field with minimal current and enhance the penetration depth of the electric field in human tissue. The HF [...] Read more.
This paper presents a high-frequency (HF) magnetic pulse generator designed for low-intensity transcranial magnetic stimulation (LI-TMS) applications. HF pulse stimulation can induce a strong electric field with minimal current and enhance the penetration depth of the electric field in human tissue. The HF magnetic pulse generator was designed and fabricated using a microcontroller unit, gate driver, full-bridge coil driver, and stimulation coil. Measurements with a full-bridge circuit supply voltage of 10 V demonstrated an electric field intensity of 6.8 Vpp/m at a frequency of 1 MHz with a power dissipation of 2.45 W. Achieving a similar electric field intensity at a frequency of 100 kHz required approximately ten times the coil current. Additionally, a quasi-resonant LC load was introduced by connecting a capacitor in series with the stimulation coil, which set the resonant frequency to approximately 10% higher than the frequency of 1 MHz. This approach reduced the coil impedance, achieving higher current with the same bias supply voltage. Experimental results showed an enhanced electric field intensity of 19.1 Vpp/m with a supply voltage of only 1.8 V and reduced power dissipation of 1.11 W. The proposed HF pulse train with quasi-resonant coil system is expected to enable a low-power LI-TMS system. Full article
(This article belongs to the Section Circuit and Signal Processing)
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Figure 1

Figure 1
<p>Basic principles of the TMS system.</p>
Full article ">Figure 2
<p>Stimulation protocols. (<b>a</b>) Traditional theta burst stimulation. (<b>b</b>) Proposed high-frequency stimulation.</p>
Full article ">Figure 3
<p>Simulation of the electric field intensity in human gray matter. (<b>a</b>) Simulation structure. (<b>b</b>) Normalized <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> </mrow> </semantics></math> as a function of frequency. (<b>c</b>) Penetration depth of the electric field as a function of frequency.</p>
Full article ">Figure 4
<p>Block diagram of the proposed HF magnetic pulse generator.</p>
Full article ">Figure 5
<p>Schematic of the full-bridge circuit with boot-strapped gate driver.</p>
Full article ">Figure 6
<p>Simulated waveforms for the control signal (<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>C</mi> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math>–<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>C</mi> <mn>4</mn> </mrow> </msub> </mrow> </semantics></math>), the coil current (<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>L</mi> </mrow> </msub> </mrow> </semantics></math>), and the voltage across the coil (<math display="inline"><semantics> <mrow> <mo>Δ</mo> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>L</mi> </mrow> </msub> </mrow> </semantics></math>). (<b>a</b>) Triangular current wave. (<b>b</b>) Trapezoidal current wave.</p>
Full article ">Figure 7
<p>Simulated waveforms in the full-bridge circuit with (solid) and without (dot) bypass capacitor and damping resistor for <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>D</mi> <mi>D</mi> <mo>,</mo> <mi>F</mi> </mrow> </msub> </mrow> </semantics></math> = 10 V and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>D</mi> <mi>D</mi> <mo>,</mo> <mi>G</mi> <mi>D</mi> </mrow> </msub> </mrow> </semantics></math> = 5.5 V. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>D</mi> <mi>D</mi> <mo>,</mo> <mi>F</mi> <mi>i</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>G</mi> <mi>S</mi> <mo>,</mo> <mi>U</mi> </mrow> </msub> </mrow> </semantics></math>, and (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>L</mi> <mo>,</mo> <mi>c</mi> <mi>o</mi> <mi>i</mi> <mi>l</mi> </mrow> </msub> </mrow> </semantics></math> at 100 kHz. (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>D</mi> <mi>D</mi> <mo>,</mo> <mi>F</mi> <mi>i</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>G</mi> <mi>S</mi> <mo>,</mo> <mi>U</mi> </mrow> </msub> </mrow> </semantics></math>, and (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>L</mi> <mo>,</mo> <mi>c</mi> <mi>o</mi> <mi>i</mi> <mi>l</mi> </mrow> </msub> </mrow> </semantics></math> at 1 MHz.</p>
Full article ">Figure 8
<p>(<b>a</b>) Fabricated HF magnetic pulse generator. (<b>b</b>) Fabricated stimulation coil.</p>
Full article ">Figure 9
<p>Measurement setup for the induced electric field intensity.</p>
Full article ">Figure 10
<p>Measured waveforms for the inductor load with DC bias voltages, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>D</mi> <mi>D</mi> <mo>,</mo> <mi>F</mi> </mrow> </msub> </mrow> </semantics></math> = 10 V and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>D</mi> <mi>D</mi> <mo>,</mo> <mi>G</mi> <mi>D</mi> </mrow> </msub> </mrow> </semantics></math> = 5.5 V. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>L</mi> <mo>,</mo> <mi>c</mi> <mi>o</mi> <mi>i</mi> <mi>l</mi> </mrow> </msub> </mrow> </semantics></math> and (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>i</mi> <mi>n</mi> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> at 100 kHz. (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>L</mi> <mo>,</mo> <mi>c</mi> <mi>o</mi> <mi>i</mi> <mi>l</mi> </mrow> </msub> </mrow> </semantics></math> and (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>i</mi> <mi>n</mi> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> at 1 MHz.</p>
Full article ">Figure 11
<p>Measured waveforms for the quasi-resonant LC load at the frequency of 1 MHz with DC bias voltages, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>D</mi> <mi>D</mi> <mo>,</mo> <mi>F</mi> </mrow> </msub> <mo>=</mo> </mrow> </semantics></math> 1.8 V and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>D</mi> <mi>D</mi> <mo>,</mo> <mi>G</mi> <mi>D</mi> </mrow> </msub> <mo>=</mo> </mrow> </semantics></math> 5.5 V. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>L</mi> <mo>,</mo> <mi>L</mi> <mi>C</mi> </mrow> </msub> </mrow> </semantics></math> and (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>E</mi> </mrow> <mrow> <mi>i</mi> <mi>n</mi> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
Full article ">
17 pages, 6933 KiB  
Article
Evidence for a Giant Magneto-Electric Coupling in Bulk Composites with Coaxial Fibers of Nickel–Zinc Ferrite and PZT
by Bingfeng Ge, Jitao Zhang, Sujoy Saha, Sabita Acharya, Chaitrali Kshirsagar, Sidharth Menon, Menka Jain, Michael R. Page and Gopalan Srinivasan
J. Compos. Sci. 2024, 8(8), 309; https://doi.org/10.3390/jcs8080309 - 8 Aug 2024
Viewed by 350
Abstract
This report is on magneto-electric (ME) interactions in bulk composites with coaxial fibers of nickel–zinc ferrite and PZT. The core–shell fibers of PZT and Ni1−xZnxFe2O4 (NZFO) with x = 0–0.5 were made by electrospinning. Both kinds [...] Read more.
This report is on magneto-electric (ME) interactions in bulk composites with coaxial fibers of nickel–zinc ferrite and PZT. The core–shell fibers of PZT and Ni1−xZnxFe2O4 (NZFO) with x = 0–0.5 were made by electrospinning. Both kinds of fibers, either with ferrite or PZT core and with diameters in the range of 1–3 μm were made. Electron and scanning probe microscopy images indicated well-formed fibers with uniform core and shell structures and defect-free interface. X-ray diffraction data for the fibers annealed at 700–900 °C did not show any impurity phases. Magnetization, magnetostriction, ferromagnetic resonance, and polarization P versus electric field E measurements confirmed the ferroic nature of the fibers. For ME measurements, the fibers were pressed into disks and rectangular platelets and then annealed at 900–1000 °C for densification. The strengths of strain-mediated ME coupling were measured by the H-induced changes in remnant polarization Pr and by low-frequency ME voltage coefficient (MEVC). The fractional change in Pr under H increased in magnitude, from +3% for disks of NFO–PZT to −82% for NZFO (x = 0.3)-PZT, and a further increase in x resulted in a decrease to a value of −3% for x = 0.5. The low-frequency MEVC measured in disks of the core–shell fibers ranged from 6 mV/cm Oe to 37 mV/cm Oe. The fractional changes in Pr and the MEVC values were an order of magnitude higher than for bulk samples containing mixed fibers with a random distribution of NZFO and PZT. The bulk composites with coaxial fibers have the potential for use as magnetic field sensors and in energy-harvesting applications. Full article
(This article belongs to the Special Issue Discontinuous Fiber Composites, Volume III)
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Figure 1

Figure 1
<p>X-ray diffraction patterns for the coaxial fibers of (<b>a</b>) NZFO (x = 0)-PZT and (<b>b</b>) NZFO (x = 0.3)-PZT. Small impurities are indicated by *. (<b>c</b>) SEM image showing a collection of the fibers of NFO-PZT. (<b>d</b>) SEM image showing the core and shell structure for an NFO-PZT fiber.</p>
Full article ">Figure 2
<p>(<b>a</b>) Atomic force microscopy image of an isolated coaxial fiber of NFO-PZT. (<b>b</b>) Magnetic force microscopy for a fiber of NFO shell–PZT core. (<b>c</b>) Scanning microwave microscopy (SMM) capacitance image at 10 GHz for NFO-PZT fiber.</p>
Full article ">Figure 3
<p>Magnetization vs. static magnetic field H data for the bulk samples with the fibers of (<b>a</b>) NFO-PZT, (<b>b</b>) NZFO (x = 0.2)-PZT, and (<b>c</b>) NZFO (x = 0.4)-PZT. The data are for the samples with ferrite core and PZT shell.</p>
Full article ">Figure 4
<p>(<b>a</b>) Scattering matrix parameter S<sub>11</sub> vs. frequency f for ferromagnetic resonance (FMR) for a series of in-plane static magnetic field H. The data are for a rectangular platelet of the coaxial fibers of NZFO (x = 0.2) and PZT. (<b>b</b>) The fitting of the resonance frequency f<sub>r</sub> vs. H to Kittel’s equation to determine the gyromagnetic ratio γ and the effective saturation induction 4πM<sub>eff</sub>.</p>
Full article ">Figure 5
<p>Profiles showing FMR (<b>a</b>) and the fitting of f<sub>r</sub> vs. H data to Kittel’s equation (<b>b</b>) as in <a href="#jcs-08-00309-f004" class="html-fig">Figure 4</a> for a platelet with the fibers of NZFO (x = 0.3)-PZT.</p>
Full article ">Figure 6
<p>Magnetostriction λ<sub>11</sub> measured parallel to the applied in-plane static magnetic field H. The data are for a rectangular platelet made of the coaxial fibers of NZFO (x = 0.5)-PZT (<b>a</b>,<b>b</b>) and NZFO (x = 0.4)-PZT (<b>c</b>,<b>d</b>). The arrows indicate increasing or decreasing H direction. The arrows represent the increasing and decreasing magnitude of H variation.</p>
Full article ">Figure 7
<p>λ<sub>11</sub> vs. H data as in <a href="#jcs-08-00309-f004" class="html-fig">Figure 4</a> for NZFO (x = 0.3)-PZT (<b>a</b>,<b>b</b>) and NZFO (x = 0.2)-PZT (<b>c</b>,<b>d</b>). The arrows represent the increasing and decreasing magnitude of H variation.</p>
Full article ">Figure 8
<p>Polarization P as a function of electric field E for a series of applied static magnetic field H for a disk with the fibers of NZFO (x = 0.5) core–PZT shell for (<b>a</b>) increasing H and (<b>b</b>) decreasing H. (<b>c</b>,<b>d</b>) show similar results for fibers with PZT cores and NZFO (x = 0.5) shells. The insets show P vs. E on an expanded scale. (<b>e</b>) The fractional change in the remnant polarization Pr as a function of H for increasing and decreasing H. PZT (<b>a</b>,<b>b</b>) and NZFO (x = 0.5)-PZT (<b>c</b>,<b>d</b>). The arrows indicate increasing or decreasing H direction.</p>
Full article ">Figure 9
<p>Polarization P as a function of electric field E for a series of applied static magnetic field H for a disk with the fibers of NZFO (x = 0.4) core–PZT shell for (<b>a</b>) increasing H and (<b>b</b>) decreasing H. (<b>c</b>,<b>d</b>) show similar results for fibers with PZT cores and NZFO (x = 0.4) shells. The insets show P vs. E on an expanded scale. (<b>e</b>) The fractional change in the remnant polarization Pr as a function of H for increasing and decreasing H. The arrows represent the increasing and decreasing magnitude of H variation. The inset shows data on expanded scale.</p>
Full article ">Figure 10
<p>Results on P vs. E for a series of (<b>a</b>,<b>c</b>) increasing H-values and (<b>b</b>,<b>d</b>) decreasing H-values for a platelet with the core–shell fibers of NZFO (x = 0.3)-PZT. (<b>e</b>) Fractional change in P<sub>r</sub> vs H for the core-shell fiber disks. The arrows represent the increasing and decreasing magnitude of H variation.</p>
Full article ">Figure 11
<p>Zn concentration x dependence of the maximum fractional variation in the remnant polarization in the bulk composites with NZFO-PZT core–shell fibers.</p>
Full article ">Figure 12
<p>ME voltage coefficient α<sub>31</sub> measured at 100 Hz as a function of the bias field H for the samples with the fibers of NZFO (x = 0.5)-PZT and NZFO (x = 0.4)-PZT. The insets show the H-dependence of α<sub>31</sub> on an expanded scale for H &lt; 1 kOe. (<b>a</b>,<b>c</b>) are for fibers with ferrite core and (<b>b</b>,<b>d</b>) are for fibers with PZT core. Arrows indicate data for increasing and decreasing magnitude of H.</p>
Full article ">Figure 13
<p>Data as in <a href="#jcs-08-00309-f012" class="html-fig">Figure 12</a> for samples of NZFO (x = 0.3)-PZT and NZFO (x = 0.2)-PZT. (<b>a</b>,<b>c</b>) are for fibers with ferrite core and (<b>b</b>,<b>d</b>) are for fibers with PZT core. Arrows indicate data for increasing and decreasing magnitude of H.</p>
Full article ">Figure 14
<p>Data as in <a href="#jcs-08-00309-f012" class="html-fig">Figure 12</a> for bulk composites with NFO-PZT fibers. Data in (<b>a</b>) are for fibers with ferrite core and data in (<b>b</b>) are for fibers with PZT core. Arrows indicate data for increasing and decreasing magnitude of H.</p>
Full article ">Figure 15
<p>Maximum fractional H-induced change in P<sub>r</sub> as a function of x in the fiber samples with randomly distributed NZFO-PZT.</p>
Full article ">
8 pages, 2537 KiB  
Communication
Valley Spin–Polarization of MoS2 Monolayer Induced by Ferromagnetic Order in an Antiferromagnet
by Chun-Wen Chan, Chia-Yun Hsieh, Fang-Mei Chan, Pin-Jia Huang and Chao-Yao Yang
Materials 2024, 17(16), 3933; https://doi.org/10.3390/ma17163933 - 8 Aug 2024
Viewed by 307
Abstract
Transition metal dichalcogenide (TMD) monolayers exhibit unique valleytronics properties due to the dependency of the coupled valley and spin state at the hexagonal corner of the first Brillouin zone. Precisely controlling valley spin-polarization via manipulating the electron population enables its application in valley-based [...] Read more.
