Search Results (194)

This work presents a novel type of soft reconfigurable mobile robot with multimodal locomotion, which is created using a controllable magneto-elastica-reinforced composite elastomer. The rope motor-driven method is employed to modulate magnetics–mechanics coupling effects and enable the magneto-elastica-reinforced elastomer actuator to produce controllable deformations. Furthermore, the 3D-printed magneto-elastica-reinforced elastomer actuators are assembled into several typical robotic patterns: linear configuration, parallel configuration, and triangular configuration. As a proof of concept, a few of the basic locomotive modes are demonstrated including squirming-type crawling at a speed of 1.11 $\mathrm{m}\mathrm{m}/\mathrm{s}$, crawling with turning functions at a speed of 1.11 $\mathrm{m}\mathrm{m}/\mathrm{s}$, and omnidirectional crawling at a speed of 1.25 $\mathrm{m}\mathrm{m}/\mathrm{s}$. Notably, the embedded magnetic balls produce magnetic adhesion on the ferromagnetic surfaces, which enables the soft mobile robot to climb upside-down on ferromagnetic curved surfaces. In the experiment, the inverted ceiling-based inverted crawling speed is 2.17 $\mathrm{m}\mathrm{m}/\mathrm{s}$, and the inverted freeform surface-based inverted crawling speed is 3.40 $\mathrm{m}\mathrm{m}/\mathrm{s}$. As indicated by the experimental results, the proposed robot has the advantages of a simple structure, low cost, reconfigurable multimodal motion ability, and so on, and has potential application in the inspection of high-value assets and operations in confined environments. Full article

Magnetorheological fluids (MRFs) and elastomers (MREs) are two types of smart materials that exhibit modifiable rheological properties in response to an applied magnetic field. Although they share a similarity in their magnetorheological response, these two materials differ in their nature, structure, and mechanical behavior when exposed to a magnetic field. They also have distinct application differences due to their specific rheological properties. These fundamental differences therefore influence their properties and applications in various industrial fields. This review provides a synthesis of the distinct characteristics of MRFs and MREs. The differences in their composition, rheological behavior, mechanical properties, and respective applications are summarized and highlighted. This analysis will enable a comprehensive understanding of these differences, thereby allowing for the appropriate selection of the material based on the specific requirements of a given application and fostering the development of new applications utilizing these MR materials. Full article

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

Traditional magnetorheological elastomers (MREs) often suffer from limited modulus tunability and insufficient energy dissipation, which restrict their applications. This study prepared a novel composite material by an MR gel (MRG) embedded within the MRE, called the MRE encapsulating MRG, to synergistically enhance these properties. Annular and radial MRE encapsulating MRG configurations were fabricated using 3D-printed molds, and their dynamic mechanical performance was characterized under varying magnetic fields (0–1 T) via a rheometer. The results revealed that the composite materials demonstrated significantly improved magnetic-induced modulus and magnetorheological (MR) effects compared to conventional MREs. Specifically, the annular MRE encapsulating MRG exhibited a 238.47% increase in the MR effect and a 51.35% enhancement in the magnetic-induced modulus compared to traditional MREs. Correspondingly, the radial configuration showed respective improvements of 168.19% and 27.03%. Furthermore, both the annular and radial composites displayed superior energy dissipation capabilities, with loss factors 2.68 and 2.03 times greater than those of pure MREs, respectively. Dynamic response tests indicated that composite materials, particularly the annular MRE encapsulating MRG, achieve faster response times. These advancements highlight the composite’s potential for high-precision damping systems, vibration isolation, and adaptive control applications. Full article

