Search Results (60)

Magnetorheological (MR) foams represent a class of smart materials with unique tunable viscoelastic properties when subjected to external magnetic fields. Combining porous structures with embedded magnetic particles, these materials address challenges such as leakage and sedimentation, typically encountered in conventional MR fluids while offering advantages like lightweight design, acoustic absorption, high energy harvesting capability, and tailored mechanical responses. Despite their potential, challenges such as non-uniform particle dispersion, limited durability under cyclic loads, and suboptimal magneto-mechanical coupling continue to hinder their broader adoption. This review systematically addresses these issues by evaluating the synthesis methods (ex situ vs. in situ), microstructural design strategies, and the role of magnetic particle alignment under varying curing conditions. Special attention is given to the influence of material composition—including matrix types, magnetic fillers, and additives—on the mechanical and magnetorheological behaviors. While the primary focus of this review is on MR foams, relevant studies on MR elastomers, which share fundamental principles, are also considered to provide a broader context. Recent advancements are also discussed, including the growing use of artificial intelligence (AI) to predict the rheological and magneto-mechanical behavior of MR materials, model complex device responses, and optimize material composition and processing conditions. AI applications in MR systems range from estimating shear stress, viscosity, and storage/loss moduli to analyzing nonlinear hysteresis, magnetostriction, and mixed-mode loading behavior. These data-driven approaches offer powerful new capabilities for material design and performance optimization, helping overcome long-standing limitations in conventional modeling techniques. Despite significant progress in MR foams, several challenges remain to be addressed, including achieving uniform particle dispersion, enhancing viscoelastic performance (storage modulus and MR effect), and improving durability under cyclic loading. Addressing these issues is essential for unlocking the full potential of MR foams in demanding applications where consistent performance, mechanical reliability, and long-term stability are crucial for safety, effectiveness, and operational longevity. By bridging experimental methods, theoretical modeling, and AI-driven design, this work identifies pathways toward enhancing the functionality and reliability of MR foams for applications in vibration damping, energy harvesting, biomedical devices, and soft robotics. Full article

Magnetorheological elastomers (MREs) are smart composite materials with tunable mechanical properties by ferromagnetic particle interactions. This study applied the microstructure-based dipole and Maxwell methods to evaluate the magneto-mechanical coupling and magnetostrictive responses of MREs, focusing on various particle distributions. The finite element modeling of representative volume elements with fixed volume fractions revealed that the straight chain microstructure exhibits the most significant magnetostrictive effect due to its low initial shear stiffness and significant magnetic force contributions. For particle separations exceeding three radii, the dipole and Maxwell methods yield consistent results for vertically or horizontally aligned particles. For particle separations greater than three radii, the dipole and Maxwell methods produce consistent results for vertically and horizontally aligned particles. However, discrepancies emerge for angled configurations and complex microstructures, with the largest deviation observed in the hexagonal particle distribution, where the two methods differ by approximately 27%. These findings highlight the importance of selecting appropriate modeling methods for optimizing MRE performance. Since anisotropic MREs with straight-chain alignments are the most widely used, our results confirm that the dipole method offers an efficient alternative to the Maxwell method for simulating these structures. Full article

Background: Regeneration in the case of major burn subjects must involve tissue and structural regeneration, but also functional regeneration, as scars derived from burns often compromise motility. Electromagnetic fields and electrical stimulation may be a possible treatment for these cases, considering they cause a thermal effect and magneto-mechanical transduction first and selective tissue stimulation second. Methods: A case of a majorly burned woman with severe motor deficits, treated with electromagnetic fields and electrical stimulation in vacuum, associated with a personalized nutritional program, was described. The latter was necessary to favor weight loss with the preservation of the weakened structure. Ultrasonography, Doppler ultrasound, and body composition were measured. Moreover, postural evaluation was performed. Results: Immediately after the treatment, a restructuring of all tissue was seen. After 6 months, the tissue regeneration was evident, with neo-angiogenesis. From the functional point of view, her motility improved, and she stopped using a walker. Conclusions: The combined therapy allows her to obtain unthinkable results in a short time. For this reason, it could become the elective treatment for major burn scars. Full article

Magnetic hydrogel soft robots have shown great potential in various fields. However, their contact dynamic behaviors are complex, considering stick–slip motion at the contact interface, and lack accurate computational models to analyze them. This paper improves the numerical computational method for hydrogel materials with magneto-mechanical coupling effect, analyses the inchworm-like contact motion of the biomimetic bipedal magnetic hydrogel soft robot, and designs and optimizes the robot’s structure. In the constitutive model, a correction factor representing the influence of the direction of magnetic flux density on the domain density has been introduced. The magnetic part of the Helmholtz free energy has been redefined as the magnetic potential energy, which can be used to explain the phenomenon that the material will still deform when the magnetic flux density is parallel to the external magnetic field. The accuracy of the simulation is verified by comparing numerical solutions with experimental results for a magnetic hydrogel cantilever beam. Furthermore, employing the present methods, the locomotion of a magnetic hydrogel soft robot modeled after the inchworm’s gait is simulated, and the influence of the coefficient of friction on its movement is discussed. The numerical results clearly display the control effect of the external magnetic field on the robot’s motion. Full article