Transition metal dichalcogenide (TMD) monolayers exhibit unique valleytronics properties due to the dependency of the coupled valley and spin state at the hexagonal corner of the first Brillouin zone. Precisely controlling valley spin-polarization via manipulating the electron population enables its application in valley-based memory or quantum technologies. This study uncovered the uncompensated spins of the antiferromagnetic nickel oxide (NiO) serving as the ferromagnetic (FM) order to induce valley spin-polarization in molybdenum disulfide (MoS2) monolayers via the magnetic proximity effect (MPE). Spin-resolved photoluminescence spectroscopy (SR-PL) was employed to observe MoS2, where the spin-polarized trions appear to be responsible for the MPE, leading to a valley magnetism. Results indicate that local FM order from the uncompensated surface of NiO could successfully induce significant valley spin-polarization in MoS2 with the depolarization temperature approximately at 100 K, which is relatively high compared to the related literature. This study reveals new perspectives in that the precise control over the surface orientation of AFMs serves as a crystallographic switch to activate the MPE and the magnetic sustainability of the trion state is responsible for the observed valley spin-polarization with the increasing temperature, which promotes the potential of AFM materials in the field of exchange-coupled Van der Waals heterostructures. Full article
(This article belongs to the Section Materials Physics)
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Optical microscope image of the MoS<sub>2</sub> monolayers distributed on the sapphire surface. (<b>b</b>) Raman spectrum acquired by the MoS<sub>2</sub> monolayer in (<b>a</b>). (<b>c</b>) Topographic image of MoS<sub>2</sub> monolayer taken by an atomic force microscope together with (<b>d</b>) step height of approximately 0.744 nm taken at its edge, as marked by the blue line. The red dots in (<b>c</b>) correspond to the red dots in (<b>d</b>) to mark the positions for step height scan.</p>
Full article ">Figure 2
<p>(<b>a</b>) Crystal and magnetic structure of NiO substrate exhibiting the rock-salt structure and the G-type AFM texture, respectively, in which the unit cell of rock-salt structure was highlighted by the color and dashed line. The FM and AFM orders of NiO can be observed on the (111)-terminated and (001)-terminated surfaces, corresponding to the uncompensated and compensated plane of NiO. (<b>b</b>) Raman spectra and (<b>c</b>) PL spectra acquired from the MoS<sub>2</sub> monolayers on Al<sub>2</sub>O<sub>3</sub> and NiO<sub>(111)</sub> substrate.</p>
Full article ">Figure 3
<p>(<b>a</b>) SR-PL spectra of MoS<sub>2</sub> monolayers on NiO(111) taken at various temperatures. (<b>b</b>) SR-PL spectra of MoS<sub>2</sub> monolayers on NiO<sub>(001)</sub> taken at 4 K. (<b>c</b>) Plots of the degrees of valley spin-polarization at T and A states acquired from the MoS<sub>2</sub> monolayers on NiO<sub>(111)</sub> and NiO<sub>(001)</sub> at various temperatures to reveal the depolarization temperature. Temperature during the measurement was precisely controlled using a cryostat with liquid helium.</p>
Full article ">Figure 4
<p>Schematic diagram to demonstrate the spin configuration of trion with (<b>a</b>) MPE-induced valley spin-polarization via preferred population to T(↑) driven by (111)-terminated NiO surface and (<b>b</b>) neutral population driven by (001)-terminated NiO surface. Arrows at the bottom in (<b>a</b>,<b>b</b>) present the spin configuration on the (111)- and (001)-terminated NiO surface.</p>
Full article ">
25 pages, 22466 KiB  
Article
Comparative In Vitro Study between Biocompatible Chitosan-Based Magnetic Nanocapsules and Liposome Formulations with Potential Application in Anti-Inflammatory Therapy
by Gabriela Vochița, Anca Niculina Cadinoiu, Delia-Mihaela Rață, Leonard Ionuț Atanase, Marcel Popa, Athar Mahdieh, Cosmin-Teodor Mihai, Alexandru-Bogdan Stache, Cristina-Veronica Moldovan, Elena Simona Băcăiţă, Iustina Petra Condriuc and Daniela Gherghel
Int. J. Mol. Sci. 2024, 25(15), 8454; https://doi.org/10.3390/ijms25158454 - 2 Aug 2024
Viewed by 437
Abstract
This study describes the comparison between the interaction of a series of peptide-functionalized chitosan-based nanocapsules and liposomes with two cell lines, i.e., mouse macrophages RAW 264.7 and human endothelial cells EA.hy926. Both types of nanocarriers are loaded with magnetic nanoparticles and designed for [...] Read more.
This study describes the comparison between the interaction of a series of peptide-functionalized chitosan-based nanocapsules and liposomes with two cell lines, i.e., mouse macrophages RAW 264.7 and human endothelial cells EA.hy926. Both types of nanocarriers are loaded with magnetic nanoparticles and designed for anti-inflammatory therapy. The choice of these magnetic nanostructures is argued based on their advantages in terms of size, morphology, chemical composition, and the multiple possibilities of modifying their surface. Moreover, active targeting might be ensured by using an external magnetic field. To explore the impact of chitosan-based nanocapsules and liposomes on cell cytophysiology, the cell viability, using the MTT assay, and cell morphology were investigated. The results revealed low to moderate cytotoxicity of free nanocapsules and significant cytotoxicity induced by chitosan-coated liposomes loaded with dexamethasone, confirming its release from the delivery system. Thus, after 48 h of treatment with nanocapsules, the viability of RAW 264.7 cells varied between 88.18% (OCNPM-1I, 3.125 µg/mL) and 76.37% (OCNPM-1, 25 µg/mL). In the same conditions, EA.hy926 cell viability was between 99.91% (OCNPM-3, 3.125 µg/mL) and 75.15% (OCNPM-3, 25 µg/mL) at the highest dose (25 µg/mL), the values being comparable for both cell lines. Referring to the cell reactivity after dexamethasone-loaded liposome application, the lowest viability of RAW 264.7 cells was 41.25% (CLDM5CP-1, 25 µg/mL) and 58.20% (CLDMM2CP-1 1.25 µg/mL) in the endothelial cell line, proving a selective character of action of nanocarriers. The cell morphology test, performed to support and confirm the results obtained by the MTT test, revealed a differentiated response for the two types of nano-carriers. As expected, an intense cytotoxic effect in the case of dexamethasone-loaded liposomes and a lack of cytotoxicity for drug-free nanocapsules were noticed. Therefore, our study demonstrated the biocompatible feature of the studied nanocarriers, which highlights them for future research as potential drug delivery systems for pharmacological applications, including anti-inflammatory therapy. Full article
(This article belongs to the Special Issue Biopolymers for Enhanced Health Benefits—2nd Edition)
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Figure 1

Figure 1
<p>Release efficiency results of free Dex-P and Dex-P from nanocapsules in PBS solution with pH = 7.4.</p>
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<p>The amount of drug released (µg) from magnetic cationic liposomes coated with chitosan, up to 24 h.</p>
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<p>Effect of 24 and 48 h treatment with different concentrations of chitosan-based nanocapsules with magnetic particles on the viability of RAW 264.7 mouse macrophages. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 4
<p>Effect of 24 and 48 h treatment with different concentrations of chitosan-based nanocapsules with magnetic particles on the viability of EA.hy926 human endothelial cells. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 5
<p>Effect of 24 and 48 h treatment with magnetic cationic liposomes, in different concentrations, on the viability of RAW 264.7 mouse macrophages. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effect of 24 and 48 h treatment with magnetic cationic liposomes, in different concentrations, on the viability of EA.hy926 human endothelial cells. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>The morphology of the EA.hy926 cells after 24 and 48 h of OCNPM-1 treatment.</p>
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<p>The morphology of the EA.hy926 cells after 24 and 48 h of OCNPM-1I treatment.</p>
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<p>The morphology of the EA.hy926 cells after 24 and 48 h of OCNPM-3 treatment.</p>
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<p>The morphology of the EA.hy926 cells after 24 and 48 h of OCNPM-3I treatment.</p>
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<p>The morphology of the EA.hy926 cells after 24 and 48 h of CLDM5CP-1 treatment.</p>
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<p>The morphology of the EA.hy926 cells after 24 and 48 h of CLDM5CP-2 treatment.</p>
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<p>The morphology of the EA.hy926 cells after 24 and 48 h of CLDM5CP-3 treatment.</p>
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<p>The morphology of the EA.hy926 cells after 24 and 48 h of CLDM2CP-1 treatment.</p>
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<p>The morphology of the EA.hy926 cells after 24 and 48 h of CLDMM2CP-1 treatment.</p>
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<p>Comparative analysis of the EA.hy926 human endothelial cell viability influenced by 24 and 48 h treatment with magnetic cationic liposomes, in different concentrations. Statistical significance was determined by Tukey post hoc multiple comparison test (ns—nonsignificant, * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001).</p>
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<p>Comparative analysis of the RAW 264.7 macrophage viability influenced by 24 and 48 h treatment with magnetic cationic liposomes, in different concentrations. Statistical significance was determined by Tukey post hoc multiple comparison test (ns—nonsignificant, * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001).</p>
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17 pages, 3450 KiB  
Article
Evaluation of Superparamagnetic Fe3O4-Ag Decorated Nanoparticles: Cytotoxicity Studies in Human Fibroblasts (HFF-1) and Breast Cancer Cells (MCF-7)
by Álvaro de Jesús Ruíz-Baltazar, Simón Yobanny Reyes-López, Néstor Méndez-Lozano and Karla Juárez-Moreno
Appl. Sci. 2024, 14(15), 6750; https://doi.org/10.3390/app14156750 - 2 Aug 2024
Viewed by 405
Abstract
This study investigates the cytotoxicity profile of superparamagnetic Fe3O4-Ag decorated nanoparticles against human fibroblasts (HFF-1) and breast cancer cells (MCF-7). The nanoparticles underwent comprehensive characterization employing scanning electron microscopy (SEM), X-ray diffraction (XRD) analysis, X-ray photoelectron spectroscopy (XPS), and [...] Read more.
