Smart Materials and Structures

Four-dimensional (4D) printing is an advanced manufacturing technology that has rapidly emerged as a transformative tool with the capacity to reshape various research domains and industries. Distinguished by its integration of time as a dimension, 4D printing allows objects to dynamically respond to external stimuli, setting it apart from conventional 3D printing. This roadmap has been devised, by contributions of 44 active researchers in this field from 32 affiliations world-wide, to navigate the swiftly evolving landscape of 4D printing, consolidating recent advancements and making them accessible to experts across diverse fields, ranging from biomedicine to aerospace, textiles to electronics. The roadmap's goal is to empower both experts and enthusiasts, facilitating the exploitation of 4D printing's transformative potential to create intelligent, adaptive objects that are not only feasible but readily attainable. By addressing current and future challenges and proposing advancements in science and technology, it sets the stage for revolutionary progress in numerous industries, positioning 4D printing as a transformative tool for the future.

Energy harvesting technologies have been explored by researchers for more than two decades as an alternative to conventional power sources (e.g. batteries) for small-sized and low-power electronic devices. The limited life-time and necessity for periodic recharging or replacement of batteries has been a consistent issue in portable, remote, and implantable devices. Ambient energy can usually be found in the form of solar energy, thermal energy, and vibration energy. Amongst these energy sources, vibration energy presents a persistent presence in nature and manmade structures. Various materials and transduction mechanisms have the ability to convert vibratory energy to useful electrical energy, such as piezoelectric, electromagnetic, and electrostatic generators. Piezoelectric transducers, with their inherent electromechanical coupling and high power density compared to electromagnetic and electrostatic transducers, have been widely explored to generate power from vibration energy sources. A topical review of piezoelectric energy harvesting methods was carried out and published in this journal by the authors in 2007. Since 2007, countless researchers have introduced novel materials, transduction mechanisms, electrical circuits, and analytical models to improve various aspects of piezoelectric energy harvesting devices. Additionally, many researchers have also reported novel applications of piezoelectric energy harvesting technology in the past decade. While the body of literature in the field of piezoelectric energy harvesting has grown significantly since 2007, this paper presents an update to the authors' previous review paper by summarizing the notable developments in the field of piezoelectric energy harvesting through the past decade.

The current work develops a physics-based model for twisted and coiled artificial muscles (TCAMs) using the extended Cosserat theory of rods. These artificial muscles are lightweight and low-cost, generating a high power-to-weight ratio. They produce tensile forces up to 12 600 times their own weight, closely mimicking the functionality of biological muscles. The contraction of these muscles is driven by the anisotropic volume expansion of their twisted fibers, induced by deformation of the fibers' cross-section. Unlike prior models, this study implements the extended Cosserat theory, which models not only rigid rotations (like standard Cosserat theory) but also planar anisotropic deformation of the TCAMs' cross-section. The static deformation and dynamic motion of TCAMs are formulated herein. The governing equations for the bulk deformation of TCAMs are derived through standard Cosserat rod theory, while a continuum mechanics approach is utilized to model the cross-sectional deformation. The Bernstein polynomial method is applied to discretize the continuous formulations, enabling numerical solutions to the problem. Experimental datasets are used for evaluation of the models.

The advancement of information and energy technologies has spurred an increased demand for low-power and compact electronic devices with across various fields. Developing energy harvesting technologies to capture ambient and sustainable energy offers a promising solution to complement or replace conventional batteries. The piezoelectric technique provides a solution for energy harvesting from different energy sources, and high-frequency operation in piezoelectric energy harvesting offers several advantages. These include increased power output, as more charge is generated per unit of time, which increases the current. Additionally, better alignment with the natural resonance of piezoelectric elements enhances energy conversion efficiency. Considering the growing interest in efficient energy harvesting, a review of recent advancements in piezoelectric energy harvesting under high-frequency excitations and operations is presented in this paper. A brief introduction to the operating modes of piezoelectric energy harvester (PEH) is first introduced to provide a general understanding of energy conversion from the piezoelectric effect. PEHs under high-frequency operations from different energy sources are then reviewed and classified into three categories: wind, vehicle and train, and water flow. Next, novel ideas and structures to facilitate high-frequency operations for PEHs are summarized and discussed in detail. Subsequently, the working mechanisms for PEHs under high-frequency operations are described in detail and classified into three groups: high-speed rotation, frequency up-conversion, and friction-induced vibration mechanisms. Finally, applying advanced piezoelectric materials in novel structures and fostering application-oriented prototype testing are identified as trends for future development.

Structures inspired by the Kresling origami pattern have recently emerged as a foundation for building functional engineering systems with versatile characteristics that target niche applications spanning different technological fields. Their light weight, deployability, modularity, and customizability are a few of the key characteristics that continue to drive their implementation in robotics, aerospace structures, metamaterial and sensor design, switching, actuation, energy harvesting and absorption, and wireless communications, among many other examples. This work aims to perform a systematic review of the literature to assess the potential of the Kresling origami springs as a structural component for engineering design keeping three objectives in mind: (i) facilitating future research by summarizing and categorizing the current literature, (ii) identifying the current shortcomings and voids, and (iii) proposing directions for future research to fill those voids.

