Shape memory alloy (SMA)-polymer composites offer promising opportunities for aerodynamic morphing structures in automotive applications, but face significant challenges related to adhesion at the SMA-polymer interface, thermomechanical stresses during activation, and delamination under repeated actuation cycles. Predicting the mechanical response of SMAs under complex fluid-structure interaction (FSI) coupling is also complex, lacking experimental validation in the literature. This research addresses these issues by developing a robust multi-material design and fully-coupled FSI modeling approach within COMSOL Multiphysics. Both numerical modeling and experimental tests are employed, with comprehensive multiphysics FSI simulations incorporating thermomechanical SMA constitutive models to predict structural-aerodynamic force interactions. Model validity is established through wind tunnel tests on a thermally activated SMA-polymer composite plate subjected to fluid flows up to 125 km/h to assess aerodynamic influence on deformation. Simulation and experimental results show a very good agreement, with peak deflection discrepancies within 5%. An increased airflow velocity significantly reduces the peak plate deflection by up to 35% at the maximum tested velocity. Furthermore, the FSI model effectively captures the stress distribution within SMA wires, crucial for evaluating structural integrity. This investigation successfully validates the FSI modeling approach for SMA-driven composites, providing insights into their structural performance under aerodynamic loads to optimize the design of SMA-based morphing structures and to guide future research enhancing their durability and functionality.

Robotic technologies for upper-limb rehabilitation have emerged to address the increasing demand for therapy associated with aging populations and post-stroke recovery. Despite their technological maturity, significant barriers to clinical translation continue to limit widespread adoption. This study aims to systematically analyze existing robotic architectures and identify strategic pathways toward evidence-based implementation. A systematic review was conducted following PRISMA guidelines. A structured search of the Scopus database yielded 215 records. After applying rigorous inclusion criteria focused on peer-reviewed engineering studies, 35 devices developed between 2003 and 2024 were selected for analysis. Devices were compared across eight parameters: structural typology, actuation modality, kinematic complexity, system mass, assisted movements, therapeutic function, validation status, and user interface characteristics. Temporal analysis indicated a marked increase in development after 2018, accounting for 58.3

Shape memory alloy (SMA) spring-based actuators are promising for wearable robotics, offering over 50% contraction, but are limited by slow thermal response, electrical safety risks, and unreliable mechanical connections. These deficiencies hinder their widespread adoption in human-interactive applications where safety and performance are critical. This work introduces a novel modular SMA spring actuator architecture to address these limitations. The actuator integrates borosilicate glass fiber sheaths for electrical and thermal isolation, and precision electrical discharge machining-fabricated aluminum terminals for reliable mechanical coupling. A comprehensive theoretical framework, based on the validated static two-state model, was used for systematic spring dimensioning. The proposed architecture demonstrated complete electrical isolation between springs, enabling flexible series-parallel configurations. The actuator consistently achieved approximately 50% contraction recovery under loads of 38 N up to 66 N, with maximum displacement ranging from over 50 mm down to 35 mm. Cyclic actuation experiments under external loads up to 45 N indicate a stable displacement recovery of 40-42 mm and a stable temperature activation range of 68 degrees C-70 degrees C is reached in less than 100 activation cycles with no functional degradation in terms of actuation stroke (Delta L). This research presents a significant advancement in SMA actuator technology by simultaneously improving thermal safety, electrical isolation, and mechanical reliability. Furthermore, the actuator's performance and safety were validated at the application level through a case study involving a wearable device for shoulder abduction assistance, demonstrating effective muscular load compensation (confirmed by EMG analysis) and safe thermal operation. These findings pave the way for the development of safer and more efficient SMA-actuated systems, with potential applications in soft robotics, wearable exoskeletons, and human-robot interaction.

This study introduces a novel multi-physics one-dimensional simulation framework for shape memory alloy (SMA) wire actuators, addressing their complex electro-thermo-mechanical coupling and hysteretic behavior. By integrating a constitutive model based on Brinson's formulation with a Finite State Machine (FSM) methodology, the framework captures the path-dependent phase transformations inherent to SMAs under different loading scenarios. The FSM approach simplifies system representation and enhances scalability, enabling efficient realtime simulations and control strategies. Experimental validations were carried out using NiTi SMA wires under various thermo-mechanical loading conditions, with results highlighting the ability of the model to predict stress-strain-temperature responses and hysteresis effects even under partial transformation cycling. The proposed FSM-based formulation demonstrates high accuracy across varying configurations and loading paths, establishing it as a viable tool for SMA actuators thermomechanical performance prediction and control system integration.