This study investigates the cytotoxicity profile of superparamagnetic Fe3O4-Ag decorated nanoparticles against human fibroblasts (HFF-1) and breast cancer cells (MCF-7). The nanoparticles underwent comprehensive characterization employing scanning electron microscopy (SEM), X-ray diffraction (XRD) analysis, X-ray photoelectron spectroscopy (XPS), and magnetic assays including hysteresis curves and zero-field-cooled (ZFC) plots. The nanoparticles exhibited superparamagnetic behavior as evidenced by magnetic studies. Cytotoxicity assays demonstrated that both HFF-1 and MCF-7 cells maintained nearly 100% viability upon nanoparticle exposure, underscoring the outstanding biocompatibility of Fe3O4/Ag decorated nanoparticles and suggesting their potential utility in biomedical applications such as drug delivery and magnetic targeting. Furthermore, the study analyzed the cytotoxic effects of Fe3O4 and Fe3O4-Ag decorated nanoparticles to evaluate their biocompatibility for further therapeutic efficacy. Results showed that neither type of nanoparticle significantly reduced cell viability in HFF-1 fibroblasts, indicating non-cytotoxicity at the tested concentrations. Similarly, MCF-7 breast cancer cells did not exhibit a significant change in viability when exposed to different nanoparticle concentrations, highlighting the compatibility of these nanoparticles with both healthy and cancerous cells. Additionally, the production of reactive oxygen species (ROS) by cells exposed to the nanoparticles was examined to guarantee their biosafety for further therapeutic potential. Higher concentrations (50–100 μg/mL) of Fe3O4-Ag nanoparticles decreased ROS production in both HFF-1 and MCF-7 cells, while Fe3O4 nanoparticles were more effective in generating ROS. This differential response suggests that Fe3O4-Ag nanoparticles might modulate oxidative stress more effectively, thus beneficial for future anticancer strategies due to cancer cells’ susceptibility to ROS-induced damage. These findings contribute to understanding nanoparticle interactions with cellular oxidative mechanisms, which are crucial for developing safe and effective nanoparticle-based therapies. This investigation advances our understanding of nanostructured materials in biological settings and highlights their promising prospects in biomedicine. Full article
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<p>SEM micrographs depicting the Fe<sub>3</sub>O<sub>4</sub>-Ag nanoparticle sample. (<b>a</b>) SE-HA ima.e showing nanoparticle topology and the presence of Fe<sub>3</sub>O<sub>4</sub> and Ag phases. (<b>b</b>) SE(U) image confirming Fe<sub>3</sub>O<sub>4</sub> and Ag presence, providing high-resolution surface details. (<b>c</b>) HA(T) image emphasizing Fe<sub>3</sub>O<sub>4</sub>-Ag formation. (<b>d</b>) SE + HA + OFF composite image displaying surface morphology and elemental composition. Magnification: ×500k; Working distance: 3.7 mm; Acceleration voltage: 3.0 kV. (<b>e</b>) Scheme of the distribution of Fe<sub>3</sub>O<sub>4</sub> and Ag nanostructures corresponding to the decorated type Fe<sub>3</sub>O<sub>4</sub>-Ag nanoparticle samples.</p>
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<p>Chemical Analysis of Fe<sub>3</sub>O<sub>4</sub>-Ag Decorated Nanoparticles. (<b>a</b>) SE image of Fe<sub>3</sub>O<sub>4</sub>. (<b>b</b>) Elemental mapping showing Ag distribution, confirming Fe<sub>3</sub>O<sub>4</sub>-Ag structure. Elemental mappings of Fe, O, and Ag from SE image of Fe<sub>3</sub>O<sub>4</sub> are in (<b>c</b>–<b>e</b>). (<b>f</b>) Chemical analysis confirms Fe, O, and Ag composition.</p>
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<p>Experimental X-ray Diffraction (XRD) Pattern of the Fe<sub>3</sub>O<sub>4</sub>-Ag Decorated Nanoparticles.</p>
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<p>Magnetic Characterization of Fe<sub>3</sub>O<sub>4</sub>/Ag Nanoalloys. (<b>a</b>) Hysteresis curve analysis at 300 K confirms superparamagnetic behavior in Fe<sub>3</sub>O<sub>4</sub>/Ag nanoalloys, with negligible magnetic coercivity and a magnetization value of 47 emu/g. (<b>b</b>) Zero-field-cooled (ZFC) curve depicts superparamagnetic behavior across temperatures, with a broad peak indicating the average blocking temperature.</p>
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<p>XPS Spectra of Fe<sub>3</sub>O<sub>4</sub>-Ag Decorated Nanostructures: (<b>a</b>) Survey Spectra, (<b>b</b>) HR-XPS of Fe 2p, (<b>c</b>) O 1s, and (<b>d</b>) Ag 3d.</p>
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<p>Cell viability assay of Fe<sub>3</sub>O<sub>4</sub> and Fe<sub>3</sub>O<sub>4</sub>-Ag decorated nanoparticles on (<b>a</b>) human fibroblast (HFF-1), and (<b>b</b>) breast cancer (MCF-7) cells. The cell viability results are expressed as the mean of cell viability percentage ± the standard deviation from three independent experiments. Statistical analysis was performed using two-way ANOVA followed by Tukey’s multiple comparison test. Significance was indicated as * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>ROS measurement production induced by Fe<sub>3</sub>O<sub>4</sub> and Fe<sub>3</sub>O<sub>4</sub>-Ag decorated nanoparticles on (<b>a</b>) human fibroblast (HFF-1) and (<b>b</b>) breast cancer cells (MCF-7). Statistical analysis was performed using two-way ANOVA followed by Tukey’s multiple comparison test. Statistical significance was indicated as * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>(<b>a</b>) Hemolysis of erythrocytes and (<b>b</b>) nitrite production in macrophages induced by Fe<sub>3</sub>O<sub>4</sub> and Fe<sub>3</sub>O<sub>4</sub>-Ag decorated nanoparticles. Statistical analysis was performed using two-way ANOVA followed by Tukey’s multiple comparison test. Statistical significance was indicated as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &gt; 0.001 and **** <span class="html-italic">p</span> &gt; 0.0001.</p>
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<p>Zeta potential graph of Fe<sub>3</sub>O<sub>4</sub> nanoparticles as a function of pH.</p>
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15 pages, 3036 KiB  
Article
Self-Assembly of Three-Dimensional Hyperbranched Magnetic Composites and Application in High-Turbidity Water Treatment
by Yuan Zhao, Qianlong Fan, Yinhua Liu, Junhui Liu, Mengcheng Zhu, Xuan Wang and Ling Shen
Molecules 2024, 29(15), 3639; https://doi.org/10.3390/molecules29153639 - 1 Aug 2024
Viewed by 404
Abstract
In order to improve dispersibility, polymerization characteristics, chemical stability, and magnetic flocculation performance, magnetic Fe3O4 is often assembled with multifarious polymers to realize a functionalization process. Herein, a typical three-dimensional configuration of hyperbranched amino acid polymer (HAAP) was employed to [...] Read more.
In order to improve dispersibility, polymerization characteristics, chemical stability, and magnetic flocculation performance, magnetic Fe3O4 is often assembled with multifarious polymers to realize a functionalization process. Herein, a typical three-dimensional configuration of hyperbranched amino acid polymer (HAAP) was employed to assemble it with Fe3O4, in which we obtained three-dimensional hyperbranched magnetic amino acid composites (Fe3O4@HAAP). The characterization of the Fe3O4@HAAP composites was analyzed, for instance, their size, morphology, structure, configuration, chemical composition, charged characteristics, and magnetic properties. The magnetic flocculation of kaolin suspensions was conducted under different Fe3O4@HAAP dosages, pHs, and kaolin concentrations. The embedded assembly of HAAP with Fe3O4 was constructed by the N–O bond according to an X-ray photoelectron energy spectrum (XPS) analysis. The characteristic peaks of –OH (3420 cm−1), C=O (1728 cm−1), Fe–O (563 cm−1), and N–H (1622 cm−1) were observed in the Fourier transform infrared spectrometer (FTIR) spectra of Fe3O4@HAAP successfully. In a field emission scanning electron microscope (FE-SEM) observation, Fe3O4@HAAP exhibited a lotus-leaf-like morphological structure. A vibrating sample magnetometer (VSM) showed that Fe3O4@HAAP had a relatively low magnetization (Ms) and magnetic induction (Mr); nevertheless, the ferromagnetic Fe3O4@HAAP could also quickly respond to an external magnetic field. The isoelectric point of Fe3O4@HAAP was at 8.5. Fe3O4@HAAP could not only achieve a 98.5% removal efficiency of kaolin suspensions, but could also overcome the obstacles induced by high-concentration suspensions (4500 NTU), high pHs, and low fields. The results showed that the magnetic flocculation of kaolin with Fe3O4@HAAP was a rapid process with a 91.96% removal efficiency at 0.25 h. In an interaction energy analysis, both the UDLVO and UEDLVO showed electrostatic repulsion between the kaolin particles in the condition of a flocculation distance of <30 nm, and this changed to electrostatic attraction when the separation distance was >30 nm. As Fe3O4@ HAAP was employed, kaolin particles could cross the energy barrier more easily; thus, the fine flocs and particles were destabilized and aggregated further. Rapid magnetic separation was realized under the action of an external magnetic field. Full article
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Graphical abstract
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<p>The FTIR spectra of Fe<sub>3</sub>O<sub>4</sub>, HAAP, Fe<sub>3</sub>O<sub>4</sub>@HAAP.</p>
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<p>The XPS spectra of Fe<sub>3</sub>O<sub>4</sub>@HAAP: (<b>a</b>) Fe 2p spectrum, (<b>b</b>) O 1s spectrum, (<b>c</b>) C 1s spectrum, (<b>d</b>) N 1s spectrum.</p>
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<p>SEM images of Fe<sub>3</sub>O<sub>4</sub>@HAAP: (<b>a</b>) ×50; (<b>b</b>) ×2000; (<b>c</b>) ×10,000; (<b>d</b>) ×50,000.</p>
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<p>The magnetization hysteresis loops of Fe<sub>3</sub>O<sub>4</sub> and Fe<sub>3</sub>O<sub>4</sub>@HAAP.</p>
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<p>Zeta potential of kaolin solution, Fe<sub>3</sub>O<sub>4</sub>, HAAP, and Fe<sub>3</sub>O<sub>4</sub>@HAAP.</p>
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<p>Removing efficiency of Fe<sub>3</sub>O<sub>4</sub>@HAAP on kaolin solution under different conditions: (<b>a</b>) Fe<sub>3</sub>O<sub>4</sub>@HAAP dosage, (<b>b</b>) pH, (<b>c</b>) kaolin concentration, (<b>d</b>) reaction time.</p>
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<p>Removing efficiency of Fe<sub>3</sub>O<sub>4</sub>@HAAP on actual water: (<b>a</b>) Lake 1, (<b>b</b>) Lake 2. The Fe<sub>3</sub>O<sub>4</sub>@HAAP dosage was 50 mg/L, pH = 5.</p>
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<p>The recycling efficiency (<b>a</b>) and removing efficiency (<b>b</b>) of Fe<sub>3</sub>O<sub>4</sub> and Fe<sub>3</sub>O<sub>4</sub>@HAAP on kaolin treatment under 5 recycling times, the colors correspond to different recycling times.</p>
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<p>The interaction energy between Fe<sub>3</sub>O<sub>4</sub>@HAAP and kaolin: (<b>a</b>) kaolin–kaolin; (<b>b</b>) Fe<sub>3</sub>O<sub>4</sub>@HAAP–kaolin. pH = 5.</p>
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16 pages, 15750 KiB  
Article
Iron Loss and Temperature Rise Analysis of a Transformer Core Considering Vector Magnetic Hysteresis Characteristics under Direct Current Bias
by Minxia Shi, Teng Li, Shuai Yuan, Leran Zhang, Yuzheng Ma and Yi Gao
Materials 2024, 17(15), 3767; https://doi.org/10.3390/ma17153767 - 31 Jul 2024
Viewed by 334
Abstract
Direct current (DC) bias induced by the DC transmission and geomagnetically induced current is a critical factor in the abnormal operation of electrical equipment and is widely used in the field of power transmission and distribution system state evaluation. As the main affected [...] Read more.
