Search Results (253)

Four-dimensional (4D) printing integrates additive manufacturing with stimuli-responsive materials to fabricate biomedical implants and functional healthcare devices that undergo programmed, time-dependent changes in shape or function. Unlike static 3D-printed constructs, 4D-printed systems can respond to clinically relevant stimuli such as temperature, hydration, pH, light (including near-infrared), magnetic fields, or electrical inputs. These triggers drive defined actuation mechanisms, most commonly thermomechanical shape-memory recovery, swelling-induced morphing, and magnetothermal activation. This review synthesizes the principal material platforms used for biomedical 4D printing, including shape-memory polymers and alloys, hydrogels, liquid-crystal elastomers, and responsive composites, and links material choice to device behavior and translational feasibility. Applications are discussed across self-expanding stents, cardiac occluders, tissue-engineered constructs, implantable drug delivery systems, and adaptive wearables. Key translational challenges include sterilization compatibility, manufacturing reproducibility and quality control, safe stimulus delivery, predictable biodegradation and long-term biocompatibility, and regulatory pathway definition. Full article

Wireless Capsule Endoscopy (WCE) is a minimally invasive technology for imaging the gastrointestinal (GI) tract, particularly the small intestine, where conventional endoscopy faces accessibility limitations. Traditional capsule endoscopes rely on passive motion driven by natural peristalsis, which limits controllability and may increase the risk of capsule retention. To address these challenges, this study presents the design and experimental validation of a compliant active capsule endoscope actuated by four Shape Memory Alloy (SMA) spring actuators. A key feature of the proposed system is a steering mechanism that reuses the same SMA actuators responsible for locomotion, enabling control of the camera orientation without increasing system complexity, size, or weight. The capsule architecture consists of rigid polylactic acid (PLA) links connected through thermoplastic polyurethane (TPU) flexure hinges, fabricated using dual-material 3D printing. Nonlinear finite element analysis (FEA) was employed to optimize the flexure hinge geometry for maximum displacement while maintaining safe stress levels. To validate the concept, a $3.5\times$ scaled prototype was fabricated and integrated with SMA actuators and an Arduino-based control system. The experimental results demonstrate effective locomotion and steering capabilities, achieving a maximum stroke of approximately 5.4 mm and a steering angle of 24° for the $3.5\times$ scaled prototype, corresponding to an estimated stroke of approximately 1.98 mm (Based on the FEA) at the intended clinical scale. Thermal characterization of the SMA actuators was also conducted to identify suitable operating current ranges for future biomedical deployment. The results demonstrate the feasibility of integrating locomotion and steering within a compact compliant capsule architecture, representing a step toward next-generation capsule endoscopy systems with improved navigation and diagnostic capability. Full article

The behavior of shape memory alloy (SMA) materials is more complex than linear isotropic metals because of their nonlinear thermomechanical coupling. When an SMA material is mechanically stressed or joule-heated, phase transformation happens in the material, and accordingly some material properties dramatically change. In any loading or unloading scenario, the initial state of the material should be known because it significantly affects its behavior. Stress and strain alone are not enough to describe such materials. Temperature and martensitic fraction are also required to simulate SMA materials accurately. This paper presents a MATLAB application, called “SMA Simulator,” that was developed to simulate the nonlinear behavior of SMA wires under mechanical or thermal loads. This tool is very effective in helping users understand the shape memory and pseudoelastic effects in such smart materials, as it allows for plotting the loading path in the 3D stress–strain–temperature space while monitoring the evolution of the martensitic fraction. Any load–unload scenario can be studied, including multiple consecutive partial loading cycles. Since the application is not based on any numerical method that would require extensive meshing, the computational time is minimal, allowing users to perform more simulations and acquire results instantaneously. Full article