The current boom in soft robotics development has spurred extensive research into these flexible, deformable, and adaptive robotic systems. However, the unique characteristics of soft materials, such as non-linearity and hysteresis, present challenges in modeling, calibration, and control, laying the foundation for a compelling exploration based on finite element analysis (FEA), machine learning (ML), and digital twins (DT). Therefore, in this review paper, we present a comprehensive exploration of the evolving field of soft robots, tracing their historical origins and current status. We explore the transformative potential of FEA and ML in the field of soft robotics, covering material selection, structural design, sensing, control, and actuation. In addition, we introduce the concept of DT for soft robots and discuss its technical approaches and integration in remote operation, training, predictive maintenance, and health monitoring. We address the challenges facing the field, map out future directions, and finally conclude the important role that FEA, ML, and DT play in shaping the future of soft robots.

The superelasticity of shape memory alloys (SMA) can be used to provide self-centering and/or energy dissipation characteristics to structures including buildings, bridges, automobiles, and aircrafts. The functional fatigue behavior of SMA is important because it affects the stiffness, strength, strain recovery and energy dissipation of the material. This study investigated the functional fatigue behavior of large diameter Ni–Ti SMA bars under different levels of plastic deformation and different ambient temperatures. Differential scanning calorimetry was used to measure the martensitic transformation temperatures. Cyclic loading with a 1% strain increment was applied to investigate the maximum recovery strain, i.e. the superelastic limit. Low-cycle fatigue loading with different applied peak strains (2%, 3%, 4% and 5%) was performed at different temperatures (−40 °C, −10 °C, 10 °C, 25 °C and 50 °C). The effects of plastic deformation, testing temperature, and number of cycles on the stress-induced martensitic phase transformation, degradation of superelastic properties, and fatigue life were studied. The superelastic properties, such as the changes in the stress–strain curves, elastic modulus, yield stress, damping ratio and recovery strain, were analyzed. It was shown that the functional fatigue resistance (in terms of degradation in the superelastic properties and fatigue life) of Ni–Ti SMA reduced as the applied peak strain increased, particularly when the applied peak strain was higher than the superelastic limit. Additionally, when Ni–Ti SMA was subjected to combined plastic deformation and higher than room temperature, the functional fatigue resistance reduced as the temperature increased.

High energy dissipation materials are crucial for impact protection gear. Additionally, if these materials also have shape memory property, they can offer a better body fit and increase comfort feeling. Herein, we present a novel auxetic composite foam with ultrahigh specific energy dissipation (SED) and shape memory property, which was prepared by directly foaming with low-melting-point alloy (LMPA) in polyurethane (PU) followed by thermal compression process. Due to the synergetic action of LMPA and auxetic PU foam (APU), APU/LMPA foam showed better energy dissipation than pristine PU foam. The compression test showed the energy dissipation and SED of the APU/LMPA foam were 13.4 times and 4.8 times higher than non-APU foam, respectively. Furthermore, the SED improvement of APU/LMPA foam was much higher than other reported auxetic foams. The impact test demonstrated that APU/LMPA foam with 30% thinner thickness could reduce transmitted peak force by 62.1% compared to non-APU foam. Additionally, APU/LMPA foam exhibited shape memory effect due to the phase transition of LMPA, allowing it to adapt to different body shapes through thermal process. With its outstanding energy dissipation and shape memory properties, this composite foam is highly promising for personal safety protection, offering excellent user experience.

Soft actuators can be classified into five categories: tendon-driven actuators, electroactive polymers, shape-memory materials, soft fluidic actuators (SFAs), and hybrid actuators. The characteristics and potential challenges of each class are explained at the beginning of this review. Furthermore, recent advances especially focusing on SFAs are illustrated. There are already some impressive SFA designs to be found in the literature, constituting a fundamental basis for design and inspiration. The goal of this review is to address the latest innovative designs for SFAs and their challenges and improvements with respect to previous generations, and to help researchers to select appropriate materials for their application. We suggest seven influential designs: pneumatic artificial muscle, PneuNet, continuum arm, universal granular gripper, origami soft structure, vacuum-actuated muscle-inspired pneumatic, and hydraulically amplified self-healing electrostatic. The hybrid design of SFAs for improved functionality and shape controllability is also considered. Modeling SFAs, based on previous research, can be classified into three main groups: analytical methods, numerical methods, and model-free methods. We demonstrate the latest advances and potential challenges in each category. Regarding the fact that the performance of soft actuators is dependent on material selection, we then focus on the behaviors and mechanical properties of the various types of silicone that can be found in the SFA literature. For a better comparison of the different constitutive models of silicone materials proposed and tested in the literature, ABAQUS software is here employed to generate the engineering and true strain-stress data from the constitutive models, and compare them with standard uniaxial tensile test data based on ASTM412. Although the figures presented show that in a small range of stress–strain data, most of these models can predict the material model acceptably, few of them predict it accurately for large strain-stress values. Sensor technology integrated into SFAs is also being developed, and has the potential to increase controllability and observability by detecting a wide variety of data such as curvature, tactile contacts, produced force, and pressure values.