Direct current (DC) bias induced by the DC transmission and geomagnetically induced current is a critical factor in the abnormal operation of electrical equipment and is widely used in the field of power transmission and distribution system state evaluation. As the main affected component, the vector magnetization state of a transformer core under DC bias has rarely been studied, resulting in inaccurate transformer operation state estimations. In this paper, a dynamic vector hysteresis model that considers the impact of rotating and DC-biased fields is introduced into the numerical analysis to simulate the distribution of magnetic properties, iron loss and temperature of the transformer core model and a physical 110 kV single-phase autotransformer core. The maximum values of B, H and iron loss exist at the corners and T-joint of the core under rotating and DC-biased fields. The corresponding maximum value of the temperature increase is found in the main core limb area. The temperature rise of the 110 kV transformer core under various DC-biased conditions is measured and compared with the FEM (Finite Element Method) results of the proposed model and the model solely based on the magnetization curve B||H. The calculation error of the temperature rise obtained by the improved model is approximately 3.76–15.73% and is much less than the model solely based on magnetization curve B||H (approximately 50.71–66.92%). Full article
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<p>The desired field and the feedback measurement system: (<b>a</b>) Desired field. (<b>b</b>) Schematic of the experimental measurement system. (<b>c</b>) The physical single sheet tester (SST). (<b>d</b>) The physical measurement system.</p>
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<p>Loci of <b><span class="html-italic">B</span></b> and <b><span class="html-italic">H</span></b> under different <b><span class="html-italic">B<sub>max</sub></span></b> without DC bias and the corresponding magnetization curve and permeability of 30ZH120: (<b>a</b>) <b><span class="html-italic">B</span></b> locus. (<b>b</b>) <b><span class="html-italic">H</span></b> locus. (<b>c</b>) Magnetization curve and permeability of 30ZH120 at the frequency 50 Hz in easy magnetization direction.</p>
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<p>Waveforms and harmonic component amplitudes of <b><span class="html-italic">B</span></b> and <b><span class="html-italic">H</span></b> under different <b><span class="html-italic">B<sub>dc</sub></span></b>: (<b>a</b>) <span class="html-italic">B<sub>x</sub></span> and <span class="html-italic">H<sub>x</sub></span> waveforms. (<b>b</b>) <span class="html-italic">B<sub>y</sub></span> and <span class="html-italic">H<sub>y</sub></span> waveforms. (<b>c</b>) <span class="html-italic">B<sub>x</sub></span> harmonic component amplitudes. (<b>d</b>) <span class="html-italic">H<sub>x</sub></span> harmonic component amplitudes.</p>
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<p>The iron loss under different magnetization conditions: (<b>a</b>) The loss of different <span class="html-italic">B<sub>max</sub></span> and <span class="html-italic">θ</span>. (<b>b</b>) The loss of different <span class="html-italic">B<sub>max</sub></span> and <span class="html-italic">α</span>. (<b>c</b>) The loss of different <span class="html-italic">B<sub>dc</sub></span>.</p>
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<p>The movement process of magnetic domain: (<b>a</b>) The movement process of magnetic domain under the rotating magnetic field increasing for <span class="html-italic">B<sub>max</sub></span> ranging from 0.2 to 1.0 T. (<b>b</b>) The movement process of magnetic domain under the rotating magnetic field and DC-biased field for increasing <span class="html-italic">B<sub>dc</sub></span> ranging from 0.2 to 1.0 T and increasing <span class="html-italic">θ<sub>dc</sub></span> from 0 to 90°.</p>
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<p>The movement process of magnetic domain: (<b>a</b>) The movement process of magnetic domain under the rotating magnetic field increasing for <span class="html-italic">B<sub>max</sub></span> ranging from 0.2 to 1.0 T. (<b>b</b>) The movement process of magnetic domain under the rotating magnetic field and DC-biased field for increasing <span class="html-italic">B<sub>dc</sub></span> ranging from 0.2 to 1.0 T and increasing <span class="html-italic">θ<sub>dc</sub></span> from 0 to 90°.</p>
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<p>Transform core model and the mesh: (<b>a</b>) The transform core model. (<b>b</b>) The mesh.</p>
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<p>Distribution of the maximum value of <b><span class="html-italic">B</span></b> and <b><span class="html-italic">H</span></b> of the transformer core model: (<b>a</b>) Maximum value of <b><span class="html-italic">B</span></b> calculated using the magnetization curve. (<b>b</b>) Maximum value of <b><span class="html-italic">B</span></b> calculated using the improved model. (<b>c</b>) Maximum value of <b><span class="html-italic">H</span></b> calculated using the magnetization curve. (<b>d</b>) Maximum value of <b><span class="html-italic">H</span></b> calculated using the improved model.</p>
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<p>Distribution of iron loss of the transformer core model: (<b>a</b>) Iron loss calculated using the magnetization curve. (<b>b</b>) Iron loss calculated using the improved model.</p>
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<p>Distribution of temperature of the transformer core model: (<b>a</b>) Temperature calculated using the magnetization curve. (<b>b</b>) Temperature calculated using the improved model.</p>
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<p>Schematic diagram of DC bias test: (<b>a</b>) Wiring schematic diagram for DC bias test. (<b>b</b>) Temperature rise measurement point for DC bias magnetic test.</p>
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<p>Exciting current and magnetization curve of the tested transformer core: (<b>a</b>) Exciting current for different DC bias conditions. (<b>b</b>) Magnetization curve and the corresponding permeability of 27RK090 (50 Hz) of the tested transformer core in easy magnetization direction.</p>
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<p>The 2D automatic mesh with triangular elements of the physical transformer core.</p>
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<p>Distribution of <b><span class="html-italic">B</span></b> and <b><span class="html-italic">H</span></b> of the physical 110 kV transformer core: (<b>a</b>) Distribution of <b><span class="html-italic">B</span></b> and <b><span class="html-italic">H</span></b> calculated using the basic magnetization curve. (<b>b</b>) Distribution of <b><span class="html-italic">B</span></b> and <b><span class="html-italic">H</span></b> calculated using proposed model.</p>
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<p>Distribution of temperature of the physical 110 kV transformer core: (<b>a</b>) Temperature calculated using the magnetization curve. (<b>b</b>) Temperature calculated using the improved model.</p>
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<p>Comparison between calculated and measured values of local temperature of iron core: (<b>a</b>) Point A. (<b>b</b>) Point B. (<b>c</b>) Point C. (<b>d</b>) Point D.</p>
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11 pages, 1606 KiB  
Article
Josephson Diode Effect in Parallel-Coupled Double-Quantum Dots Connected to Unalike Majorana Nanowires
by Yu-Mei Gao, Hu Xiao, Mou-Hua Jiang, Feng Chi, Zi-Chuan Yi and Li-Ming Liu
Nanomaterials 2024, 14(15), 1251; https://doi.org/10.3390/nano14151251 - 25 Jul 2024
Viewed by 474
Abstract
We study theoretically the Josephson diode effect (JDE) when realized in a system composed of parallel-coupled double-quantum dots (DQDs) sandwiched between two semiconductor nanowires deposited on an s-wave superconductor surface. Due to the combined effects of proximity-induced superconductivity, strong Rashba spin–orbit interaction, and [...] Read more.
We study theoretically the Josephson diode effect (JDE) when realized in a system composed of parallel-coupled double-quantum dots (DQDs) sandwiched between two semiconductor nanowires deposited on an s-wave superconductor surface. Due to the combined effects of proximity-induced superconductivity, strong Rashba spin–orbit interaction, and the Zeeman splitting inside the nanowires, a pair of Majorana bound states (MBSs) may possibly emerge at opposite ends of each nanowire. Different phase factors arising from the superconductor substrate can be generated in the coupling amplitudes between the DQDs and MBSs prepared at the left and right nanowires, and this will result in the Josephson current. We find that the critical Josephson currents in positive and negative directions are different from each other in amplitude within an oscillation period with respect to the magnetic flux penetrating through the system, a phenomenon known as the JDE. It arises from the quantum interference effect in this double-path device, and it can hardly occur in the system of one QD coupled to MBSs. Our results also show that the diode efficiency can reach up to 50%, but this depends on the overlap amplitude between the MBSs, as well as the energy levels of the DQDs adjustable by gate voltages. The present model is realizable within current nanofabrication technologies and may find practical use in the interdisciplinary field of Majorana and Josephson physics. Full article
(This article belongs to the Special Issue Nanoelectronics: Materials, Devices and Applications (Second Edition))
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Figure 1
<p>Schematic diagram for the studied system, which is composed of parallel double-quantum dots (DQDs) coupled to the left and right nanowires hosting Majorana bound states (MBSs) at their ends. The MBSs are denoted by <math display="inline"><semantics> <msub> <mi>γ</mi> <mrow> <mi>α</mi> <mi>i</mi> </mrow> </msub> </semantics></math> with <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mi>L</mi> <mo>,</mo> <mi>R</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> </mrow> </semantics></math>, and they interact with the QDs with strengths of <math display="inline"><semantics> <msub> <mi>λ</mi> <mrow> <mi>α</mi> <mi>i</mi> </mrow> </msub> </semantics></math>. The DQDs are coupled to each other via a tunnel barrier of amplitude <math display="inline"><semantics> <msub> <mi>t</mi> <mi>c</mi> </msub> </semantics></math>. In the presence of a magnetic flux <math display="inline"><semantics> <mo>Φ</mo> </semantics></math> threading through the system, a phase factor <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math> was added to <math display="inline"><semantics> <msub> <mi>λ</mi> <mrow> <mi>α</mi> <mi>i</mi> </mrow> </msub> </semantics></math> in addition to the phase difference from the superconductor substrate <math display="inline"><semantics> <msub> <mi>φ</mi> <mi>α</mi> </msub> </semantics></math>. The relationship between <math display="inline"><semantics> <msub> <mi>λ</mi> <mrow> <mi>α</mi> <mi>i</mi> </mrow> </msub> </semantics></math> and the phase factors <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math> and <math display="inline"><semantics> <msub> <mi>φ</mi> <mi>α</mi> </msub> </semantics></math> will be specified in the main text.</p>
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<p>The (color online) Josephson current and CCDOS individually in (<b>a</b>,<b>b</b>) for the case of dot levels <math display="inline"><semantics> <mrow> <msubsup> <mi>ε</mi> <mn>1</mn> <mn>0</mn> </msubsup> <mo>=</mo> <msubsup> <mi>ε</mi> <mn>2</mn> <mn>0</mn> </msubsup> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, i.e., the configuration of (0, 0). (<b>c</b>) and (<b>d</b>) are for the Josephson current in the configurations of (0, −4) and (−2, 4), respectively. The tunnel-coupling strength between the dots were fixed at <math display="inline"><semantics> <mrow> <msub> <mi>t</mi> <mi>c</mi> </msub> <mo>=</mo> <msub> <mi>λ</mi> <mn>0</mn> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mi>π</mi> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <mi>φ</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math>.</p>
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<p>Josephson current <span class="html-italic">J</span> as a function of <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math> and <math display="inline"><semantics> <mi>φ</mi> </semantics></math>, the positive (negative) critical current <math display="inline"><semantics> <msub> <mi>J</mi> <mrow> <mi>c</mi> <mo>+</mo> <mo>(</mo> <mo>−</mo> <mo>)</mo> </mrow> </msub> </semantics></math>, the diode efficiency <math display="inline"><semantics> <mi>η</mi> </semantics></math> as functions of <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math> for the configurations of (0, 0) in (<b>a</b>) and (<b>b</b>), the (0, −4) in (<b>c</b>) and (<b>d</b>), and the (−2, 4) in (<b>e</b>) and (<b>f</b>) for <math display="inline"><semantics> <mrow> <mi>φ</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math>, respectively. Other parameters are <math display="inline"><semantics> <mrow> <msub> <mi>t</mi> <mi>c</mi> </msub> <mo>=</mo> <msub> <mi>λ</mi> <mn>0</mn> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>e</mi> <msub> <mi>V</mi> <mi>g</mi> </msub> <mo>=</mo> <msub> <mi>δ</mi> <mi>M</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.</p>
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<p>Diode efficiency <math display="inline"><semantics> <mi>η</mi> </semantics></math> as a function of <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math> for the dot level configuration <math display="inline"><semantics> <mrow> <mo>(</mo> <mo>−</mo> <mn>2</mn> <mo>,</mo> <mn>4</mn> <mo>)</mo> </mrow> </semantics></math> and different values of MBS–MBS overlap amplitude <math display="inline"><semantics> <msub> <mi>δ</mi> <mi>M</mi> </msub> </semantics></math> for <math display="inline"><semantics> <mrow> <mi>φ</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math>. The other parameters are as in <a href="#nanomaterials-14-01251-f003" class="html-fig">Figure 3</a>.</p>
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<p>Josephson current <span class="html-italic">J</span> as a function of <math display="inline"><semantics> <mi>φ</mi> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>e</mi> <msub> <mi>V</mi> <mi>g</mi> </msub> </mrow> </semantics></math> for <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>4</mn> </mrow> </semantics></math>, and the diode efficiency <math display="inline"><semantics> <mi>η</mi> </semantics></math> as a function of <math display="inline"><semantics> <msub> <mi>V</mi> <mi>g</mi> </msub> </semantics></math> for different values of <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math>. The dot level configurations are <math display="inline"><semantics> <mrow> <mo>(</mo> <mn>0</mn> <mo>,</mo> <mo>−</mo> <mn>4</mn> <mo>)</mo> </mrow> </semantics></math> in (<b>a</b>) and (<b>b</b>), (−2, 4) in (<b>c</b>) and (<b>d</b>) at <math display="inline"><semantics> <mrow> <msub> <mi>δ</mi> <mi>M</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <mi>φ</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math> in (<b>b</b>) and (<b>d</b>). The other parameters are as in <a href="#nanomaterials-14-01251-f003" class="html-fig">Figure 3</a>.</p>
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20 pages, 5586 KiB  
Article
Impact of Serotonin Transporter Absence on Brain Insulin Receptor Expression, Plasma Metabolome Changes, and ADHD-like Behavior in Mice fed a Western Diet
by Daniel C. Anthony, Fay Probert, Anna Gorlova, Jenna Hebert, Daniel Radford-Smith, Zlata Nefedova, Aleksei Umriukhin, Andrey Nedorubov, Raymond Cespuglio, Boris Shulgin, Aleksey Lyundup, Klaus Peter Lesch and Tatyana Strekalova
Biomolecules 2024, 14(8), 884; https://doi.org/10.3390/biom14080884 - 23 Jul 2024
Viewed by 556
Abstract
The impaired function of the serotonin transporter (SERT) in humans has been linked to a higher risk of obesity and type 2 diabetes, especially as people age. Consuming a “Western diet” (WD), which is high in saturated fats, cholesterol, and sugars, can induce [...] Read more.