This paper focuses on the modeling and design of an adaptive vortex generator (AVG). The device is actuated through shape memory alloy (SMA) elements. The interest of the research community in these devices is due to their ability to improve the performance of the aircraft, directly altering and controlling the boundary layer. Their action consists of energizing the flow, thereby hindering separation. The peculiarity of the presented AVG architecture lies in its compactness and adaptability, which allows for its activation just for some specific phases that are not adequately covered by the conventional. This system can enable load alleviation in the cruise phase when a gust occurs (spoiler modality) and stall prevention in high-lift conditions (vane modality). These two working capabilities can be obtained by mounting the AVGs at different angles of incidence, with respect to the direction of the flow. The present paper is structured as follows. First, the project of RADAR, hosting the activities, is presented with specific focus on the main objectives and on the strategy of maturation of the technologies. Then, attention is paid to the simulations of the aerodynamic field produced by the AVG. These outcomes have driven the next part of the work, focusing on the identification of the architecture of the AVG. A dedicated finite element modeling approach was implemented to address the design task, even in the presence of SMA non-linear elements. Three main operational phases were simulated: (1) the stretching of the springs up to their connection to the architecture (pre-load phase); (2) the elastic recovery of the springs and the achievement of equilibrium with the hosting structure; and (3) the activation of the springs through heating to deflect the AVG. The simulations proved the capability of the system to produce the required deflection/deployment, even under the most severe load conditions. In particular, the simulations highlighted the capability of the system to produce a deflection of the vortex generator of 83.5 deg under the most severe load conditions, against the required value of 80 deg. This result was obtained by also keeping the structural safety factor at a value of four, in line with the wind tunnel facility requirement. Another key outcome of the dynamic analysis was the absence of coupling with vortex shedding, since the system resonance frequencies (135 and 415 Hz) are well outside the vortex-shedding frequency range (500–1400 Hz). Full article

Shape memory alloys (SMAs) are materials that, when used as actuators, can generate deformation and force that can be used to perform mechanical work. This actuation capability is driven by temperature variation, which induces a reversible phase transformation between martensite (at low temperature) and austenite (at high temperature). Owing to their advantages, SMAs are widely applied as actuators and, in certain applications, can be more suitable than other actuation technologies. A thorough understanding of SMA actuator characteristics is therefore essential for their effective implementation in practical applications. This article provides an overview of the most important properties of SMA actuators. In addition, it reviews the application potential of SMA actuators in robotics. Based on the survey of the literature, perspectives for further research and development in this field are also presented. Full article

The growing demand for marine resource development and in-depth exploration of the marine environment has positioned soft biomimetic underwater vehicles (SBUVs) as a research hotspot in the fields of underwater equipment and soft robotics. SBUVs are characterized by bodies made of flexible and extensible materials, integrating the dual advantages of softness and biomimetics. They can achieve muscle-like continuous deformation to efficiently absorb collision energy, while mimicking the propulsion mechanisms of marine organisms—such as fish and jellyfish—through undulating body movements or cavity contraction and relaxation. Such biomimetic propulsion is highly compatible with the flexible actuation of soft materials, enabling excellent environmental adaptability while maintaining favorable propulsion efficiency. Compared with traditional rigid underwater vehicles, SBUVs offer higher degrees of freedom, superior environmental adaptability, enhanced impact resistance and greater motion flexibility. This review systematically summarizes typical actuation methods for SBUVs—including fluid-powered actuation, shape memory alloy actuation, and electroactive polymer actuation—elaborating on their working principles, key technological advances, and representative application cases on SBUVs. These actuation mechanisms each offer distinct advantages. Fluid-powered systems are valued for high power density and precise motion control through direct fluidic force transmission. Shape memory alloys provide high force output and accurate positional recovery via controlled thermal phase changes. Meanwhile, electroactive polymers stand out for their rapid (often millisecond-scale) dynamic response, low hysteresis, and fine, muscle-like deformation under electrical stimuli. Current challenges are also analyzed, such as limited actuation efficiency, material durability issues, and system integration difficulties. Despite these constraints, SBUVs show broad application prospects in marine resource exploration, ecological monitoring, and underwater engineering operations. Future research should prioritize the development of novel materials, coordinated optimization of actuation and control systems, and breakthroughs in core technologies to accelerate the practical implementation and industrialization of SBUVs. Full article

The parametrization of the thermomechanical behavior of shape memory alloys (SMAs) under constant load is described in terms of their functional properties. The deformation–temperature–stress behavior of SMAs from various alloy systems—such as Ni-Ti, Ni-Ti-Cu, and Ni-Mn-Ga—was parametrized using a sigmoidal function. This approach enables the characterization of phase transformation parameters, including transformation temperatures, kinetic parameters, and the relationship between recoverable deformation and applied stress. It is shown that the sigmoid function can serve as a universal descriptor of thermoelastic phase transformations across different alloy systems and transformation types, such as B2–R–B19′–R–B2 (Ni-Ti-Cu), B2–R–B19′–B2 (Ni-Ti), and B2 (L2₁)–B19′ (L2₀)–B2 (L2₁). A correlation coefficient of approximately 0.99 was achieved. The present work extends the theoretical framework of diffuse martensitic transitions in SMAs, for which the sigmoid function has been theoretically derived to describe phase fractions. The article’s novelty lies in shifting from pure mathematical approximation (curve fitting) to physical parametrization of SMA behavior specifically under constant stress (actuator mode). Full article