Touch is a crucial sense for advanced organisms, particularly humans, as it provides essential information about the shape, size, and texture of contacting objects. In robotics and automation, the integration of tactile sensors has become increasingly relevant, enabling devices to properly interact with their environment. This study aimed to develop a biomimetic, skin-inspired tactile sensor device capable of sensing applied force, characterizing it in three dimensions, and determining the point of application. The device was designed as a 4 × 4 matrix of tunneling magnetoresistive sensors, which provide a higher sensitivity in comparison to the ones based on the Hall effect, the current standard in tactile sensors. These detect magnetic field changes along a single axis, wire-bonded to a PCB and encapsulated in epoxy. This sensing array detects the magnetic field from an overlayed magnetorheological elastomer composed of Ecoflex and 5 µm neodymium–iron–boron ferromagnetic particles. Structural integrity tests showed that the device could withstand forces above 100 N, with an epoxy coverage of 0.12 mL per sensor chip. A 3D movement stage equipped with an indenting tip and force sensor was used to collect device data, which was then used to train neural network models to predict the contact location and 3D magnitude of the applied force. The magnitude-sensing model was trained on 31,260 data points, being able to accurately characterize force with a mean absolute error ranging between 0.07 and 0.17 N. The spatial sensitivity model was trained on 171,008 points and achieved a mean absolute error of 0.26 mm when predicting the location of applied force within a sensitive area of 25.5 mm × 25.5 mm using sensors spaced 4.5 mm apart. For points outside the testing range, the mean absolute error was 0.63 mm. Full article

The macroscopic magnetic properties of magnetorheological elastomers (MREs) are influenced by their microstructure, yet limited investigations has been conducted on this subject to date. In this paper, a microstructure-based model is proposed to investigate the magnetization response of MREs. The dipole theory is employed to compute the local magnetic field, and a fitting equation derived from finite element analysis is used to correct the magnetic field. The Fröhlich–Kennelly equation is applied to describe the nonlinear magnetic properties of the particle material. Based on experimental observations, a body-centered tetragonal (BCT) model is established to describe the magnetization properties of anisotropic MREs. The proposed model is validated by comparison with experimental data and can be utilized to predict the effective susceptibility of MREs. The effects of particle volume fraction, the direction of the external magnetic field, and the shape of the MRE samples can also be analyzed using this model. Full article

Two-layered structures consisting of piezopolymer and magnetic elastomer were investigated as magnetoelectric material. Three types of magnetic elastomer based on cobalt ferrite (CoFe₂O₄) and Ni- or Zn-substituted CoFe₂O₄ nanoparticles were used as magnetically sensitive layers. Cobalt ferrite nanoparticles are considered one of the most promising metal-oxide nanomaterials because of their favorable magnetic properties, such as high saturation magnetization and magnetic anisotropy. The substitution of Co²⁺ in cobalt ferrite with other transition metals allows for additional tailoring of these properties. The modified magnetic behavior of the substituted CoFe₂O₄ nanoparticles directly influenced the magnetic properties of magnetic elastomers and, consequently, the magnetoelectric response of composite structures. In this case, the resonant frequency of the magnetoelectric effect remained largely independent of the type of magnetic nanoparticles in the magnetic elastomer layer but its magnitude increased upon Zn substitution up to ~107 mV·cm⁻¹·Oe⁻¹. These findings highlight the potential of chemically engineered magnetic properties of CoFe₂O₄ nanoparticles for manufacturing magnetoelectric composites to expand their applications in energy harvesting and sensors. Full article

Flexible magnetic tactile sensors hold transformative potential in robotics and human–computer interactions by enabling precise force detection. However, existing sensors face challenges in balancing sensitivity, detection range, and structural adaptability for sensing force. This study proposed a pre-compressed magnetization method to address these limitations by amplifying the magnetoelastic effect through optimized magnetization direction distribution of the elastomer. A body-centered cubic lattice-structured magnetoelastomer featuring regular deformation under compression was fabricated via digital light processing (DLP) to validate this method. Finite element simulations and experimental analyses revealed that magnetizing the material under 60% compression strain optimized magnetization direction distribution, enhancing force–magnetic coupling. Integrating the magnetic elastomer with a hall sensor, the prepared tactile sensor demonstrated a low detection limit (1 mN), wide detection range (0.001–10 N), rapid response/recovery times (40 ms/50 ms), and durability (>1500 cycles). By using machine learning, the sensor enabled accurate 3D force prediction. Full article