The impaired function of the serotonin transporter (SERT) in humans has been linked to a higher risk of obesity and type 2 diabetes, especially as people age. Consuming a “Western diet” (WD), which is high in saturated fats, cholesterol, and sugars, can induce metabolic syndrome. Previous research indicated that mice carrying a targeted inactivation of the Sert gene (knockout, KO) and fed a WD display significant metabolic disturbances and behaviors reminiscent of ADHD. These abnormalities might be mediated via a dysfunction in insulin receptor (IR) signaling, which is also associated with adult ADHD. However, the impact of Sert deficiency on IR signaling and systemic metabolic changes has not been thoroughly explored. In this study, we conducted a detailed analysis of locomotor behavior in wild-type (WT) and KO mice fed a WD or control diet. We investigated changes in the blood metabolome and examined, via PCR, the expression of insulin receptor A and B isoforms and key regulators of their function in the brain. Twelve-month-old KO mice and their WT littermates were fed a WD for three weeks. Nuclear magnetic resonance spectroscopy analysis of plasma samples showed that KO mice on a WD had higher levels of lipids and lipoproteins and lower levels of glucose, lactate, alanine, valine, and isoleucine compared to other groups. SERT-KO mice on the control diet exhibited increased brain levels of both IR A and B isoforms, accompanied by a modest increase in the negative regulator ENPP. The KO mice also displayed anxiety-like behavior and reduced exploratory activity in an open field test. However, when the KO animals were fed a WD, the aberrant expression levels of IR isoforms in the KO mice and locomotor behavior were ameliorated indicating a complex interaction between genetic and dietary factors that might contribute to ADHD-like symptoms. Overall, our findings suggest that the lack of Sert leads to a unique metabolic phenotype in aged mice, characterized by dysregulated IR-related pathways. These changes are exacerbated by WD in the blood metabolome and are associated with behavioral abnormalities. Full article
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Figure 1

Figure 1
<p>Experiment design: Flow diagram of experimental paradigm paradigm assessing the impact of the WD on WT and SERT-KO mice. (<b>A</b>) In the first study, a glucose tolerance test was carried out on Day 22, blood was harvested for biochemical assay on Day 24. (<b>B</b>) In the second study, behavioral evaluation and the open field test was performed on day 21. After the last behavioral assessment, mice were sacrificed on Day 22, and the brains were dissected, blood was collected. Brain was harvested to be used for a subsequent RNA isolation and RT-qPCR assay blood was used in the metabolome assay.</p>
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<p>Physiological and metabolic changes in SERT-KO and WT mice on a WD. We found an effect of genotype on body weight at week 1 (<b>A</b>) and week 2 (<b>B</b>). At week 3 (<b>C</b>), significant diet and genotype effects were observed, with body weight increased in the normalized KO/WD group compared to 100%. There was an effect of diet on glucose tolerance (<b>D</b>), with the normalized WT/WD group showing an increased AUC compared to 100%. Significant diet and genotype effects on leptin levels in the blood were also found (<b>E</b>); both WT and KO mice normalized to their respective CD groups had increased leptin levels compared to 100%. Statistical analyses were performed using two-way ANOVA with Tukey’s post-hoc test, <span class="html-italic">t</span>-test (&amp; <span class="html-italic">p</span> &lt; 0.05), and one-sample <span class="html-italic">t</span>-test (# <span class="html-italic">p</span> &lt; 0.05). (WT-CD group, n = 6, WT-WD group, n = 7, KO-SERT-CD group, n = 8, KO-SERT-WD group, n = 8). Black and diagonal bars represent WD-fed groups whose measurements were normalized to the respective genotype control diet group. All data are presented as mean ± SEM.</p>
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<p>Distinct plasma metabolic profile changes in SERT-KO and WT mice housed on the WD. (<b>A</b>) PCA plot depicting how PC1 accounts for 40.8% of the variance in the data and PC2 for 25.8% which separated the data into four clusters. (<b>B</b>) OPLS-DA plots of the pairwise comparison revealed that the average accuracy for the models was high (*** <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">t</span>-test) The true models performed significantly better than random chance in categorizing the samples in the test sets (* <span class="html-italic">p</span> &lt; 0.001, Kolmogorov–Smirnov test) (<b>C</b>) A heatmap of the principal metabolites responsible for the group showing the relative relationship of each metabolite in each group. We found significant differences in the lipids, energy metabolites and amino acids in each group (n = 7 mice for each group).</p>
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<p>Behavioral changes in the open field between SERT-KO and WT mice fed a WD. (<b>A</b>) Velocity normalized to respective CD groups was decreased in WT/WD and increased in KO/WD mice. (<b>B</b>) There was a significant genotype effect in the number of transitions between central zone and periphery. (<b>C</b>) Time spent in stretched posture normalized to CD and duration of stretched posture was decreased in WT/WD compared to 100%. (<b>D</b>) Interaction between diet and genotype in duration of grooming was revealed, this parameter when normalized to CD was increased in WT/CD compared to 100%. Two-way ANOVA and Tukey’s post-hoc test (* <span class="html-italic">p</span> &lt; 0.05), <span class="html-italic">t</span>-test (&amp; <span class="html-italic">p</span> &lt; 0.05) and one sample <span class="html-italic">t</span>-test (# <span class="html-italic">p</span> &lt; 0.05). Black and diagonal bars represent WD-fed groups whose measurements were normalized to the respective genotype control diet group. (WT-CD group, n = 6, WT-WD group, n = 7, KO-SERT-CD group, n = 8, KO-SERT-WD group, n = 8). All data are mean ± SEM.</p>
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<p>Distinct expression of IR subtypes in the brain of SERT-KO and WT mice housed on WD. IRA expression levels were increased in KO/CD compared to WT/CD mice and decreased in KO/WD compared to KO/CD in (<b>A</b>) hippocampus and (<b>B</b>) dorsal raphe. (<b>C</b>) Significant diet and genotype effects were revealed in IRA expression level in prefrontal cortex. Both WT and KO groups normalized to respective CD had this measure decreased compared to 100%. (<b>D</b>) In hypothalamus, IRA expression levels were increased in KO/CD compared to WT/CD mice and decreased in KO/WD compared to KO/CD. (<b>E</b>) IRB expression was significantly decreased in hippocampus of KO/WD compared to KO/CD. Significant genotype effect was found for IRB expression in (<b>F</b>) dorsal raphe and (<b>G</b>) prefrontal cortex. In both structures it was decreased in normalized KO mice compared to 100%. (<b>H</b>) In hypothalamus, IRB expression was significantly higher in KO/CD mice compared to WT/CD and KO/WD animals. Two-way ANOVA and Tukey’s post-hoc test (* <span class="html-italic">p</span> &lt; 0.05), <span class="html-italic">t</span>-test (&amp; <span class="html-italic">p</span> &lt; 0.05) and one sample <span class="html-italic">t</span>-test (# <span class="html-italic">p</span> &lt; 0.05; n = 7 mice for each group). Black and diagonal bars represent WD-fed groups whose measurements were normalized to the respective genotype control diet group. All data are mean ± SEM.</p>
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<p>WD-induced changes in brain expression of transcription factors in SERT-KO and WT mice. ACSL1 expression in the (<b>A</b>) hippocampus, (<b>B</b>) dorsal raphe, (<b>C</b>) prefrontal cortex, and (<b>D</b>) hypothalamus. ENPP expression in the (<b>E</b>) hippocampus, (<b>F</b>) dorsal raphe, (<b>G</b>) prefrontal cortex and (<b>H</b>) hypothalamus. PTPN1 expression in the (<b>I</b>) hippocampus, (<b>J</b>) dorsal raphe, (<b>K</b>) prefrontal cortex, (<b>L</b>) hypothalamus. PTEN expression in the (<b>M</b>) hippocampus, (<b>N</b>) dorsal raphe, (<b>O</b>) prefrontal cortex, and (<b>P</b>) hypothalamus. CD36 expression in the (<b>Q</b>) hippocampus, (<b>R</b>) dorsal raphe, (<b>S</b>) prefrontal cortex, and (<b>T</b>) hypothalamus. Two-way ANOVA and Tukey’s post-hoc test (* <span class="html-italic">p</span> &lt; 0.05), <span class="html-italic">t</span>-test (&amp; <span class="html-italic">p</span> &lt; 0.05) and one sample <span class="html-italic">t</span>-test (# <span class="html-italic">p</span> &lt; 0.05; n = 7 mice for each group). Black and diagonal bars represent WD-fed groups whose measurements were normalized to the respective genotype control diet group. All data are mean ± SEM.</p>
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10 pages, 267 KiB  
Article
Estimate for the Neutrino Magnetic Moment from Pulsar Kick Velocities Induced at the Birth of Strange Quark Matter Neutron Stars
by Alejandro Ayala, Santiago Bernal-Langarica and Daryel Manreza-Paret
Universe 2024, 10(7), 301; https://doi.org/10.3390/universe10070301 - 20 Jul 2024
Viewed by 499
Abstract
We estimate the magnetic moment of electron neutrinos by computing the neutrino chirality flip rate that can occur in the core of a strange quark matter neutron star at birth. We show that this process allows neutrinos to anisotropically escape, thus inducing the [...] Read more.