The integration of fiber Bragg grating (FBG) with geogrids has led to the development of intelligent geogrids with exceptional reinforcement and monitoring capabilities, making them highly suitable for geotechnical engineering applications such as slopes and roadbeds. This study introduces a fabrication technique for FBG-embedded geogrids, employing 3D printing and UV adhesive encapsulation. Laboratory tensile and out-of-plane compression tests were conducted to evaluate the repeatability, linearity, and strain-sensing performance of the FBG-embedded geogrids, confirming the reliability of the proposed fabrication method. A coupled fiber-adhesive-geogrid analytical model was developed to elucidate the strain transfer mechanism, and a theoretical strain transfer coefficient was derived. The model was validated through finite element analysis simulations and laboratory experiments, with experimental results at the rib center—showing a strain transfer coefficient of 93.88%—deviating by approximately 6% from theoretical predictions. Further parameter analysis revealed that the elastic modulus, height, width of the adhesive layer and the embedding length significantly influence the strain transfer coefficient. Comparisons with geogrids featuring surface-mounted FBGs demonstrated the superior strain transfer efficiency of the proposed FBG-embedded geogrids. As the encapsulation length decreased from 160 mm to 20 mm, the strain transfer advantage of the FBG-embedded geogrid over the FBG-bonded type increased from 0.6% to 14.3%. These findings provide practical insights into optimizing FBG-embedded geogrid parameters for improved strain-sensing performance, offering valuable guidance for their application in engineering scenarios.

This paper presents a double-pendulum energy harvester designed to convert low-frequency environmental vibrations, such as wave-induced motions on unmanned surface vehicles, into usable electrical energy. The key innovation lies in its double-pendulum-spring configuration, which features a serially connected inverted pendulum with a normal pendulum. This unique design effectively broadens the frequency bandwidth for energy harvesting. The harvester was designed, mathematically modeled, constructed, and experimentally tested, demonstrating effective performance in low-frequency and wide-bandwidth characteristics. Experimental results show that the prototype exhibits two distinct resonance peaks at 0.6 Hz and 1.2 Hz, with corresponding maximum average output powers of 0.250 W and 0.404 W, respectively. Compared to single-pendulum harvesters of the same pendulum length, this design offers the advantage of a broader frequency band, enhancing its energy harvesting potential.

To enhance the efficiency of piezoelectric energy harvesting, various interface circuits have been developed, including standard energy harvesting (SEH), synchronized charge extraction (SCE), and both parallel and series synchronized switch harvesting on inductor (P-SSHI and S-SSHI) circuits. However, voltage drops in transistors and diodes prevent the synchronization switch from closing precisely when the output voltage of a piezoelectric energy harvester (PEH) reaches its peak, resulting in a switching delay. The impact of this delay on energy harvesting and storage remains insufficiently understood. This study models and compares the effects of voltage drops in transistors and diodes on energy harvesting and storage in self-powered SCE, P-SSHI, and S-SSHI circuits. Analytical solutions for the voltage variations on energy storage capacitors during each half-cycle are derived, and experimental tests are conducted to validate the theoretical results. A systematic comparison of the energy charging performance is conducted for PEHs under weak, medium, and strong coupling conditions, with a focus on the influence of threshold voltages across transistors and diodes. Results show that switching delays can reduce the energy charged into storage capacitors in systems with self-powered P-SSHI and S-SSHI circuits. The self-powered P-SSHI circuit is most effective for energy charging in PEHs with weak coupling, while the SEH circuit proves most efficient for PEHs with medium or strong coupling.

High energy dissipation materials are crucial for impact protection gear. Additionally, if these materials also have shape memory property, they can offer a better body fit and increase comfort feeling. Herein, we present a novel auxetic composite foam with ultrahigh specific energy dissipation (SED) and shape memory property, which was prepared by directly foaming with low-melting-point alloy (LMPA) in polyurethane (PU) followed by thermal compression process. Due to the synergetic action of LMPA and auxetic PU foam (APU), APU/LMPA foam showed better energy dissipation than pristine PU foam. The compression test showed the energy dissipation and SED of the APU/LMPA foam were 13.4 times and 4.8 times higher than non-APU foam, respectively. Furthermore, the SED improvement of APU/LMPA foam was much higher than other reported auxetic foams. The impact test demonstrated that APU/LMPA foam with 30% thinner thickness could reduce transmitted peak force by 62.1% compared to non-APU foam. Additionally, APU/LMPA foam exhibited shape memory effect due to the phase transition of LMPA, allowing it to adapt to different body shapes through thermal process. With its outstanding energy dissipation and shape memory properties, this composite foam is highly promising for personal safety protection, offering excellent user experience.