Soft robots, constructed from deformable materials, offer significant advantages over rigid robots by mimicking biological tissues and providing enhanced adaptability, safety, and functionality across various applications. Central to these robots are electroactive polymer (EAP) actuators, which allow large deformations in response to external stimuli. This review examines various EAP actuators, including dielectric elastomers, liquid crystal elastomers (LCEs), and ionic polymers, focusing on their potential as artificial muscles. EAPs, particularly ionic and electronic varieties, are noted for their high actuation strain, flexibility, lightweight nature, and energy efficiency, making them ideal for applications in mechatronics, robotics, and biomedical engineering. This review also highlights piezoelectric polymers like polyvinylidene fluoride (PVDF), known for their flexibility, biocompatibility, and ease of fabrication, contributing to tactile and pressure sensing in robotic systems. Additionally, conducting polymers, with their fast actuation speeds and high strain capabilities, are explored, alongside magnetic polymer composites (MPCs) with applications in biomedicine and electronics. The integration of machine learning (ML) and the Internet of Things (IoT) is transforming soft robotics, enhancing actuation, control, and design. Finally, the paper discusses future directions in soft robotics, focusing on self-healing composites, bio-inspired designs, sustainability, and the continued integration of IoT and ML for intelligent, adaptive, and responsive robotic systems. 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

In order to meet the dual requirements of hydraulic dynamic sealing to ensure a reduction in friction, this study prepared polyurethane-based magnetorheological elastomers (MREs). The compression performance of isotropic and anisotropic samples under a magnetic field was tested in samples containing carbonyl iron powder (CIP) particles with different volume contents and particle sizes. The compression performance of isotropic and anisotropic samples under the magnetic field was tested under static loading, and the friction coefficient changes in isotropic and anisotropic samples under a magnetic field were analyzed by a friction testing machine. The test results show that under static compression load, the contact stress of isotropic and anisotropic specimens increases with the increase in magnetic field strength, and the magnitude of the contact stress changes when the increase in magnetic field strength is proportional to the CIP content and CIP particle size of the specimen. The friction test results of the samples showed that an increase in magnetic field strength, CIP particle diameter, and CIP content reduces the friction coefficient of the CIP particle polyurethane-based magnetorheological elastomer samples, and the variation in the magnetic friction coefficient of anisotropic samples is greater than that of isotropic samples. This research result indicates that utilizing the magneto-mechanical properties of polyurethane-based magnetorheological elastomers can provide an innovative solution to the inherent contradiction between increasing contact stress and avoiding wear in the dynamic sealing of hydraulic systems, which can provide controllable sealing performance for hydraulic dynamic sealing components in specific application scenarios, enabling them to have a better sealing ability while reducing the friction coefficient of the sealing pair. Full article

The vibration of a ship’s propulsion shaft system directly affects the ship’s lifespan, and many studies have designed vibration absorbers only for one of the natural frequencies of a ship’s propulsion shaft system without considering the influence of multiple low-order resonance frequencies. In this paper, a vibration absorber combined with a magnetorheological elastomer vibration absorber and a rubber vibration absorber in series is designed, and it can cover two torsional natural frequency band ranges to achieve better vibration reduction performances in multiple different torsional natural frequencies. The torsional natural frequency of the propulsion shafting of a 45 m fishing vessel is determined based on a multiple-degrees-of-freedom equivalent discretization model. Two natural frequencies, 22.4 Hz and 131.4 Hz, of a ship propulsion shaft system are selected as the design goal parameters of the combined vibration absorber. The magnetic field is simulated to ensure that the magnetic field generated by an energized coil can meet requirements. Then, a dynamic simulation of the ship propulsion shaft system with a combined vibration absorber is conducted via co-simulation. Afterward, the device is installed on the intermediate shaft of the ship propulsion shaft system for simulation, and the vibration reduction effect of the device is analyzed at different frequencies by controlling the current. When the device is controlled to operate at the optimal frequency point, the results show that the angular acceleration vibration amplitude reduction around the first and third torsional natural frequencies of the propulsion shaft system reaches 90% and 18%, respectively. This study provides new ideas for the intelligent and controllable vibration damping of ship propulsion shaft systems, especially for the development trend of intelligent ship equipment under complex working conditions. Full article