A numerical tool for simulating the detection signals of electromagnetic nondestructive testing technology (ENDT) is of great significance for studying detection mechanisms and improving detection efficiency. However, the quantitative analysis methods for ENDT have not yet been sufficiently studied due to the absence of an effective constitutive model. This paper proposed a new magneto–mechanical model that can reflect the dependence of relative permeability on elasto–plastic deformation and proposed a finite element–infinite element coupling method that can replace the traditional finite element truncation boundary. The validity of the finite element–infinite element coupling method is verified by the experimental result of testing electromagnetic analysis methods using TEAM Problem 7. Then, the reliability and accuracy of the proposed model are verified by comparing the simulation results under elasto–plastic deformation with experimental results. This paper also investigates the effect of elasto–plastic deformation on the transient magnetic flux signal, a quantitative hyperbolic tangent model between Bz_pp (peak–peak value of the normal component of magnetic flux signal) and elastic stress, and the exponential function relationship between Bz_pp and plastic deformation is established. In addition, the difference and mechanism of a magnetic flux signal under elasto–plastic deformations are analyzed. The results reveal that the variation of the transient magnetic flux signal is mainly due to domain wall pinning, which is significantly affected by elasto–plastic deformation. The results of this paper are important for improving the accuracy of quantitative ENDT for elasto–plastic deformation. Full article

Multifunctional stretchable rubber composites are gaining attention due to their unique electrical, mechanical, and magnetic properties. However, their high production costs pose economic challenges. This study explores the use of cost-effective metal powders—iron, aluminum, and their 1:1 (vol/vol) hybrid filler—in styrene–butadiene rubber composites, varying from 10 to 20 vol%. The effects of these metal particles on the mechanical, electrical, morphological, and swelling properties were investigated. Metal particles generally act as non-reinforcing fillers but can significantly enhance the mechanical modulus, electrical, and magnetic properties based on the filler structure and the filler–rubber interactions. Iron-based composites exhibit significant electrical conductivity and excellent magnetic properties. Aluminum enhances the modulus, while the combination yields average mechanical properties with added magnetic characteristics. Iron demonstrates higher reactivity with sulfur-based crosslinking ingredients, adversely affecting the rubber matrix’s crosslinks, as shown by swelling tests. This reactivity is attributed to iron’s transition metal characteristics. At 20 vol%, iron-filled composites display the highest magnetic anisotropic effect on toughness (~25%) under a magnetic field by permanent magnets and excellent electrical conductivity (1.5 × 10⁻² S/m). While iron significantly boosts the electrical and magnetic properties, higher filler amounts degrade the mechanical properties. These composites are currently suitable for electrical and smart mechanical applications, but incorporating reinforcing fillers could enhance their robustness for broader applications. Full article

Weak magnetic detection technology can detect stress concentration areas in ferromagnetic materials. However, the stress non-uniform characteristics of pipeline welds lead to significant differences in stress distribution range and values between inner wall welds and outer wall welds. This discrepancy makes it crucial to further evaluate the impact of stress non-uniformity on magnetic signals. To study the magnetic signal characteristics under the influence of residual stress in weld seams, a magneto-mechanical analytical model was established based on the magnetic charge theory and the distribution characteristics of residual stress in the weld seam. The magneto-mechanical relationship and magnetic signal distribution characteristics at the inner and outer wall welds of the pipeline are calculated. Furthermore, the effects of different excitation intensities on the amplitude growth characteristics of magnetic signals are analyzed and compared. To verify the analysis model, weld detection experiments with different excitation intensities were designed. The results show that both the peak-to-valley values of the normal component and the peak values of the tangential component of the outer wall weld are lower than those of the inner wall weld. Conversely, the peak-to-valley width of the normal component and the peak width of the tangential component are greater than those of the inner wall weld. Additionally, the rate of increase in weak magnetic signal amplitude decreases in a first-order exponential relationship with increasing excitation intensity. The average decay rates of the normal and tangential component amplitude growth rates for the inner wall weld are 34.03% and 27.9%, respectively, while for the outer wall weld, they are 31.75% and 28.01%, respectively. This study contributes to the identification and quantitative assessment of weak magnetic signals in inner and outer wall welds. Full article