Shape memory alloys (SMAs) with shape recovery capabilities have been investigated recently at the European Organization for Nuclear Research (CERN) to develop ring-shaped pipe couplers for vacuum applications. SMA couplers exploit the One-Way and Two-Way Shape Memory Effect (OW- and TW-SME) to mount/dismount vacuum pipe, by temperature variations. A phenomenological analytical model based on simplified elastic-plastic axisymmetric theory has been developed and implemented in a commercial software to simulate biaxial constrained recovery mechanisms in thick-walled SMA rings with rectangular cross section. The model is particularly useful to predict the stress field in the SMA coupler as well as the contact pressure developed at the SMA ring/pipe interface during thermal mounting/dismounting operations, knowing their initial geometry and material properties. The predictions of the analytical model have been compared with experimental data and Finite Element (FE) simulations based on a user-defined material routine.

Shape Memory Alloy (SMA) actuators are pivotal in modern engineering due to their unique thermomechanical properties, but their inherent non-linearities, hysteresis, and temperature sensitivity pose significant control challenges. This systematic review evaluates artificial intelligence (AI)-based control methodologies to address these limitations, analyzing their efficacy in enhancing precision, adaptability, and reliability for SMA and Magnetic SMA (MSMA) systems. A PRISMA-guided literature review (2003–2025) identified 24 studies, which were categorized by control architectures (hybrid AI-linear, pure AI, adaptive, and model predictive control) and evaluated through quantitative metrics, including Root Mean Square Error (RMSE%) and a weighted scoring system for experimental rigor. Results revealed hybrid AI-linear controllers as the dominant approach (36%), with online-trained neural networks achieving superior accuracy (+2.4%) over offline methods. Feedforward neural networks outperformed recurrent architectures (+3.1%), while Model Predictive Control (MPC) excelled for SMA actuators (+5.8% accuracy) but underperformed for MSMAs (−7.7%). Sensorless strategies proved advantageous for MSMAs (+5.0%), leveraging intrinsic material properties like electrical resistance for state estimation. The analysis underscores AI’s capacity to mitigate hysteresis and non-linear dynamics, though material-specific optimization is critical: SMA systems favor dynamic control and MPC, whereas MSMAs benefit from sensorless AI and pure neural networks. Challenges persist in computational demands for online training and reinforcement learning’s exploration–exploitation trade-offs. Future research should prioritize adaptive algorithms for fatigue compensation, lightweight AI models for embedded deployment, and standardized benchmarking to bridge material-specific performance gaps. This synthesis establishes AI as a transformative paradigm for SMA actuation, enabling precise control in aerospace, biomedical, and soft robotics applications.

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.

Shape Memory Alloys (SMAs) are a popular class of actuators widely used in complex soft robotics applications due to their shape memory effect, high recoverable strain, and stress. However, most existing actuation models frequently fail to accurately capture hysteresis and dynamic loading behavior while remaining computationally efficient. Moreover, current control strategies often lack adaptability, robustness, and the ability to generalize to varying system dynamics. This paper presents a robust adaptive closed-loop controller for electro-thermally actuated Ni–Ti SMAs, developed based on a Finite State Machine framework to address these challenges. The proposed controller is designed to compensate for disturbances and uncertainties in the SMA behavior. Experimental validation and statistical analysis have demonstrated the effectiveness of the $${\mathcal {L}}_{1}$$ L 1 adaptive controller across various SMA configurations, enabling precise strain and stress target tracking. Finally, the controller is deployed to a case study involving a Ni–Ti SMA-powered assistive robotic device, where it successfully manages position tracking with enhanced performance.