We estimate the magnetic moment of electron neutrinos by computing the neutrino chirality flip rate that can occur in the core of a strange quark matter neutron star at birth. We show that this process allows neutrinos to anisotropically escape, thus inducing the star kick velocity. Although the flip from left- to right-handed neutrinos is assumed to happen in equilibrium, the no-go theorem does not apply because right-handed neutrinos do not interact with matter and the reverse process does not happen, producing the loss of detailed balance. For simplicity, we model the star core as consisting of strange quark matter. We find that even when the energy released in right-handed neutrinos is a small fraction of the total energy released in left-handed neutrinos, the process describes kick velocities for natal conditions, which are consistent with the observed ones and span the correct range of radii, temperatures and chemical potentials for typical magnetic field intensities. The neutrino magnetic moment is estimated to be μν3.6×1018μB, where μB is the Bohr magneton. This value is more stringent than the bound found for massive neutrinos in a minimal extension of the standard model. Full article
(This article belongs to the Special Issue Studies in Neutron Stars)
19 pages, 6214 KiB  
Article
Effect of Ho3+ Substitution on Magnetic Properties of ZnCr2Se4
by Izabela Jendrzejewska, Tadeusz Groń, Elżbieta Tomaszewicz, Zbigniew Stokłosa, Tomasz Goryczka, Jerzy Goraus, Michał Pilch, Ewa Pietrasik and Beata Witkowska-Kita
Int. J. Mol. Sci. 2024, 25(14), 7918; https://doi.org/10.3390/ijms25147918 - 19 Jul 2024
Viewed by 344
Abstract
A series of ZnCr2−xHoxSe4 microcrystalline spinels (where x = 0.05, 0.075, and 0.10) containing holmium ions in octahedral coordination were obtained by sintering of adequate reactants at high temperatures. The obtained doped materials were characterized by X-ray [...] Read more.
A series of ZnCr2−xHoxSe4 microcrystalline spinels (where x = 0.05, 0.075, and 0.10) containing holmium ions in octahedral coordination were obtained by sintering of adequate reactants at high temperatures. The obtained doped materials were characterized by X-ray diffraction, Scanning Electron Microscopy, UV–Vis–NIR, molecular field approximation, and XPS spectroscopies. Their thermal properties were also investigated. The doping of the ZnCr2S4 matrix with paramagnetic Ho3+ ions with a content of not more than 0.1 and a screened 4f shell revealed a significant effect of orbital and Landau diamagnetism, a strong reduction in short-range ferromagnetic interactions, and a broadening and shift of the peak of the first critical field by simultaneous stabilization of the sharp peak in the second critical field. These results correlate well with FPLO calculations, which show that Cr sites have magnetic moments of 3.19 µB and Ho sites have significantly larger ones with a value of 3.95 µB. Zn has a negligible magnetic polarization of 0.02 µB, and Se induces a polarization of approximately −0.12 µB. Full article
(This article belongs to the Section Materials Science)
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Figure 1

Figure 1
<p>X–ray diffraction patterns of ZnCr<sub>2−<span class="html-italic">x</span></sub>Ho<span class="html-italic"><sub>x</sub></span>Se<sub>4</sub> samples (<span class="html-italic">x</span> = 0.05, 0.075, and 0.10).</p>
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<p>The relation between observed and calculated X–ray diffraction patterns and their difference for the ZnCr<sub>2−<span class="html-italic">x</span></sub>Ho<span class="html-italic"><sub>x</sub></span>Se<sub>4</sub> sample when <span class="html-italic">x</span> = 0.10.</p>
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<p>The dependence of the lattice parameter (a) and the anion parameter (u) of ZnCr<sub>2−x</sub>Ho<sub>x</sub>Se<sub>4</sub> on the concentration of holmium ions.</p>
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<p>A fracture surface by SEI for ZnCr<sub>2−x</sub>Ho<sub>x</sub>Se<sub>4</sub> samples, scale bar = 1 μm. (<b>a</b>) ZnCr<sub>1.95</sub>Ho<sub>0.05</sub>Se<sub>4.0</sub>, magnification 3000×, (<b>b</b>) ZnCr<sub>1.925</sub>Ho<sub>0.075</sub>Se<sub>4.0</sub>, magnification 2000×, and (<b>c</b>) ZnCr<sub>1.90</sub>Ho<sub>0.10</sub>Se<sub>4.0,</sub> magnification 3500×.</p>
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<p>Map of element distribution measured for ZnCr<sub>1.90</sub>Ho<sub>0.10</sub>Se<sub>4.0</sub> sample.</p>
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<p>DSC–TG–DTG curves recorded during controlled heating of the ZnCr<sub>1.90</sub>Ho<sub>0.10</sub>Se<sub>4.0</sub> sample.</p>
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<p>The total density of states calculated for the ZnCr<sub>1.95</sub>Ho<sub>0.05</sub>Se<sub>4.0</sub> sample.</p>
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<p>UV–vis–NIR absorption spectra of ZnCr<sub>2−<span class="html-italic">x</span></sub>Ho<span class="html-italic"><sub>x</sub></span>Se<sub>4</sub> when <span class="html-italic">x</span> = 0.05; 0.075; and 0.10.</p>
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<p>The plot of (αhν)<sup>2</sup> vs. hν of ZnCr<sub>2−<span class="html-italic">x</span></sub>Ho<span class="html-italic"><sub>x</sub></span>Se<sub>4</sub> when <span class="html-italic">x</span> = 0.075 with determined direct optical band gap (E<sub>g</sub>). Insert: plot of ln(αhν) vs. ln(hν − E<sub>g</sub>) of ZnCr<sub>2−<span class="html-italic">x</span></sub>Ho<span class="html-italic"><sub>x</sub></span>Se<sub>4</sub> when <span class="html-italic">x</span> = 0.075.</p>
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<p>Heat capacity measured in the narrower temperature range around the magnetic transition (main figure) and in the broad temperature range (right bottom inset). The left inset shows a low-temperature peak at 3.8 K, observed for all samples. The middle inset shows the change in the magnetic peak position concerning the applied magnetic field. A quadratic dependence is noticeable here (usually for simple magnets, which the mean-field model can explain).</p>
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<p>DC magnetic susceptibility χ<sub>dc</sub>, 1/χ<sub>dc,</sub> and 1/(χ<sub>dc</sub> – χ<sub>0</sub>) and product χ<sub>dc</sub>·T as a function of temperature T of a series of microcrystalline ZnCr<sub>2−<span class="html-italic">x</span></sub>Ho<span class="html-italic"><sub>x</sub></span>Se<sub>4</sub> spinels for <span class="html-italic">x</span> = 0.05, 0.075, and 0.10, recorded at H<sub>dc</sub> = 1 kOe. The solid, (T − θ)/C, and dashed, χ<sub>0</sub>·T + b, lines indicate Curie–Weiss behaviour. χ<sub>0</sub> is the slope and b is the intercept.</p>
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<p>Magnetization M vs. magnetic field H recorded at 5 K of a series of polycrystalline ZnCr<sub>2−<span class="html-italic">x</span></sub>Ho<span class="html-italic"><sub>x</sub></span>Se<sub>4</sub> spinels for <span class="html-italic">x</span> = 0.05, 0.075, and 0.10. The upper pictures show the evolution of magnetic structure in an external magnetic field from the spiral via conical to the FM order.</p>
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<p>Magnetization M and ac magnetic susceptibility χ<sub>ac</sub> as a function of dc magnetic field H recorded at 5, 10, 20, 40, 60, and 300 K and 5, 10, 20, and 30 K (in an internal oscillating magnetic field H<sub>ac</sub> = 3.9 Oe and internal frequency f = 1 kHz), respectively, of a series of polycrystalline ZnCr<sub>2−x</sub>Ho<sub>x</sub>Se<sub>4</sub> spinels for <span class="html-italic">x</span> = 0.05, 0.075, and 0.10.</p>
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<p>Ninety-degree exchange interaction: (<b>a</b>) with one p orbital: <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mi mathvariant="normal">x</mi> <mi mathvariant="normal">z</mi> </mrow> </msub> <munder> <mrow> <mi mathvariant="sans-serif">π</mi> </mrow> <mo>_</mo> </munder> <msub> <mrow> <mi mathvariant="normal">p</mi> </mrow> <mrow> <mi mathvariant="normal">z</mi> </mrow> </msub> <munder> <mrow> <mi mathvariant="sans-serif">π</mi> </mrow> <mo>_</mo> </munder> <msub> <mrow> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">z</mi> </mrow> </msub> </mrow> </semantics></math> and (<b>b</b>) with two p orbitals: <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">d</mi> </mrow> <mrow> <msup> <mrow> <mi mathvariant="normal">x</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msup> <mo>−</mo> <msup> <mrow> <mi mathvariant="normal">y</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msup> </mrow> </msub> <munder> <mrow> <mi mathvariant="sans-serif">π</mi> </mrow> <mo>_</mo> </munder> <msub> <mrow> <mi mathvariant="normal">p</mi> </mrow> <mrow> <mi mathvariant="normal">x</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">p</mi> </mrow> <mrow> <mi mathvariant="normal">y</mi> </mrow> </msub> <munder> <mrow> <mi mathvariant="sans-serif">σ</mi> </mrow> <mo>_</mo> </munder> <msub> <mrow> <mi mathvariant="normal">d</mi> </mrow> <mrow> <msup> <mrow> <mi mathvariant="normal">x</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msup> <mo>−</mo> <msup> <mrow> <mi mathvariant="normal">y</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msup> </mrow> </msub> </mrow> </semantics></math>. Dashed lines indicate the overlapping orbitals.</p>
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<p>XPS survey spectra of ZnCr<sub>2–x</sub>Ho<sub>x</sub>Se<sub>4</sub> (x = 0.05, 0.075, and 0.10).</p>
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<p>XPS core lines: Zn 2p, Cr 2p, Se 3d, and Ho 4d of ZnCr<sub>1–x</sub>Ho<sub>x</sub>Se<sub>4</sub> (x = 0.05, 0.075, and 0.10).</p>
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20 pages, 8537 KiB  
Article
Uncertainty Quantification in SAR Induced by Ultra-High-Field MRI RF Coil via High-Dimensional Model Representation
by Xi Wang, Shao Ying Huang and Abdulkadir C. Yucel
Bioengineering 2024, 11(7), 730; https://doi.org/10.3390/bioengineering11070730 - 18 Jul 2024
Viewed by 498
Abstract
As magnetic field strength in Magnetic Resonance Imaging (MRI) technology increases, maintaining the specific absorption rate (SAR) within safe limits across human head tissues becomes challenging due to the formation of standing waves at a shortened wavelength. Compounding this challenge is the uncertainty [...] Read more.