Photothermal therapy (PTT) can overcome cancer treatment resistance by enhancing the cell membrane permeability, facilitating drug accumulation, and promoting drug release within the tumor tissue. Iron oxide nanoparticles (IONPs) have emerged as effective agents for PTT due to their unique properties and biocompatibility. Approved for the treatment of anemia, as MRI contrast agents, and as magnetic hyperthermia mediators, IONPs also offer excellent light-to-heat conversion and can be manipulated using external magnetic fields for targeted accumulation in specific tissue. Optimizing parameters such as the laser wavelength, power density, shape, size, iron oxidation state, functionalization, and concentration is crucial for IONPs’ effectiveness. In addition to PTT, IONPs enhance other cancer treatment modalities. They improve tumor oxygenation, enhancing the efficacy of radiotherapy and photodynamic therapy. IONPs can also trigger ferroptosis, a programmed cell death pathway mediated by iron-dependent lipid peroxidation. Their magneto-mechanical effect allows them to exert a mechanical force on cancer cells to destroy tumors, minimizing the damage to healthy tissue. This review outlines strategies for the management of the photothermal performance and PTT efficiency with iron oxide nanoparticles, as well as synergies with other cancer therapies. Full article

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations. Full article

“Gel-type” soft and stretchable magneto-mechanical composites made of silicone rubber and iron particles are in focus because of their high magnetic sensitivity, and intelligence perspective. The “intelligence” mentioned here is related to the “smartness” of these magneto-rheological elastomers (MREs) to tune the “mechanical stiffness” and “output voltage” in energy-harvesting applications by switching magnetic fields. Hence, this work develops “gel-type” soft composites based on rubber reinforced with iron particles in a hybrid with piezoelectric fillers such as barium titanate. A further aspect of the work relies on studying the mechanical stability of intelligence and the stretchability of the composites. For example, the stretchability was 105% (control), and higher for 158% (60 per 100 parts of rubber (phr) of barium titanate, BaTiO₃), 149% (60 phr of electrolyte iron particles, EIP), and 148% (60 phr of BaTiO₃ + EIP hybrid). Then, the magneto-mechanical aspect will be investigated to explore the magnetic sensitivity of these “gel-type” soft composites with a change in mechanical stiffness under a magnetic field. For example, the anisotropic effect was 14.3% (60 phr of EIP), and 4.4% (60 phr of hybrid). Finally, energy harvesting was performed. For example, the isotropic samples exhibit ~20 mV (60 phr of BaTiO₃), ~5.4 mV (60 phr of EIP), and ~3.7 mV (60 phr of hybrid). However, the anisotropic samples exhibit ~5.6 mV (60 phr of EIP), and ~8.8 mV (60 phr of hybrid). In the end, the composites prepared have three configurations, namely one with electro-mechanical aspects, another with magnetic sensitivity, and a third with both features. Overall, the experimental outcomes will make fabricated composites useful for different intelligent and stretchable applications. Full article

The resonant magnetoelectric (ME) effect of Fe₇₈Si₉B₁₃/Pb(Zr,Ti)O₃ (FeSiB/PZT) composites with a surface-modified Fe₇₈Si₉B₁₃ amorphous alloy has been studied. The surface-modified FeSiB can improve the ME coefficient at the resonant frequency by optimizing the magnetomechancial power conversion efficiency. The maximum ME coefficient of the surface-modified ribbons combined with soft PZT (PZT5) is two-thirds larger than that of the composites with fully amorphous ribbons. Meanwhile, the maximum value of the ME coefficient with surface-modified FeSiB ribbons and hard PZT (PZT8) is one-third higher compared with the fully amorphous composites. In addition, experimental results of magnetomechanical coupling properties of FeSiB/PZT composites with or without piezoelectric layers indicate that the power efficiency of the composites first decreases and then increases with the increase in the number of FeSiB layers. When the surface crystalline FeSiB ribbons are combined with a commercially available hard piezoelectric ceramic plate, the maximum magnetoelectric coupling coefficient of the ME composite reaches 5522 V/(Oe*cm), of which the electromechanical resonant frequency is 23.89 kHz. Full article