Shape memory alloy (SMA) actuators possess unique advantages for aerospace applications, including significant deformation, a high work-to-weight ratio, and structural simplicity. However, SMA actuators exhibit inherently strongly saturated and asymmetric hysteresis characteristics, which cause significant hysteresis in the output response. These hysteresis nonlinearities, compounded by process and measurement noise, severely degrade control precision. To overcome these issues, this study proposes a Smoothed Generalized Prandtl–Ishlinskii (SGPI) model to characterize such hysteresis behavior. Based on the SGPI model, we developed a state-space representation for the SMA actuator. Furthermore, an Extended Kalman Filter (EKF) is employed to estimate unmeasurable internal hysteresis states, and these estimates are subsequently utilized as input states for Model Predictive Control (MPC). The simulation results demonstrate that the proposed EKF-MPC approach achieves both rapid dynamic response and high-precision tracking control, effectively compensating for hysteresis nonlinearity while rejecting noise disturbances. Full article

The development of upper-limb prostheses is often hindered by limited dexterity, a restricted workspace, and bulky designs, primarily due to performance limitations in proximal joints like the shoulder and elbow, which contribute to high user abandonment rates. To overcome these challenges, this paper presents a novel, bioinspired, and integrated prosthetic system as an advancement in bionic technology. The design incorporates a shoulder joint based on an asymmetric 3-RRR spherical parallel mechanism (SPM) with actuators embedded within the moving platform, and an elbow joint actuated by low-voltage Shape Memory Alloy (SMA) springs. The inverse kinematics of the shoulder mechanism was established, revealing the existence of up to eight configurations. We employed Multi-Objective Particle Swarm Optimization (MOPSO) to simultaneously maximize workspace coverage, enhance dexterity, and minimize joint torque. The optimized design achieves remarkable performance: (1) 85% coverage of the natural shoulder’s workspace; (2) a maximum von Mises stress of merely 3.4 MPa under a 40 N load, ensuring structural integrity; and (3) a sub-0.2 s response time for the SMA-driven elbow under low-voltage conditions (6 V) at a motion velocity of 6°/s. Both motion simulation and prototype testing validated smooth and anthropomorphic motion trajectories. This work provides a comprehensive framework for developing lightweight, high-performance prosthetic limbs, establishing a solid foundation for next-generation wearable robotics and bionic devices. Future research will focus on the integration of neural interfaces for intuitive control. Full article

Shape Memory Alloy (SMA) actuators offer strong potential for compact, lightweight, silent, and compliant robotic grippers; however, their practical deployment is limited by the challenge of controlling nonlinear and hysteretic thermal dynamics. This paper presents a complete Sim-to-Real control framework for precise temperature regulation of a tendon-driven SMA gripper using Deep Reinforcement Learning (DRL). A novel 12-action discrete control space is introduced, comprising 11 heating levels (0–100% PWM) and one active cooling action, enabling effective management of thermal inertia and environmental disturbances. The DRL agent is trained entirely in a calibrated thermo-mechanical simulation and deployed directly on physical hardware without real-world fine-tuning. Experimental results demonstrate accurate temperature tracking over a wide operating range (35–70 °C), achieving a mean steady-state error of approximately 0.26 °C below 50 °C and 0.41 °C at higher temperatures. Non-contact thermal imaging further confirms spatial temperature uniformity and the reliability of thermistor-based feedback. Finally, grasping experiments validate the practical effectiveness of the proposed controller, enabling reliable manipulation of delicate objects without crushing or slippage. These results demonstrate that the proposed DRL-based Sim-to-Real framework provides a robust and practical solution for high-precision SMA temperature control in soft robotic systems. Full article

This study presents a small-scale hip exoskeleton incorporating bi-directional artificial muscles constructed with springs of Shape Memory Alloy (SMA). The prototype can effectively support hip motion in both extension and flexion, spanning an angular range of $-{20}^{°}$ to ${200}^{°}$. Experiments for thermo-mechanical characterization were executed to assess the performance of the SMA muscles throughout the entire motion range. The outcomes not only confirmed the suitability of the SMA muscles for the designed exoskeleton but also provided valuable insights into their behavior and capabilities. System identification experiments were carried out to establish an accurate transfer function, guiding the tuning of Proportional-Integral-Derivative (PID) controllers for enhanced motion-control effectiveness. The safety of the SMA system was addressed with a focus on preventing overheating. Challenges in accurately measuring the temperature of a thin spring were overcome by utilizing two thermocouples for each SMA springs group. Additionally, conventional SMA temperature measurement methods, such as infrared and resistance-based techniques, are limited by high cost, nonlinearity, and small range. This study presents a model-based temperature estimation algorithm that integrates a heat transfer model, electrical input data, and thermocouple data to enable accurate and real-time SMA temperature estimation without additional sensors, offering a cost-effective and reliable alternative. To evaluate the small hip prototype and its controller capabilities, control experiments were executed for both stepping and sinusoidal trajectories. The exoskeleton successfully tracked the desired trajectories, showing its precision. Moreover, system performance under adaptive control was further investigated, revealing an RMSE of $0.{94}^{°}$ in sinusoidal trajectory experiments, indicating reliable disturbance rejection in the angle measurements. Full article