Shape memory alloys (SMAs) are unique materials capable of recovering predefined shapes through reversible phase transformations between austenite and martensite phases. This behavior enables SMAs to exhibit the shape memory effect and pseudoelasticity, allowing for the recovery of large strains and the generation of significant forces. These properties make SMAs highly desirable for applications in actuation, sensing, and other engineering domains. Conventional SMA actuator designs, while effective, often face limitations such as slow response times, non-uniform stress distribution, and reduced fatigue life under cyclic loading. Integrating Kirigami-inspired techniques into SMA actuator design addresses these challenges by introducing precise cut patterns that transform 2D SMA materials into complex 3D structures. Kirigami-based SMA structures offer enhanced stroke lengths, improved heat dissipation, and uniform load distribution, reducing stress concentrations and extending the actuator lifespan. This approach enables the creation of versatile and efficient actuators with tailored mechanical properties, overcoming traditional design constraints. This paper presents a constitutive model for Kirigami-based SMA structures, coupling mechanical deformation and thermal response modeling to capture in-plane and out-of-plane deformations. The proposed framework provides a detailed understanding of the unique thermomechanical behavior of Kirigami-inspired SMA actuators, offering insights into their performance under varying operational conditions. The findings highlight the potential of Kirigami-based SMA structures for advancing actuator technologies across a range of applications.

Research into sustainable energy sources has gained significant attention due to global environmental challenges. Vibration energy harvesting (VEH) presents a promising approach for developing self-powered sensors, offering both practical and environmental benefits. This paper reviews recent advancements in VEH with a specific focus on piezoelectric-based methods. It classifies the key techniques in the literature into categories such as multistability (including bistability), internal resonance, optimized designs, and frequency-up conversion. The paper discusses the underlying principles of each technique, provides relevant illustrations, highlights recent studies within each category, and summarizes their main contributions.

Advancements in intelligent materials for the past few decades enabled the development of functional morphing structures and robots operating in fluid environments. Fluid-structure interaction (FSI) problems for functional morphing structures and robots were naturally accentuated. In this paper, the recent advancements in shape-morphing robots and structures in fluid flow across different Reynolds number scales are reviewed and summarized, from microrobots with Reynolds numbers much lower than 1 to deformable aircraft in turbulent flows. To improve the design and functionality of the morphing structures and robots, we discuss modeling methods, experiments, and materials for the morphing structures over a vast range of Reynolds numbers. Understanding FSI in designing morphing structures and robots is emphasized. Following up with several critical future questions to address, the potential applications of artificial intelligence and machine learning (AI/ML) techniques in improving the design of shape-morphing structures and robots are discussed. These shape-morphing structures are expected to significantly enhance sustainable solutions for challenges and explore the unknown of deeper oceans and outer space.

Active (intelligent/smart) materials in engineering solutions are generally combined with other materials, and they are embedded in physical environments. In the current work, these kinds of systems are described as soft–hard active–passive embedded structures (SHAPES). The term emphasizes the interacting materials: In the same way as soft–hard is a spectrum of mechanical compliance, active–passive describes a spectrum of multi-field compliance, i.e. the strength of reaction to a non-mechanical stimulus like a temperature change or an applied electric field. SHAPES can be classified according to the interaction of the active and passive materials as having a Case I (the expansion of the active material is mostly constrained by the passive material), Case II (a combined deformation behavior ensues which is influenced by the active and passive materials) or Case III (the active material deforms freely with only negligible influence of the passive material) behavior. Various application concepts for SHAPES as actuators or for other applications—such as morphing, conductivity switching, sensing, connection-breaking, blocking, and material logic—are presented. Furthermore, the most common active materials that can be part of SHAPES are discussed with respect to their stimulus-responsivity. From these, design recommendations for SHAPES-like applications are derived. Two tables that give a comprehensive overview of relevant literature sources are provided. These tables serve as a snapshot of the currently applied materials and the realized concepts. They can serve as a starting point to add new and emerging materials. The unique focus of the present review is the classification of the interacting materials and how authors utilize the properties of the active and passive materials inside their composites. This allows the identification of gaps/shortcomings in the field and opportunities for new SHAPES designs.

Soft body armor composites are broadly utilized for individual security due to their light weight and flexible nature. However, they are not viable in halting high-velocity impact, particularly against impact at a near distance. Integrating shear thickening fluids (STFs) into these composites is a promising result of upgrading their impact resistance. This review article highlights the progress in improving the impact resistance of soft body armor composites due to the incorporation of STFs. It discusses the parameters affecting energy absorption, shear thickening fluid properties, rheological properties of STFs, mechanisms of energy dissipation during the impact, fabrication techniques of STF-fabric composites, ballistic test techniques, and challenges of ballistic performance evaluation and wearer consolation. This review paper incorporates previous research work for experimental and numerical simulation results. In general, the integration of STFs into soft body armor composites showed noteworthy guarantees in the impact resistance capabilities of soft body armor composites. The most frequent applications of soft body armor composites are security personnel, civilian applications, emergency response teams, private security, body guards, law enforcement, and the military.