As magnetic field strength in Magnetic Resonance Imaging (MRI) technology increases, maintaining the specific absorption rate (SAR) within safe limits across human head tissues becomes challenging due to the formation of standing waves at a shortened wavelength. Compounding this challenge is the uncertainty in the dielectric properties of head tissues, which notably affects the SAR induced by the radiofrequency (RF) coils in an ultra-high-field (UHF) MRI system. To this end, this study introduces a computational framework to quantify the impacts of uncertainties in head tissues’ dielectric properties on the induced SAR. The framework employs a surrogate model-assisted Monte Carlo (MC) technique, efficiently generating surrogate models of MRI observables (electric fields and SAR) and utilizing them to compute SAR statistics. Particularly, the framework leverages a high-dimensional model representation technique, which constructs the surrogate models of the MRI observables via univariate and bivariate component functions, approximated through generalized polynomial chaos expansions. The numerical results demonstrate the efficiency of the proposed technique, requiring significantly fewer deterministic simulations compared with traditional MC methods and other surrogate model-assisted MC techniques utilizing machine learning algorithms, all while maintaining high accuracy in SAR statistics. Specifically, the proposed framework constructs surrogate models of a local SAR with an average relative error of 0.28% using 289 simulations, outperforming the machine learning-based surrogate modeling techniques considered in this study. Furthermore, the SAR statistics obtained by the proposed framework reveal fluctuations of up to 30% in SAR values within specific head regions. These findings highlight the critical importance of considering dielectric property uncertainties to ensure MRI safety, particularly in 7 T MRI systems. Full article
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Figure 1
<p>(<b>a</b>) Flowchart depicting the implementation of the truncated HDMR expansion applied in this study, with <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>12</mn> </mrow> </semantics></math>. (<b>b</b>) Flowchart of HDMR-assisted MC method.</p>
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<p>The MRI-derived head model in an MRI birdcage coil with the locations of activated ports highlighted. (<b>a</b>) Front view; (<b>b</b>) right side view; (<b>c</b>) top view; (<b>d</b>) port locations: port 1 (red), port 5 (green), port 9 (black), and port 13 (yellow).</p>
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<p>Relative error distributions for 889,850 tissue voxels. Derived from the second scenario where the total order for component functions is 2, with 3 GL quadrature points along each dimension.</p>
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<p>Comparison of the SAR on slices. The ground truth (<b>Left</b>), approximation via proposed framework (<b>Mid</b>), and the logarithm of the relative error between the ground truth and approximation (<b>Right</b>). (<b>a</b>) Ground truth of the axial slice. (<b>b</b>) Approximate SAR of the axial slice. (<b>c</b>) Logarithm of relative error between (<b>a</b>,<b>b</b>). (<b>d</b>) Ground truth of the sagittal slice. (<b>e</b>) Approximate SAR of the sagittal slice. (<b>f</b>) Logarithm of relative error between (<b>d</b>,<b>e</b>). (<b>g</b>) Ground truth of the coronal slice. (<b>h</b>) Approximate SAR of the coronal slice. (<b>i</b>) Logarithm of relative error between (<b>g</b>,<b>h</b>).</p>
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<p>Convergence of mean (<b>top</b>) and variance (<b>bottom</b>) values for two different voxels, both computed using the 5000 point traditional MC method with increments of 50 random points/simulations. The black line represents the mean/variance values obtained via the HDMR-assisted MC method requiring 289 collocation points/simulations.</p>
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<p>Comparison between maximum and nominal 1g-SAR and 10g-SAR distributions. For sub-figures (<b>a</b>–<b>d</b>), only the top <math display="inline"><semantics> <mrow> <mn>5</mn> <mo>%</mo> </mrow> </semantics></math> of voxels with highest SAR values are plotted. (<b>a</b>) Maximum 1g-SAR distributions. (<b>b</b>) Nominal 1g-SAR distributions. (<b>c</b>) Maximum 10g-SAR distributions. (<b>d</b>) Nominal 10g-SAR distributions. (<b>e</b>) Activation port location (circled in red).</p>
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<p>Comparison of sagittal slices between maximum and nominal SAR distributions, along with their differences. (<b>a</b>) Maximum 1g-SAR. (<b>b</b>) Nominal 1g-SAR. (<b>c</b>) Difference between (<b>a</b>,<b>b</b>). (<b>d</b>) Maximum 10g-SAR. (<b>e</b>) Nominal 10g-SAR. (<b>f</b>) Difference between (<b>d</b>,<b>e</b>).</p>
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<p>Averaged Sobol indices for each tissue type. The x-axis depicts input dimensions, where <math display="inline"><semantics> <msub> <mi>ε</mi> <mi>r</mi> </msub> </semantics></math> is relative permittivity and <math display="inline"><semantics> <mi>σ</mi> </semantics></math> is conductivity; W, G, C, B, S, E represents white matter, grey matter, CSF, bone, scalp, and eye humor, respectively. Sub-figures show Sobol indices for (<b>a</b>) white matter, (<b>b</b>) grey matter, (<b>c</b>) CSF, (<b>d</b>) bone, (<b>e</b>) scalp, and (<b>f</b>) eye humor.</p>
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16 pages, 993 KiB  
Article
Temporal Evolution of Defects and Related Electric Properties in He-Irradiated YBa2Cu3O7−δ Thin Films
by Sandra Keppert, Bernd Aichner, Philip Rohringer, Marius-Aurel Bodea, Benedikt Müller, Max Karrer, Reinhold Kleiner, Edward Goldobin, Dieter Koelle, Johannes D. Pedarnig and Wolfgang Lang
Int. J. Mol. Sci. 2024, 25(14), 7877; https://doi.org/10.3390/ijms25147877 - 18 Jul 2024
Viewed by 457
Abstract
Thin films of the superconductor YBa2Cu3O7−δ (YBCO) were modified by low-energy light-ion irradiation employing collimated or focused He+ beams, and the long-term stability of irradiation-induced defects was investigated. For films irradiated with collimated beams, the resistance [...] Read more.
Thin films of the superconductor YBa2Cu3O7−δ (YBCO) were modified by low-energy light-ion irradiation employing collimated or focused He+ beams, and the long-term stability of irradiation-induced defects was investigated. For films irradiated with collimated beams, the resistance was measured in situ during and after irradiation and analyzed using a phenomenological model. The formation and stability of irradiation-induced defects are highly influenced by temperature. Thermal annealing experiments conducted in an Ar atmosphere at various temperatures demonstrated a decrease in resistivity and allowed us to determine diffusion coefficients and the activation energy ΔE=(0.31±0.03) eV for diffusive oxygen rearrangement within the YBCO unit cell basal plane. Additionally, thin YBCO films, nanostructured by focused He+-beam irradiation into vortex pinning arrays, displayed significant commensurability effects in magnetic fields. Despite the strong modulation of defect densities in these pinning arrays, oxygen diffusion during room-temperature annealing over almost six years did not compromise the signatures of vortex matching, which remained precisely at their magnetic fields predicted by the pattern geometry. Moreover, the critical current increased substantially within the entire magnetic field range after long-term storage in dry air. These findings underscore the potential of ion irradiation in tailoring the superconducting properties of thin YBCO films. Full article
(This article belongs to the Special Issue Application of Nanomaterials in Novel Thin Films and Coatings)
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<p>In-situ resistance measurement of YBCO thin film bridge 1 during and after 75 keV He<sup>+</sup>-ion irradiation at a temperature of <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>295</mn> </mrow> </semantics></math> K. A collimated He<sup>+</sup>-ion beam with a current density <math display="inline"><semantics> <mrow> <msub> <mi>J</mi> <mi>B</mi> </msub> <mo>=</mo> <mn>0.102</mn> <mspace width="3.33333pt"/> <mi mathvariant="sans-serif">μ</mi> </mrow> </semantics></math>A/cm<sup>2</sup> (red line) and a fluence <math display="inline"><semantics> <mrow> <mo>Φ</mo> <mo>=</mo> <mn>1.0</mn> <mo>·</mo> <msup> <mn>10</mn> <mn>15</mn> </msup> </mrow> </semantics></math> ions/cm<sup>2</sup> was used for the irradiation.</p>
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<p>In-situ resistance measurement of YBCO thin film bridge 2 during and after 75 keV He<sup>+</sup>-ion irradiation at a temperature of <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> K. A collimated He<sup>+</sup>-ion beam with a current density <math display="inline"><semantics> <mrow> <msub> <mi>J</mi> <mi>B</mi> </msub> <mo>=</mo> <mn>0.134</mn> <mspace width="3.33333pt"/> <mi mathvariant="sans-serif">μ</mi> </mrow> </semantics></math>A/cm<sup>2</sup> (red line) and a fluence <math display="inline"><semantics> <mrow> <mo>Φ</mo> <mo>=</mo> <mn>1.0</mn> <mo>·</mo> <msup> <mn>10</mn> <mn>15</mn> </msup> </mrow> </semantics></math> ions/cm<sup>2</sup> was used for the irradiation.</p>
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<p>Resistance <math display="inline"><semantics> <msub> <mi>R</mi> <mn>2</mn> </msub> </semantics></math> and temperature <span class="html-italic">T</span> of the ion-irradiated YBCO bridge 2 during warming up from 100 K to 295 K. The room-temperature resistance before ion irradiation <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mn>295</mn> <mi>K</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> is indicated by an orange dotted line. Inset: <math display="inline"><semantics> <msub> <mi>R</mi> <mn>2</mn> </msub> </semantics></math> as a function of temperature.</p>
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<p>Normalized resistance of YBCO thin film during 75 keV He<sup>+</sup> irradiation of bridge 1 at room temperature (black symbols) and bridge 2 at <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> K (blue symbols). Solid lines are fits to the data. The dimensionality parameter extracted from the fit at <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> K was used as a fixed parameter for the fit of the data at 295 K as well.</p>
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<p>Temperature dependence of the resistivities of thin YBCO films: sample A before (green) and after irradiation with 75 keV He<sup>+</sup> at a fluence of <math display="inline"><semantics> <mrow> <mn>0.7</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>15</mn> </msup> </mrow> </semantics></math> ions/cm<sup>2</sup> (lilac) and sample B after irradiation with a fluence of <math display="inline"><semantics> <mrow> <mn>1.4</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>15</mn> </msup> </mrow> </semantics></math> ions/cm<sup>2</sup> (red).</p>
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<p>Diffusion−coefficient <span class="html-italic">D</span> of oxygen in samples A and B after ion irradiation, determined from the exponential decay of the resistivity. Samples were kept at constant temperatures in the argon atmosphere. The broken lines are fits to determine the activation energy for the rearrangement of oxygen atoms. The inset shows a representative example of the resistivity decrease in sample A at <math display="inline"><semantics> <mrow> <msup> <mrow> <mn>102</mn> <mspace width="3.33333pt"/> </mrow> <mo>°</mo> </msup> </mrow> </semantics></math>C.</p>
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<p>Zero-resistance critical temperature <math display="inline"><semantics> <msub> <mi>T</mi> <mrow> <mi>c</mi> <mn>0</mn> </mrow> </msub> </semantics></math> over room-temperature storage time in an 80 nm YBCO film before and after He-FIB irradiation imprinting a square pinning array of 200 nm spacings. The black bullet represents <math display="inline"><semantics> <msub> <mi>T</mi> <mrow> <mi>c</mi> <mn>0</mn> </mrow> </msub> </semantics></math> eight days before the irradiation. The arrows indicate the sequence of <math display="inline"><semantics> <mrow> <mi>ρ</mi> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </semantics></math> measurements from which <math display="inline"><semantics> <msub> <mi>T</mi> <mrow> <mi>c</mi> <mn>0</mn> </mrow> </msub> </semantics></math> was determined, using a 10 m<math display="inline"><semantics> <mo>Ω</mo> </semantics></math> criterion. Inset: Evolution of the resistance vs. temperature characteristics of the sample with room-temperature annealing time. The black line represents the <math display="inline"><semantics> <mrow> <mi>ρ</mi> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </semantics></math> measurement of the sample before irradiation.</p>
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<p>Temporal evolution of the critical current in an 80 nm YBCO film structured by He-FIB into a square array of defect columns with 200 nm spacings. The initial critical current measurement after irradiation is denoted by red circles, while the subsequent measurement following 2122 days (almost six years) of storage in dry air at room temperature is represented by blue circles. The green symbols show the corresponding measurement at 84.7 K, taken at the same reduced temperature <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>/</mo> <msub> <mi>T</mi> <mrow> <mi>c</mi> <mn>0</mn> </mrow> </msub> <mo>=</mo> <mn>0.989</mn> </mrow> </semantics></math> as the measurement before long-term storage. Gray broken lines represent the magnetic fields according to Equation (<a href="#FD6-ijms-25-07877" class="html-disp-formula">6</a>) with values <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mo>{</mo> <mo>−</mo> <mn>2</mn> <mo>,</mo> <mo>−</mo> <mn>1</mn> <mo>,</mo> <mn>0</mn> <mo>,</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>}</mo> </mrow> </semantics></math>. Inset: Layout of the pinning lattice, where green circles represent the columnar defects and blue dots denote the positions of the trapped vortices for <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mo>±</mo> <mn>1</mn> </mrow> </semantics></math>.</p>
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22 pages, 8212 KiB  
Article
Inkjet Printing Magnetostrictive Materials for Structural Health Monitoring of Carbon Fibre-Reinforced Polymer Composite
by Nisar Ahmed, Patrick J. Smith and Nicola A. Morley
Sensors 2024, 24(14), 4657; https://doi.org/10.3390/s24144657 - 18 Jul 2024
Viewed by 397
Abstract
Inkjet printing of magnetic materials has increased in recent years, as it has the potential to improve research in smart, functional materials. Magnetostriction is an inherent property of magnetic materials which allows strain or magnetic fields to be detected. This makes it very [...] Read more.