Shape memory alloy (SMA) actuated composites enable real-time geometry modification for enhanced automotive aerodynamic performance. However, integrating SMAs into polymer matrices presents significant challenges in thermomechanical coupling and interface reliability under cyclic loading conditions. This study investigates SMA-polymer active composites for vehicle underbody shield applications through integrated experimental-computational methods. The approach combines multiphysics finite element modeling with precision manufacturing protocols, incorporating SMA-based actuators into a hybrid PC/ABS-carbon fiber reinforced polymer system. Multiple configurations with varying actuator densities and composite layer architectures (2-3 plies) were systematically characterized. The optimized configuration achieves 30 mm deflection at 135 degrees C with peak stresses below 435 MPa, demonstrating a displacement-to-length ratio of 0.4. The validated multiphysics framework predicts system behavior within 5% of experimental measurements. A scalable three-phase manufacturing protocol (carbon fiber reinforced polymer lamination, component assembly, SMA integration) enables consistent production of meter-scale adaptive structures while maintaining precise geometric tolerances. This research establishes new performance benchmarks for morphing automotive components through validated design methodologies. Future development should focus on thermal management optimization for enhanced durability under varied environmental conditions.

Practical exercises are vital in STEM education, reinforcing theoretical knowledge through hands-on activities. Access to labs is crucial from primary schools to universities, even in crowded classrooms or during movement restrictions like pandemics. To meet these challenges, a research team from the Universities of Naples Federico II, Sannio, and Calabria proposes a network of labs enabling remote experiments via extended reality. Students or workers can perform real-device experiments from home at any time, ensuring access to critical training despite physical constraints. Each experiment is unique to an individual or group, preserving authenticity and quality. This paper presents the development of an automated measurement system designed to simultaneously measure and correlate the thermal, electrical, and mechanical properties of Nichel Titanium Naval Ordinance Laboratory (NiTiNol), a Shape Memory Alloy (SMA) widely used in biomedical applications. The importance of this didactical experience is highlighted by the increasing implementation of NiTiNol-based actuators in biomedical applications. In the immersive experience guaranteed by the propsal, the students will be able to acquire a comprehensive understanding of the NiTiNol complex thermo-electro-mechanical behavior.

This study presents an experimental investigation of a novel shape memory alloy (SMA)-based active composite designed for aerodynamic applications. The research addresses critical interface challenges in SMA-polymer composites through an innovative multi-material architecture incorporating a high-temperature silicone matrix and PC/ABS structural layer. Systematic wind tunnel experiments characterized the shape morphing capabilities under various aerodynamic loading conditions, with flow velocities ranging from 0 to 125 km/h. The experimental results demonstrate robust morphing performance, achieving a maximum deflection of 52 mm under static conditions and maintaining 60% of this capability (31.6 mm) at maximum flow velocity. The composite’s deformation profiles exhibit nonlinear behavior with increasing aerodynamic loads while preserving consistent actuation characteristics across all test conditions. This stability is attributed to the strategic integration of compliant and structural layers, effectively addressing previously reported interface limitations. The findings validate the effectiveness of the proposed material architecture for active aerodynamic components, particularly in automotive applications requiring reliable performance under varied operating conditions. The experimental characterization provides valuable insights for future development of adaptive structures, establishing a foundation for optimizing geometric and material parameters in SMA-based active composites.

Shape memory alloys (SMAs) are a unique class of smart materials capable of recovering significant deformations through temperature variations, making them attractive for adaptive structures and morphing applications. However, integrating SMAs into polymer composites poses significant challenges, such as interfacial delamination and matrix overheating during thermal activation, in addition predicting the stress acting on the SMA during the actuation is pivotal. Addressing these issues is crucial for realizing the full potential of SMA-based active composites in aerospace, automotive, and renewable energy sectors. This study presents a novel multi-material design strategy for SMA-polymer active composites, featuring a rigid PC/ABS layer for mechanical integrity, a soft high-temperature silicone coating for encapsulating SMA wires, and aluminum terminals for wire crimping. A comprehensive multiphysics FEM model was developed to accurately capture the coupled thermo-mechanical response. Extensive experimental characterization and validation were conducted, followed by systematic parametric studies to investigate the effects of critical design parameters on key performance metrics. The developed prototype exhibited remarkable shape morphing capabilities, with a maximum tip deflection of 68 mm (deflection-to-length ratio of 0.4). Excellent agreement between experiments and simulations was achieved, with a maximum error of 1.7 % in tip deflection, validating the accuracy of the multiphysics model. Parametric analyses quantified the trade-offs between geometric parameters, revealing their influence on activation temperature, deflection, SMA wire stress, and fatigue life. Optimal configurations enabling low activation temperatures (<150 °C), low stress levels (<400 MPa), and high predicted fatigue life (>50,000 cycles) were identified. The multi-material design approach effectively addressed common issues in SMA-polymer composites, enabling reliable actuation cycles without damage accumulation. The validated multiphysics model and parametric insights provide a comprehensive framework for optimizing the design and performance of SMA-polymer active composites, paving the way for their widespread adoption in shape morphing applications. Potential implications include the development of adaptive aerodynamic surfaces, deployable structures, and energy-efficient systems across various industries.