Ultrasonic guided waves (UGWs) can travel long distances within the detected structures, which is of great significance for monitoring large complex engineering systems. However, the multimodal and dispersive properties of the specific research object making this promising whole structure monitoring difficult to interpret the signal mathematically and physically. With the development and maturity of deep learning and big data mining technologies, many scholars have noticed artificial intelligence algorithms such as deep learning can provide a new tool in UGWs signal processing, avoiding the mechanism analysis difficulties in the application of UGWs. But the integrity of structural state data sets has become a new pain point in engineering applications under this new approach, and how to apply the knowledge obtained from the existing data set to different but related fields through knowledge transfer in such cases begin to attract the attention of scholars and engineers. Although several systematic and valuable review articles on data-driven UGWs monitoring methods have been published, they only summarized relevant studies from the perspective of data-driven algorithms, ignoring the knowledge transfer process in practical application scenarios, and the intelligent UGWs monitoring methods based on knowledge transfer of incomplete sets are still lacking a comprehensive review. This paper focuses on the UGWs transfer monitoring technology when the training sample is missing, explores the feature correlation between samples in different domains, improves the transfer ability of the structural monitoring model under different conditions, and analyzes the UGWs intelligent monitoring methods for structural state under different sample missing conditions from three aspects: semi-supervised monitoring, multi-task transfer and cross-structure transfer. It is also expected to provide a new method and approach to solve the condition monitoring problems in other complex scenarios.

In recent years, quasi-zero-stiffness (QZS) structures have been utilized in designing galloping piezoelectric energy harvesters (GPEHs) to produce large vibration responses and high output power. However, the quasi-zero-stiffness region is relatively narrow, leading to limited enhancement of QZS-GPEH at large displacement responses. To address this issue, this paper proposes a flat potential-well tuning method to design an improved QZS-GPEH (IQZS-GPEH) by significantly expanding the QZS region. First, the governing equations of the proposed IQZS-GPEH were derived, and a static analysis was conducted to compare the QZS region of the IQZS-GPEH with that of a conventional QZS-GPEH. The results reveal that the QZS property can be extended to accommodate large displacement responses, remarkably expanding the QZS region. Subsequently, the harmonic balance method (HBM) was applied to derive approximate analytical solutions, and numerical simulations were performed to verify and study the dynamics and power performance of the GPEHs. Finally, wind tunnel experiments were conducted to validate the theoretical and numerical findings. The results show that the proposed method effectively enlarges the QZS region, substantially increasing dynamic responses and voltage outputs. Specifically, as the wind speed increased from 3.6 m/s to 5.0 m/s, the power output improvement rose from 23.55% to 55.64%. Therefore, it can be concluded that broadening the QZS region is an effective approach to enhancing the performance of QZS-based galloping energy harvesters.

This study introduces a modular quasi-zero-stiffness (QZS) metamaterial for low-frequency vibration isolation with adaptable load-carrying capacity. The proposed structure integrates a double-curved beam as a negative stiffness (NS) element and two pairs of V-shaped springs as positive stiffness (PS) elements, forming an extendable modular metamaterial. These metamaterials provide scalable and tunable load-adaptive performance through multiple modular configurations. Finite element analysis (FEA) is utilized to optimize the design parameters, ensuring effective and consistent QZS behavior across the modules. A dynamic model, validated using harmonic balance methods, demonstrates the isolation effectiveness under varying loads and excitation amplitudes. By arranging multiple unit modules in series, parallel, or combined configurations, the QZS characteristics scale in a linear and predictable manner, enabling versatile load adaptability and tunability. Quasi-static tests confirm the predicted QZS behavior, while dynamic tests validate the vibration isolation performance. A single unit module attenuates vibrations at 8.6 Hz with a payload of 1420 g, while the modular configuration achieves vibration suppression above 4.2 Hz for payloads ranging from 4320 g to 5680 g, without requiring alterations to the design parameters. These findings underscore the potential of the proposed modular QZS metamaterial for scalable, load-adaptive, and low-frequency vibration isolation in engineering applications.

Sensor accuracy is vital for effective structural health monitoring. However, due to the shear lag effect, the strain transferred from the structure to the sensor experiences some loss, which affects accuracy. This paper offers a review of strain transfer effects for flexible sensors within Structural Health Monitoring (SHM), highlighting the vital role that sensors play in accurately detecting structural strain. A thorough understanding of strain transfer characteristics is crucial for improving measurement accuracy, especially in complex and often harsh conditions typical of practical applications. This review delves into the interactions between substrates and nanomaterials, placing particular emphasis on interfacial mechanics and the influence of various loading conditions, including temperature fluctuations, cyclic loads, boundary conditions, and diverse damage modes, on the strain transfer efficiency. We also discuss the unique properties of flexible sensors, such as their nonlinear responses and increased sensitivity to environmental factors, which further complicate strain measurement. By systematically analyzing these strain-transfer mechanisms, this study aims to establish a robust theoretical framework that supports the development and optimization of flexible sensors for SHM applications. The insights gained from this review are intended to enhance the reliability and accuracy of flexible sensor-based strain measurements, ultimately improving the effectiveness of health monitoring and condition assessment of critical infrastructure.