Magnetic field-assisted control of magnetite location is a promising strategy for developing flexible, electrically conductive sensors with enhanced performance and adjustable properties. This study investigates the effect of static magnetic fields applied on thermoplastic elastomer (TPE) composites with magnetite and multi-walled carbon nanotubes (MWCNT). The composites were prepared by compression moulding and the magnetic field was applied on the mould cavity during processing. Composites were prepared with a range of concentrations of magnetite (1, 3, and 6 wt.%) and MWCNT (1 and 3 wt.%). The effect of particle concentration on composite viscosity was investigated. Rheological analysis showed that MWCNTs significantly increased the composite viscosity while magnetite had minimal impact, ensuring stable processing and facilitating particle orientation under a static magnetic field. Particle orientation and electrical conductivity were evaluated for the composites prepared with different particle concentrations under different processing temperatures. Magnetic field application at 190 °C enhanced magnetite/MWCNT interactions, substantially reducing electrical resistivity while preserving thermal stability. The composites showed no degradation at 220 °C and above, demonstrating suitability for high-temperature applications requiring thermal resilience. Furthermore, magnetite’s magnetic response facilitated precise sensor positioning and strong adhesion to polyimide substrates at 220 °C. These findings demonstrate a scalable and adaptable approach for enhancing sensor performance and positioning, with broad potential in flexible electronics. Full article

The application of smart materials in robots has attracted considerable research attention. This study developed an inchworm robot that integrates smart materials and a bionic design, using the unique properties of magnetorheological elastomers (MREs) to improve the performance of robots in complex environments, as well as their adaptability and movement efficiency. This research stems from solving the problem of the insufficient adaptability of traditional bionic robots on different surfaces. A robot that combines an MRE foot, an electromagnetic control system, and a bionic motion mechanism was designed and manufactured. The MRE foot was made from silicone rubber mixed with carbonyl iron particles at a specific ratio. Systematic experiments were conducted on three typical surfaces, PMMA, wood, and copper plates, to test the friction characteristics and motion performance of the robot. On all tested surfaces, the friction force of the MRE foot was reduced significantly after applying a magnetic field. For example, on the PMMA surface, the friction force of the front leg dropped from 2.09 N to 1.90 N, and that of the hind leg decreased from 3.34 N to 1.75 N. The robot movement speed increased by 1.79, 1.76, and 1.13 times on PMMA, wooden, and copper plate surfaces, respectively. The MRE-based intelligent foot design improved the environmental adaptability and movement efficiency of the inchworm robot significantly, providing new ideas for the application of intelligent materials in the field of bionic robots and solutions to movement challenges in complex environments. Full article

This review will examine the rapidly growing field of soft robotics, with a special emphasis on soft robotic actuators and their applications in bioengineering. Bioengineering has increasingly utilized soft robotics due to their mechanical adaptability and flexibility, with applications including drug delivery, assistive and wearable devices, artificial organs, and prosthetics. Soft robotic applications, as well as the responsive mechanisms employed in soft robotics, include electrical, magnetic, thermal, photo-responsive, and pressure-driven actuators. Special attention is given to hydraulically amplified self-healing electrostatic (HASEL) actuators due to their biomimetic properties and innovative combination of dielectric elastomer actuators (DEAs) and hydraulic actuators, which eliminates the limitations of each actuator while introducing capabilities such as self-healing. HASEL actuators combine the fast response and self-sensing features of DEAs, as well as the force generation and adaptability of hydraulic systems. Their self-healing ability from electrical damage not only makes HASELs a unique technology among others but also makes them promising for long-term bioengineering applications. A key contribution of this study is the comparative analysis of the soft actuators, presented in detailed tables. The performance of soft actuators is assessed against a common set of critical parameters, including specific power, strain, maximum actuation stress, energy efficiency, cycle life, and self-healing capabilities. This study has also identified some important research gaps and potential areas where soft robotics may still be developed in the future. Future research should focus on improvements in power supply design, long-term material durability, and enhanced energy efficiency. This review will serve as an intermediate reference for researchers and system designers, guiding the next generation of advancements in soft robotics within bioengineering. Full article