Inkjet printing of magnetic materials has increased in recent years, as it has the potential to improve research in smart, functional materials. Magnetostriction is an inherent property of magnetic materials which allows strain or magnetic fields to be detected. This makes it very attractive for sensors in the area of structural health monitoring by detecting internal strains in carbon fibre-reinforced polymer (CFRP) composite. Inkjet printing offers design flexibility for these sensors to influence the magnetic response to the strain. This allows the sensor to be tailored to suit the location of defects in the CFRP. This research has looked into the viability of printable soft magnetic materials for structural health monitoring (SHM) of CFRP. Magnetite and nickel ink dispersions were selected to print using the JetLab 4 drop-on-demand technique. The printability of both inks was tested by selecting substrate, viscosity and solvent evaporation. Clogging was found to be an issue for both ink dispersions. Sonicating and adjusting the jetting parameters helped in distributing the nanoparticles. We found that magnetite nanoparticles were ideal as a sensor as there is more than double increase in saturation magnetisation by 49 Am2/kg and more than quadruple reduction of coercive field of 5.34 kA/m than nickel. The coil design was found to be the most sensitive to the field as a function of strain, where the gradient was around 80% higher than other sensor designs. Additive layering of 10, 20 and 30 layers of a magnetite square patch was investigated, and it was found that the 20-layered magnetite print had an improved field response to strain while maintaining excellent print resolution. SHM of CFRP was performed by inducing a strain via bending and it was found that the magnetite coil detected a change in field as the strain was applied. Full article
(This article belongs to the Special Issue Challenges and Future Trends of Magnetic Sensors)
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<p>JetLab signal input standard wave for each droplet.</p>
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<p>(<b>a</b>) Bending test on a known radius of curvature (<b>b</b>) 3D printed bend rig.</p>
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<p>(<b>a</b>) Dimension of the air core coil holder used for inductance measurements, (<b>b</b>) inductance measurement with coil and clamp on 3d printed bend rig and (<b>c</b>) circuit schematic with inductor, capacitor (where 1 and 2 are positive and negative connection) and AC power supply in series.</p>
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<p>Hysteresis loop of magnetite and nickel NP from −1200 to 1200 kA/m field.</p>
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<p>(<b>a</b>) image and (<b>b</b>) printed design: (<b>i</b>) magnetite uniaxial patch, (<b>ii</b>) magnetite coil and (<b>iii</b>) grid design and (<b>iiiv</b>) nickel lines print.</p>
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<p>Optical microscope of (<b>a</b>) magnetite uniaxial patch design on paper and (<b>b</b>) nickel coil design on paper.</p>
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<p>(<b>a</b>) SEM image of magnetite on paper at 2 kV, (<b>b</b>) EDS element map at 10 kV, (<b>c</b>) SEM spectrum label at 2 kV, (<b>d</b>) EDS spectrum 2 at 10 kV and (<b>e</b>) EDS spectrum 3 at 10 kV.</p>
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<p>(<b>a</b>) SEM image of magnetite on paper at 2 kV, (<b>b</b>) EDS element map at 10 kV, (<b>c</b>) SEM spectrum label at 2 kV, (<b>d</b>) EDS spectrum 2 at 10 kV and (<b>e</b>) EDS spectrum 3 at 10 kV.</p>
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<p>(<b>a</b>) Nickel droplet on paper SEM at 2 kV, (<b>b</b>) EDS layered map at 10 kV, (<b>c</b>) nickel EDS spectrum 11 and (<b>d</b>) nickel EDS spectrum 12 at 10 kV.</p>
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<p>Change in inductance as a function of strain from 0.22 µε to 1.3 µε for (<b>a</b>) magnetite print designs and (<b>b</b>) nickel print designs.</p>
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<p>Magnetite print designs linear fitting showing (<b>a</b>) intercept, (<b>b</b>) gradient and (<b>c</b>) R-squared value.</p>
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<p>Magnetite print designs linear fitting showing (<b>a</b>) intercept, (<b>b</b>) gradient and (<b>c</b>) R-squared value.</p>
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<p>Nickel print designs linear fitting graph showing (<b>a</b>) intercept, (<b>b</b>) gradient and (<b>c</b>) R-squared value.</p>
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<p>Nickel print designs linear fitting graph showing (<b>a</b>) intercept, (<b>b</b>) gradient and (<b>c</b>) R-squared value.</p>
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<p>Magnetite print in (<b>a</b>) 10, (<b>b</b>) 20, (<b>c</b>) 30 layered square design.</p>
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<p>Bending test of magnetite square designs of 10, 20 and 30 layers measuring the inductance as a function of strain.</p>
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<p>Magnetite coil print on CFRP.</p>
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<p>Inductance of coil print on CFRP with 200 coil inductor.</p>
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<p>Strain calculated values for radius of curvature from 1000 to 100 for paper and CFRP.</p>
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<p>Print head nozzle during jetting metal NP when jetting from nozzle (<b>a</b>), single droplet (<b>b</b>), satellite (<b>c</b>) and clogged (<b>d</b>).</p>
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20 pages, 9973 KiB  
Article
The Preparation Phase of the 2022 ML 5.7 Offshore Fano (Italy) Earthquake: A Multiparametric–Multilayer Approach
by Martina Orlando, Angelo De Santis, Mariagrazia De Caro, Loredana Perrone, Saioa A. Campuzano, Gianfranco Cianchini, Alessandro Piscini, Serena D’Arcangelo, Massimo Calcara, Cristiano Fidani, Adriano Nardi, Dario Sabbagh and Maurizio Soldani
Geosciences 2024, 14(7), 191; https://doi.org/10.3390/geosciences14070191 - 16 Jul 2024
Viewed by 545
Abstract
This paper presents an analysis of anomalies detected during the preparatory phase of the 9 November 2022 ML = 5.7 earthquake, occurring approximately 30 km off the coast of the Marche region in the Adriatic Sea (Italy). It was the largest earthquake [...] Read more.
This paper presents an analysis of anomalies detected during the preparatory phase of the 9 November 2022 ML = 5.7 earthquake, occurring approximately 30 km off the coast of the Marche region in the Adriatic Sea (Italy). It was the largest earthquake in Italy in the last 5 years. According to lithosphere–atmosphere–ionosphere coupling (LAIC) models, such earthquake could induce anomalies in various observable variables, from the Earth’s surface to the ionosphere. Therefore, a multiparametric and multilayer approach based on ground and satellite data collected in each geolayer was adopted. This included the revised accelerated moment release method, the identification of anomalies in atmospheric parameters, such as Skin Temperature and Outgoing Longwave Radiation, and ionospheric signals, such as Es and F2 layer parameters from ionosonde measurements, magnetic field from Swarm satellites, and energetic electron precipitations from NOAA satellites. Several anomalies were detected in the days preceding the earthquake, revealing that their cumulative occurrence follows an exponential trend from the ground, progressing towards the upper atmosphere and the ionosphere. This progression of anomalies through different geolayers cannot simply be attributed to chance and is likely associated with the preparation phase of this earthquake, supporting the LAIC approach. Full article
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<p>Summary map of the study conducted: the different layers analyzed are observed, from bottom to top. For each layer, the types of parameters considered are indicated.</p>
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<p>Simplified structural map of Italy, with the epicenter of the 9 November 2022 Fano EQ indicated by a small yellow star (modified from [<a href="#B40-geosciences-14-00191" class="html-bibr">40</a>]).</p>
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<p>Seismotectonic framework of the coastal area of the Marche region. The light blue squares represent the seismic sequence from 9 November 2022 to 14 February 2023; the first event is marked with a yellow star and the second event is shown with a green star. Historical and instrumental earthquakes from CPTI15 [<a href="#B45-geosciences-14-00191" class="html-bibr">45</a>] are indicated with colored squares, with earthquakes of Mw ≥ 5.5 highlighted in red. The surface projections of seismogenic zones are depicted with orange ribbons [<a href="#B41-geosciences-14-00191" class="html-bibr">41</a>]. The focal mechanisms of the 9 November 2022 earthquake and the event of 30 October 1930, represented by the grey and white balls, come from TDMT (Time Domain Moment Tensor) and Vannoli et al. [<a href="#B46-geosciences-14-00191" class="html-bibr">46</a>], respectively (modified from [<a href="#B30-geosciences-14-00191" class="html-bibr">30</a>]).</p>
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<p>Spatial distribution of the 174.723 events extracted from the INGV Catalog during the period 2012–2022 within a circular radius of 150 km from the epicenter of the main EQ, highlighted by the yellow star. The grey and white sphere represents the focal mechanism of the earthquake on 9 November 2022. The chosen radius includes the Central Italy sequence (2016), identifiable by the cluster of events to the south near the edge of the area.</p>
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<p>Spatial distribution of ten years of seismicity around the mainshock, in a radius of 150 km from the epicenter (largest green circle). Blue and red dots (confined within blue and red circles, respectively) represent the events contributing to the acceleration found by the R-AMR analysis. The red dots are the events closer to the seismogenic fault.</p>
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<p>Scenario of hypothesized pre-EQ coupling processes between the lithosphere of Central Italy and areas where possible EBs could be detected by LEO satellites.</p>
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<p>Outcome of the R-AMR algorithm applied to the extracted seismic dataset. The red points represent EQs that are closer to the fault (within 37 km) than those represented by the blue points. At the bottom of the main figure, the magnitudes of the involved events are represented: red is used for EQs falling within 37 km from the fault and green those outside that limit.</p>
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<p>Analysis of the SKT parameter for the Fano EQ with comparison between the 2022 time series (dashed red line) and the historical time series (1980–2021, blue line). Evidenced by red circles there are two quite anomalous values near the second standard deviations from the mean: the first one refers to 18 August, and the second one to 15 September.</p>
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<p>Maps of the SKT anomalous days in terms of difference with respect to the historical mean: (<b>a</b>) 18 August; (<b>b</b>) 15 September. The EQ epicenter is indicated by the central star. SKT is defined only on land.</p>
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<p>Analysis of the OLR for the Fano EQ with the identification of two anomalous days that exceed the historical average calculated from 1980 to 2021 by two standard deviations.</p>
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<p>Maps of OLR anomalous days maps in terms of difference with respect to the historical mean: (<b>a</b>) 5 September; (<b>b</b>) 12 September. The epicenter is indicated by the central star.</p>
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<p>The anomaly observed 9 days before the 9 November 2022 Fano EQ using Δh’Es, δfbEs, and δfoF2 variations, along with 3 h Kp index values given as a reference of geomagnetic activity.</p>
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<p>Ionosonde anomaly for the 9 November 2022 M5.7 Fano EQ (red square), compared to the relationship between ∆T·R and M previously found by the analysis of the most powerful Central Italian EQs since 1984 (red line and black squares).</p>
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<p>Anomalies found 4 days after (<b>a</b>) and 75 days before the Fano EQ (<b>b</b>) by means of an automatic search for magnetic anomalies 90 days before and 10 days after the EQ; MASS algorithm (kt = 2.5) applied to Swarm A satellite. The anomalies are evidenced by coloured rectangles. The vertical red line on the geographical map represents the satellite track.</p>
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<p>Three-dimensional representation of the NOAA-15 semi-orbits on 8 November 2022; EB evidenced by a red circle while the star identified the EQ epicenter.</p>
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<p>In a comprehensive approach of the anomalies, the cumulative number of anomalies for Fano EQ is shown here. It is possible to notice that the anomalies appear in time mostly from below (seismic data in the lithosphere) to above (atmosphere and ionosphere). The red curve is an exponential fit of the data.</p>
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