In this study, we propose a locally resonant seismic metamaterial (SM) inspired by gyroid-typed triply periodic minimal surfaces. This novel SM with a lattice constant of only 2.0 m achieves an ultrawide and ultralow-frequency bandgap of 0-47.05 Hz, covering the frequencies of typical seismic waves completely. Calculations for homogeneous half-space models show that the proposed SM with infinite units can absolutely isolate the surface waves and drive the P- and S-waves away from the surface of the earth. The efficiency of the SM attenuating seismic waves decreases markedly in layered formations with a cover layer of soft soil because the layer interface obstructs the P- and S-waves going away from the surface of the earth. This decrease in attenuation efficiency can be resolved by adjusting the height of the SM to correspond with or exceed the thickness of the cover layer. Furthermore, we conduct a 1/40 scaled-down experiment in the laboratory to validate the effectiveness of the proposed SM for attenuating seismic waves with ultralow frequencies. The ultra-low-frequency bandgap relies on TPMS-type structure characteristics of the SM, whose materials can be selected according to the engineering requirements. This study provides a new way for seismic wave shielding, which can promote the application of SM in practical engineering.

Surfaces science is a complex subject that is exceedingly important to understand, with mastering surface wettability leading to a new realm of applications with wide reaching impacts. Research into superhydrophobic surface is of increasing interest because of the unique abilities that these surfaces possess such as high contact angle (CA), low or high contact angle hysteresis (CAH), and air layer retention, among others. Furthermore, the ability to modify surfaces to control their behaviour could lead to the creation of novel devices and expand opportunities. This review paper explores the intersection between superhydrophobic surfaces and smart materials that enables the development of active superhydrophobic surfaces with switchable wettability. Active superhydrophobic surfaces have shown to be particularly well suited for use across many industries, including environmental, biomedical, and microfluidic, where their diverse range of abilities and fabrication options can be taken advantage of to provide innovative solutions to complex problems. Additionally, we explore natural occurrences of superhydrophobic surfaces, fundamental principles, fabrication techniques, and current advancements, along with their real-world applications.

In recent years, quasi-zero-stiffness (QZS) structures have been utilized in designing galloping piezoelectric energy harvesters (GPEHs) to produce large vibration responses and high output power. However, the quasi-zero-stiffness region is relatively narrow, leading to limited enhancement of QZS-GPEH at large displacement responses. To address this issue, this paper proposes a flat potential-well tuning method to design an improved QZS-GPEH (IQZS-GPEH) by significantly expanding the QZS region. First, the governing equations of the proposed IQZS-GPEH were derived, and a static analysis was conducted to compare the QZS region of the IQZS-GPEH with that of a conventional QZS-GPEH. The results reveal that the QZS property can be extended to accommodate large displacement responses, remarkably expanding the QZS region. Subsequently, the harmonic balance method (HBM) was applied to derive approximate analytical solutions, and numerical simulations were performed to verify and study the dynamics and power performance of the GPEHs. Finally, wind tunnel experiments were conducted to validate the theoretical and numerical findings. The results show that the proposed method effectively enlarges the QZS region, substantially increasing dynamic responses and voltage outputs. Specifically, as the wind speed increased from 3.6 m/s to 5.0 m/s, the power output improvement rose from 23.55% to 55.64%. Therefore, it can be concluded that broadening the QZS region is an effective approach to enhancing the performance of QZS-based galloping energy harvesters.

Surfaces science is a complex subject that is exceedingly important to understand, with mastering surface wettability leading to a new realm of applications with wide reaching impacts. Research into superhydrophobic surface is of increasing interest because of the unique abilities that these surfaces possess such as high contact angle (CA), low or high contact angle hysteresis (CAH), and air layer retention, among others. Furthermore, the ability to modify surfaces to control their behaviour could lead to the creation of novel devices and expand opportunities. This review paper explores the intersection between superhydrophobic surfaces and smart materials that enables the development of active superhydrophobic surfaces with switchable wettability. Active superhydrophobic surfaces have shown to be particularly well suited for use across many industries, including environmental, biomedical, and microfluidic, where their diverse range of abilities and fabrication options can be taken advantage of to provide innovative solutions to complex problems. Additionally, we explore natural occurrences of superhydrophobic surfaces, fundamental principles, fabrication techniques, and current advancements, along with their real-world applications.