Shape memory alloys (SMAs) enable unique actuation capabilities through reversible phase transformations when heated, making them promising for adaptive structures. Integrating SMAs into composites creates smart systems with controllable shape morphing functionality. This paper reviews recent research on SMA-driven shape morphing composites. SMAs exhibit pseudoelasticity and the shape memory effect due to austenite-martensite phase changes, enabling high recoverable strains and tailored shape recovery. These properties have motivated growing interest in SMA-based active composites for applications like aerospace, automotive, soft robotics, and biomedicine. The paper categorizes SMA integration strategies into fully embedded versus hybrid layouts. Key design trade-offs are analyzed regarding achievable deformation modes, manufacturability, activation uniformity, and interfacing. Proper SMA positioning and insulation are crucial to prevent matrix overheating and enable unconstrained actuation. Enhancing SMA-matrix adhesion and balancing component thermomechanical properties are also critical. The unique capabilities of SMA hybrid composites are highlighted through case studies across diverse fields. Ongoing challenges around actuation speeds, fatigue life, and interfacial durability motivate new material development and manufacturing optimizations. Overall, SMA-enabled active composites present exciting potential for reversible, programmable shape morphing. This review synthesizes recent progress and provides insights to guide future research and innovation.

Within the powder bed fusion electron beam (PBF-EB) category, due to the high cost of material feedstock, the unused powder can be reused in subsequent production cycles, thereby reducing the costs associated with powder production. However, since the impact of recycling processes on the metallurgical and mechanical properties has not been fully investigated in the scientific literature, this study aimed to analyze fatigue crack growth propagation by examining three types of compact tension (CT) specimens. The specimens were manufactured using the Electron Beam Melting (EBM) process with three different batches of Ti-6Al-4V powder particles: virgin, recycled five times, and recycled more than 100 times. The results reveal that the oxygen content increases with each cycle, indicating the potential effects of recycling. Furthermore, from a mechanical testing perspective, the obtained results did not indicate any significant effects of powder reuse on the investigated CT samples, as the obtained curves exhibited a high degree of similarity. This can be attributed to the presence of numerous internal defects, such as porosity and Lack of Fusion, and thus, it is believed that the effect of powder recycling has been overshadowed by the influence of these defects.

Background Comprehensive datasets quantifying the coupled thermo-mechanical and electrical properties of shape memory alloys (SMAs) are lacking, as are standardized techniques for robust characterization. This hampers accurate modeling and design of SMA-based components. Objective: This work develops an automated experimental system to enable simultaneous measurement of stress-strain-temperature behavior and electrical resistivity evolution in NiTi SMA wires under controlled stress conditions. Methods: Customized test frames apply precise mechanical stresses while allowing for in situ electrical measurements and infrared imaging during complete thermal cycling protocols. Specialized instrumentation including a Keithley 2002 multimeter, Agilent E3631A programmable power supply, and FLIR A615 thermal camera are integrated with LabVIEW-based software routines for complete automation of the characterization process. Rigorous metrology principles are implemented throughout the measurement procedure to improve accuracy, repeatability, and consistency compared to prior manual techniques. Results: Extensive datasets are generated which reveal pronounced stress-dependencies in key SMA material parameters including transformation temperatures, recoverable strain, and electrical resistivity. A 3D regression model describes the comprehensive relationship between resistivity, temperature, and applied stress across the entire characterization domain. Conclusions: The automated measurement framework and methodology establishes a foundation for high-fidelity, reliable acquisition of coupled SMA property data. This will enable more accurate modeling and design of components and systems incorporating SMA actuation or sensing functions.