Knee flexion refers to the relative motion between the tibia and femur including rolling and sliding (rollback motion). Notwithstanding the individual variations in knee motion, conventional wearable knee-assistive devices use hinge joints—resulting in nonnegligible mismatched movements, particularly during deep flexion. Therefore, we proposed a biomimetic knee joint (BKJ) that adapts to individual knee motion. A polycentric BKJ, integrating two gears with different radii, was designed to match the trajectory of the rotational axes of the knee. In this study, we developed a semi-active polycentric BKJ (SA-BKJ) incorporating an adjustable reaction-force mechanism (ARFM). In the ARFM, the combined spring constant can be adjusted using a shape-memory alloy actuator owing to its compact size, lightweight nature, and low energy consumption. In addition, the geared joint of the SA-BKJ (which integrates two gears with different radii) was designed to match the average trajectory of the rotational axes of the knee (of 22 healthy men). Applying the genetic algorithm, the radius of the femur and tibia gears were determined to be 25.5 and 40.0 mm. Misalignments of the designed SA-BKJ were measured in three healthy male participants. The error measurements averaged 20 degrees in the control device and 10 degrees in the optimized device. These results indicated that the optimized gears of the SA-BKJ totally reduced the misalignment. Full article

Background: Shape memory alloy spring actuators offer significant potential for advanced actuation systems in exoskeletons, medical devices, and robotics, but adoption has been limited by slow activation speeds and insufficient design guidelines for achieving rapid response times while maintaining structural integrity. Objective: This study aimed to establish comprehensive design parameters for nickel–titanium spring actuators capable of achieving sub-second activation times through systematic experimental characterization and performance optimization. Methods: Nine different nickel–titanium spring configurations with wire diameters ranging from 0.5 to 0.8 mm and spring indices from 6 to 8 were systematically evaluated using differential scanning calorimetry for thermal characterization, mechanical testing for material properties, high-current electrical activation studies spanning 5–11 A, infrared thermal distribution analysis, and laser displacement sensing for dynamic response measurement. Results: Dynamic testing achieved activation times below 1 s for currents exceeding 5 A, with maximum displacement recoveries reaching 600–800% strain recovery, while springs with intermediate spring index values of 6.5–7.5 provided optimal balance between force output and displacement range, and optimal activation involved moderate current levels of 5–7 A for thin wires and 8–11 A for thick wires. Conclusions: Systematic geometric optimization combined with controlled high-current density activation protocols enables rapid actuation response while maintaining structural integrity, providing essential design parameters for engineering applications requiring fast, reliable actuation cycles. Full article

Hysteresis primarily affects the positioning accuracy of the magnetic shape memory alloy-based actuator (M-SMAA). This paper proposes the use of the nonlinear autoregressive moving average with an exogenous input (NARMAX) model to describe the complex dynamic hysteresis of M-SMAA. First, an improved Prandtl–Ishlinskii operator is proposed as the exogenous variable function for the NARMAX model, using a hyperbolic tangent function as the input to the exogenous variable function, to better capture and represent the multivalued mapping hysteresis in M-SMAA. Then, a long short-term memory neural network is introduced to construct the NARMAX model, further optimizing its performance. Finally, the experimental results verify the effectiveness of the model. Full article

Shape Memory Alloys (SMAs) have unique thermomechanical properties, including superelasticity and the shape memory effect, which has led them to be used in a wide range of applications, from biomedical devices to aerospace and civil engineering structures. These behaviors have been addressed by phenomenological models, which represent them by simply establishing stress–strain and transformation characteristics without accounting for the microstructure. In this review article, the main phenomenological modeling examples are categorized and compared, including the main principles of operation, predictions, and limitations under operating thermomechanical loading conditions. In addition, the growing use of SMAs, especially in actuation, damping, vibration control, and energy harvesting, is explored, and the incorporation of modeling frameworks into optimization activities is discussed. The final part of the review deals with open challenges and future research directions, consisting of the development of models that more accurately predict SMAs under cyclic and/or non-proportional loading, a more robust association with commercial computational tools, and exploring the use of SMAs in new interdisciplinary areas. By bridging modeling approaches to application-based concepts, a platform is provided for the advancement of both the scientific development and practical use of shape memory alloys. Full article