In response to growing innovation demands in aviation, open-fan propulsion systems have gained renewed attention owing to their high propulsion efficiency. However, these systems introduce substantial low-frequency acoustic excitation on the aircraft fuselage, dominated by the fundamental blade pass frequency, which poses challenges for managing cabin noise and structural vibrations. This study investigates the integration of vibroacoustic metamaterials and ferroelectrets as a synergistic approach for vibration mitigation and energy harvesting in aircraft fuselages. The proposed vibroacoustic metamaterial demonstrates a vibration attenuation of up to −21.6 dB at the fundamental blade pass frequency of 300 Hz, accompanied by a maximum reduction of −18.3 dB in radiated sound power into the cabin. Electromechanical performance evaluation indicates that this approach enables broadband energy harvesting with a power conversion efficiency of up to 2.85 %, providing sufficient energy to sustain low-power sensor systems. This combination of novel technologies offers a promising pathway for enhanced noise control and self-powered sensing in next-generation aircraft and thin-walled structures in lightweight design.

The Ni49+xMn32-2xGa19+x (x = 0; 2) Heusler ferromagnetic shape memory alloys were prepared using spark plasma sintering using raw flake-type powders obtained by soft grinding melt-spun ribbons. Samples were characterized using X-ray diffraction, electron microscopy, thermal analysis, and bending tests. Although the properties of ribbons and corresponding powders show similar properties' tendencies, they are opposite in the bulk sintered alloys when compared with precursor powders. Namely, Ni49Mn32Ga19 bulk shows a higher enthalpy (5.8 J/g), an increased martensitic transformation temperature (by 9 K), and a reduced hysteresis span (5 K). Conversely, for the Ni51Mn28Ga21 sintered sample, a lower enthalpy (2 J/g), a significant decrease (by 40 K) in the martensitic transformation starting temperature, and a broadening of the hysteresis range (26 K) were observed. This difference is analyzed versus specific features of the microstructure. Moreover, the activation energy and the pre-exponential factor of the martensitic transformation, extracted through kinetic analysis within two non-isothermal models, Kissinger and Friedman, complement and sustain these findings. Fractography details of the sintered samples are discussed in relation to the stress-strain curves from the bending tests. The Ni49Mn32Ga19 bulk sample exhibits a higher bending strength (260 MPa) and a lower strain (0.55 %) than the Ni51Mn28Ga21 sample (177 MPa and 0.61 %). The observed dependence of functional characteristics on preparation enables the possibility of property control required for various applications and suggests that the proposed route is promising in this regard for further investigations.

High energy dissipation materials are crucial for impact protection gear. Additionally, if these materials also have shape memory property, they can offer a better body fit and increase comfort feeling. Herein, we present a novel auxetic composite foam with ultrahigh specific energy dissipation (SED) and shape memory property, which was prepared by directly foaming with low-melting-point alloy (LMPA) in polyurethane (PU) followed by thermal compression process. Due to the synergetic action of LMPA and auxetic PU foam (APU), APU/LMPA foam showed better energy dissipation than pristine PU foam. The compression test showed the energy dissipation and SED of the APU/LMPA foam were 13.4 times and 4.8 times higher than non-APU foam, respectively. Furthermore, the SED improvement of APU/LMPA foam was much higher than other reported auxetic foams. The impact test demonstrated that APU/LMPA foam with 30% thinner thickness could reduce transmitted peak force by 62.1% compared to non-APU foam. Additionally, APU/LMPA foam exhibited shape memory effect due to the phase transition of LMPA, allowing it to adapt to different body shapes through thermal process. With its outstanding energy dissipation and shape memory properties, this composite foam is highly promising for personal safety protection, offering excellent user experience.

Shape memory alloys (SMAs) are unique materials capable of recovering predefined shapes through reversible phase transformations between austenite and martensite phases. This behavior enables SMAs to exhibit the shape memory effect and pseudoelasticity, allowing for the recovery of large strains and the generation of significant forces. These properties make SMAs highly desirable for applications in actuation, sensing, and other engineering domains. Conventional SMA actuator designs, while effective, often face limitations such as slow response times, non-uniform stress distribution, and reduced fatigue life under cyclic loading. Integrating Kirigami-inspired techniques into SMA actuator design addresses these challenges by introducing precise cut patterns that transform 2D SMA materials into complex 3D structures. Kirigami-based SMA structures offer enhanced stroke lengths, improved heat dissipation, and uniform load distribution, reducing stress concentrations and extending the actuator lifespan. This approach enables the creation of versatile and efficient actuators with tailored mechanical properties, overcoming traditional design constraints. This paper presents a constitutive model for Kirigami-based SMA structures, coupling mechanical deformation and thermal response modeling to capture in-plane and out-of-plane deformations. The proposed framework provides a detailed understanding of the unique thermomechanical behavior of Kirigami-inspired SMA actuators, offering insights into their performance under varying operational conditions. The findings highlight the potential of Kirigami-based SMA structures for advancing actuator technologies across a range of applications.