Green energy transition has supposed to give a huge boost to the electric vehicle rechargeable battery market. This has generated a compelling demand for raw materials, such as cobalt and nickel, which are key common constituents in lithium-ion batteries (LIBs). However, their existing mining protocols and the concentrated localization of such ores have made cobalt and nickel mineral conundrums, and their supplies experience shortages, which threaten to slow the progress of the renewable energy transition. Aiming to contribute to the sustainable recycling of these valuable metals from LIBs and wastewater, in this work, we explore the use of four mixed matrix membranes (MMMs) embedding different metal-organic frameworks (MOFs), i.e., MIL-53(Al), MIL-53(Fe), MIL-101(Fe), and {(SrCu6II)-Cu-II[(S,S)-serimox](3)(OH)(2)(H2O)}39H(2)O (SrCu(6)Ser) in polyether sulfone (PES), for the recovery of cobalt(II) and nickel(II) metal cations from mixed cobalt-nickel aqueous solutions containing common interfering ions. Whereas the neat PES membrane slightly contributes to the adsorption of metal ions, showing reduced removal efficiency values of 10.2 and 9.5% for Ni(II) and Co(II), respectively, the inclusion of MOFs in the polymeric matrix substantially improves the adsorption performances. The four MOF@PES MMMs efficiently remove these metals from water, with MIL-53(Al)@PES being the one that presents better performance, with a removal efficiency up to 95% of Ni(II) and Co(II). Remarkably, SrCu(6)Ser@PES exhibits outstanding selectivity toward cobalt(II) cations compared to of nickel(II) ones, with removal efficiencies of 63.7 and 15.1% for Co(II) and Ni(II), respectively. Overall, the remarkable efficiencies, versatility, high environmental robustness, and cost-effective synthesis shown by this family of MOF@PES MMMs situate them among the best adsorbents for the extraction of this kind of contaminants.

The internal structure of two Messinian halite crystals belonging to the white and transparent facies examined in order to investigate how the presence, amount and distribution of fluid inclusions (FIs) and voids, could affect petrophysical properties of halite crystals. In this investigation standard petrographic techniques and geomechanical tests were used in conjunctions with synchrotron radiation X-ray and computed microtomography. The computed microtomography allows a high-resolution 3D reconstruction of the inner part of the crystals and the identification of three phases: solid (halite), liquid (FIs), and air (voids). The different distribution and amount of these components produce an important variability in petrophysical properties in both samples, in terms of porosity, density Young’s modulus and mechanical strength. These data differ from those reported in the literature in which halite is mainly considered as a homogenous material with almost constant values of petrophysical parameters.This innovative approach could open new scenario on the halite investigation mainly for geotechnical studies applied to mining, construction and civil engineering, management of mineral resources, groundwater, geological and environmental risks, underground space for urban and industrial use.

The choice of the proper restorative material is essential for the long-term success of implant-supported rehabilitations. This study aimed to analyze and compare the mechanical properties of four different types of commercial abutment materials for implant-supported restorations. These materials included: lithium disilicate (A), translucent zirconia (B), fiber-reinforced polymethyl methacrylate (PMMA) (C), and ceramic-reinforced polyether ether ketone (PEEK) (D). Tests were carried out under combined bending–compression conditions, which involved applying a compressive force tilted with respect to the abutment axis. Static and fatigue tests were performed on two different geometries for each material, and the results were analyzed according to ISO standard 14801:2016. Monotonic loads were applied to measure static strength, whereas alternating loads with a frequency of 10 Hz and a runout of 5 × 106 cycles were applied for fatigue life estimation, corresponding to five years of clinical service. Fatigue tests were carried out with a load ratio of 0.1 and at least four load levels for each material, and the peak value of the load levels was reduced accordingly in subsequent levels. The results showed that the static and fatigue strengths of Type A and Type B materials were better than those of Type C and Type D. Moreover, the fiber-reinforced polymer material, Type C, showed marked material–geometry coupling. The study revealed that the final properties of the restoration depended on manufacturing techniques and the operator’s experience. The findings of this study can be used to inform clinicians’ choice of restorative materials for implant-supported rehabilitation, considering factors such as esthetics, mechanical properties, and cost.

Nowadays, active composite materials with shape-morphing capabilities are becoming increasingly used, this is mainly due their efficiency and weight reduction. Smart material like Shape Memory Alloys (SMAs) can be used for these application as embedded actuators. Indeed, from aerospace to automotive field these components can increase the aerodynamic performance by continuous morphable surface and are able to simplify the models by reducing the quantity of movable parts. A design solution for an SMA-polymer composite plate with morphing capabilities was developed and manufactured by 3D printing processes. Furthermore, a simple and effective analytical model was developed to predict the shape morphing properties of the active composite. The accuracy of the model was verified through comparison with experimental data obtained from the developed prototypes.