Isotropic magnetorheological elastomers (MREs) with hybrid-size particles are proposed to tailor the zero-field elastic modulus and the relative magnetorheological rate. The hyperelastic magneto–mechanical property of MREs with hybrid-size CIPs (carbonyl iron particles) was experimentally investigated under large strain, which showed differential hyperelastic mechanical behavior with different hybrid-size ratios. Quasi-static magneto–mechanical compression tests corresponding to MREs with different hybrid size ratios and mass fractions were performed to analyze the effects of hybrid size ratio, magnetic flux density, and CIP mass fraction on the magneto–mechanical properties. An extended Knowles magneto–mechanical hyperelastic model based on magnetic energy, coupling the magnetic interaction, is proposed to predict the influence of mass fraction, hybrid size ratio, and magnetic flux density on the magneto–mechanical properties of isotropic MRE. Comparing the experimental and predicted results, the proposed model can accurately evaluate the quasi-static compressive magneto–mechanical properties, which show that the predicted mean square deviations of the magneto–mechanical constitutive curves for different mass fractions are all in the range of 0.9–1. The results demonstrate that the proposed hyperelastic magneto–mechanical model, evaluating the magneto–mechanical properties of isotropic MREs with hybrid-size CIPs, has a significant stress–strain relationship. The proposed model is important for the characterization of magneto–mechanical properties of MRE-based smart devices. Full article

Magnetic nanoparticles based on iron oxide attract researchers’ attention due to a wide range of possible applications in biomedicine. As synthesized, most of the magnetic nanoparticles do not form the stable colloidal solutions that are required for the evaluation of their interactions with cells or their efficacy on animal models. For further application in biomedicine, magnetic nanoparticles must be further modified with biocompatible coating. Both the size and shape of magnetic nanoparticles and the chemical composition of the coating have an effect on magnetic nanoparticles’ interactions with living objects. Thus, a universal method for magnetic nanoparticles’ stabilization in water solutions is needed, regardless of how magnetic nanoparticles were initially synthesized. In this paper, we propose the versatile and highly reproducible ligand exchange technique of coating with 3,4-dihydroxiphenylacetic acid (DOPAC), based on the formation of Fe-O bonds with hydroxyl groups of DOPAC leading to the hydrophilization of the magnetic nanoparticles’ surfaces following phase transfer from organic solutions to water. The proposed technique allows for obtaining stable water–colloidal solutions of magnetic nanoparticles with sizes from 21 to 307 nm synthesized by thermal decomposition or coprecipitation techniques. Those stabilized by DOPAC nanoparticles were shown to be efficient in the magnetomechanical actuation of DNA duplexes, drug delivery of doxorubicin to cancer cells, and targeted delivery by conjugation with antibodies. Moreover, the diversity of possible biomedical applications of the resulting nanoparticles was presented. This finding is important in terms of nanoparticle design for various biomedical applications and will reduce nanomedicines manufacturing time, along with difficulties related to comparative studies of magnetic nanoparticles with different magnetic core characteristics. Full article

Metal magnetic memory (MMM) is a nondestructive testing technology based on the magnetomechanical effect, which is widely used in the qualitative detection of stress concentration zones for welded joints. However, there is inevitable residual stress after welding, which brings the bottleneck of quantitative identification between the weld residual stress concentration and the early hidden damage. In order to overcome the bottleneck of quantitative identification of weld defect levels with MMM technology, a modified maximum likelihood estimation (MLE) MMM quantitative identifying model is first proposed. The experimental materials are Q235B welded plate specimens. Fatigue tension experiments were operated to find the MMM feature laws of critical hidden crack by comparing with synchronous X-ray detection results. Six MMM characteristic parameters, which are, ΔH_p(x), G_x^max, Z_x^max, ΔH_p(y), G_y^max and Z_y^max, are extracted corresponding to the normal state, the hidden crack state and the macroscopic crack, respectively. The MLE values of the six parameters are obtained by the kernel density functions with optimized bandwidth from the view of mathematical statistics. Furthermore, the modified MLE MMM quantitative identifying model is established based on D–S theory to overcome the partial overlap of MLE values among different defect levels, of which the uncertainty is as low as 0.3%. The verification result from scanning electron microscopy (SEM) is consistent with the prediction of the modified MLE MMM model, which provides a new method for quantitative identification of weld defect levels. Full article

Giant magnetostrictive transducer can be widely used in active vibration control, micro-positioning mechanism, energy harvesting system, and ultrasonic machining. Hysteresis and coupling effects are present in transducer behavior. The accurate prediction of output characteristics is critical for a transducer. A dynamic characteristic model of a transducer is proposed, by providing a modeling methodology capable of characterizing the nonlinearities. To attain this objective, the output displacement, acceleration, and force are discussed, the effects of operating conditions on the performance of Terfenol-D are studied, and a magneto-mechanical model for the behavior of transducer is proposed. A prototype of the transducer is fabricated and tested to verify the proposed model. The output displacement, acceleration, and force have been theoretically and experimentally studied at different working conditions. The results show that, the displacement amplitude, acceleration amplitude, and force amplitude are about 49 μm, 1943 m/s², and 20 N. The error between the model and experimental results are 3 μm, 57 m/s², and 0.2 N. Calculation results and experimental results show a good agreement. Full article