In-plane thin dielectric elastomer actuators (DEAs) represent a promising solution for miniaturised soft robots capable of navigating confined spaces. However, most existing in-plane DEAs are either fabricated using off-the-shelf materials or rely on membranes attached to rigid frames, which limit their actuation performance and pose challenges for integration into locomotion-based soft robots. This work introduces a novel in-plane DEA-based thin soft-rigid hybrid robot for fast movement. The innovative design features a multi-layer silicone-based elastomer tensioned by an in-plane elastic PETG frame. A detailed spin coating fabrication method is presented for producing multilayer silicone-based in-plane DEAs. The robot demonstrated effective crawling on flat surfaces and resonance-driven high-speed locomotion at 53 Hz, achieving a peak velocity of approximately 12.3 mm/s which is 34.2% of its body length per second and 224% of body thickness per second. This study highlights the potential of DEAs for advancing miniaturised soft robotics, especially in applications that demand lightweight, flexible, and thin profile actuators.

Magnetic shape memory polymers (MSMPs) represent a new family of smart materials that unify the tunable mechanical properties typical for shape memory polymers (SMPs) with remote actuation abilities utilizing magnetic fields. First developed in the late 20th century, these MSMPs leverage recent developments in polymer technology and material science for enhanced functionality, placing these materials as key components in several applications, from biomedical devices to soft robotics and smart textiles. This focused review aims to comprehensively summarize the fundamental mechanisms, constituents, and principal applications of MSMPs. Furthermore, non-contact shape recovery methods such as magnetic induction heating or magneto-mechanical forces are also realized by integrating the particles (e.g., iron oxide, cobalt ferrite) with the polymer matrix. The authors of this paper review methods to fabricate uniform particle dispersion and how the selection of polymer can lead to changes in thermal and mechanical properties due to the incorporation of particles into them; they also comment on maintaining a balance between efficiency, durability, and scalability against optimizing. Emphasis is placed on the review of multiple applications of MSMPs in areas like biomedicine, soft robotics, and self-healing materials that require precise manipulation. This review provides a detailed summary of the current constraints, such as particle aggregation, long-term stability, and production costs, while also suggesting key areas that could improve the effectiveness and utility of MSMPs. This analysis aims to describe the current landscape in MSMP research, its technological potential, and areas that require further development.

In the pursuit of solving the energy storage issues of leadless pacemakers, this study presents a piezoelectric energy harvester for self-powering. The mismatch in natural frequencies between the cardiac cycles and the piezoelectric structure affects energy generation. In this research, a groundbreaking hexa-fold piezoelectric energy harvester (HF-PEH) with contact impacts was proposed to generate high energy density from cardiac cycles. The HF-PEH was manufactured and tested in vivo inside a living pig's heart. Subsequently, we subjected this HF-PEH prototype to laboratory cardiac acceleration for over 35 million cardiac cycles to investigate its long-term performance. Post-test material analysis using SEM and X-ray energy-dispersive spectroscopy (EDS) was conducted to investigate the material structure. The HF-PEH generated maximum voltage, current, and power of 1.4 V, 458.5 µA, and 367.2 µW at in-vivo animal trial with 71 beats per minute, which are the same or higher than the values a leadless pacemaker paces into the body. Post-test material analyses showed that the piezoelectric ceramic remained intact while the electrode condition changed. A verified finite element model was used to study the long-term electrode layer erosion condition with respect to the electric displacement field. Since the electrode erosion is limited to the contact-based impact region, limited power degradation in long-term performance was observed. This study also highlights the roles of electrode materials and presents potential protective methods and materials to mitigate electrode performance degradation. Our findings pave the way for practical energy harvesting applications for leadless pacemakers and underscore the need for advanced piezoelectric coatings in contact-based energy harvesting systems.

Dielectric Elastomer Actuators (DEAs) are a recent type of smart materials that show impressive performances as soft actuators, making them a promising technology for the development of implantable artificial muscles and soft robotic devices. Notably, they are explored as implants for the restoration of facial movements post paralysis. However, implementing DEAs that mimic natural muscles has been proven difficult, as DEAs provide in-plane expansion when actuated, while natural muscles contract upon stimulation. Multiple solutions can be found in literature, namely stack DEAs and fiber-reinforced DEAs. The fibers used for DEAs to achieve contractile motion rely on a fishnet design, where the angle between the fibers, the spacing, mechanical properties as well as the fiber dimensions can be set by establishing a fiber analytical model. Contraction has only been achieved with
DEAs based on acrylic elastomer and pre-stretched with rigid frames, thus making them unsuitable as soft implants. This work introduces the first silicone-based, non-pre-stretched DEAs presenting in-plane contractile behavior by embedding such soft structured fiber sheets in the actuators. Fiber-reinforced DEAs were shown to achieve modest contractile strains, particularly with optimal fiber angles between 55° and 65°, enhancing their ability to mimic muscle-like behavior. A peak occurs at approximately 60°, where the maximum contraction of -0.6% was achieved, resulting in a 3 % error from the model. The low contractile strains of silicone-based DEAs indicate that further optimization is needed for real-world applications