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.

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.

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.

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.

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.

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.

In the rapidly evolving automotive industry, the need for reliable and efficient pneumatic elastomeric components necessitates cutting-edge health monitoring methods, given that the pneumatic components are directly connected to dampening properties, ride comfort, vehicle safety, and stability. A novel approach for pneumatic elastomeric component health monitoring utilizing ionic liquid (IL)-based soft sensor technology has been proposed, which has the promise to enable real-time health monitoring and prognostics of vehicle systems. The proposed polymer sensor leverages the distinctive characteristics of flexibility, stretchability, and high sensitivity. These properties are critical for precisely measuring load, vertical displacement, air pressure, force locations, and load frequency of the air pressure responsive rubber part. The sensors are attached to three key contact positions: two on the metal cover of the elastomeric component and one on the piston of the component to provide critical information about the rolled and unrolled rubber. These sensors continuously measure essential parameters for health monitoring. The collected data can identify potential issues such as leaks, wear, or structural weaknesses. The finding illustrates the effectiveness of the IL-based soft sensors in providing precise and reliable data for health monitoring parameters.

Piezoelectric (PZT) energy harvesting technologies have regained popularity due to the increasing global demand for renewable electricity capacity and the sustainability requirements to be met by 2028. The evolution of this technology involves exploring various geometries to meet the natural frequency and power spectral density requirements. The rise of additive manufacturing has unlocked new possibilities for producing more complex geometries to further meet these requirements. This research focuses on the design, fabrication, and testing of a low-frequency, PZT-based vibration energy harvesting unit that employs additively manufactured substrates. The proposed unit is biologically inspired by the geometry of a golden tortoise beetle wing, known for its high flexibility, strength, and robust protection. The design features a rim structure divided into six equally sized sections, each with a PZT unit shaped in a meandering pattern made of beams with nonuniform thicknesses. The symmetry of each unit prevents charge cancellation caused by torsional effects. The substrate was 3D printed using the laser powder bed fusion technique. A two-step heat treatment process was employed to enhance the substrate's mechanical properties, such as yield strength. The PZT material was fabricated using dicing techniques and bonded to the substrate using electrically conductive epoxy. In addition to the conducted experiments to obtain the power spectrum for excitations at the fundamental natural frequency, the harvester was modeled using COMSOL software to obtain the natural frequency and power plots. The model and test results were in good agreement and the power density demonstrates its excellence compared to notable similar works in the literature.

To address the issue that traditional structures might inhibit the propagation of elastic waves only in one direction, a multi-dimensional (MD) quasi-zero-stiffness (QZS) mechanical metamaterial with multi-directional vibration isolation capability is proposed in this paper. The quasi-static mechanical properties and bandgap characteristics of the structure are investigated by a combination of simulation and experiment, revealing the influence of different cell numbers and frame thicknesses on the elastic wave propagation characteristics. Meanwhile, the vibration isolation performance of metamaterials with different material damping is explored by Rayleigh damping. The results demonstrate that the MD-QZS metamaterials proposed in this paper have excellent low-frequency attenuation ability for elastic waves in multi-directions, and the proportion of the bandgap under different loading directions within 0–200 Hz is about 60%–70%, offering an outstanding low-frequency broadband vibration isolation capability. In addition, each bandgap is almost constant with the number of unit cells, but the starting frequency would increase progressively as the frame thickness increasing. Meanwhile, the low-frequency vibration isolation performance of the metamaterial could be further enhanced by selecting the material with suitable damping. The MD-QZS mechanical metamaterials presented in this paper could provide a reference in the field of multi-functional structural design and supply a novel solution to the problem of multi-directional vibration isolation.

In aerospace applications, the Miura-ori core sandwich structure is increasingly recognized as a promising alternative to traditional honeycomb core structure. During aircraft operation, the structure is subjected to impact loads that generate vibrations, and excessive amplitude may lead to structural fatigue failure. In the present work, piezoelectric actuators and sensors were utilized to implement active vibration control of the Miura-ori sandwich beam (MSB). First, the motion equation of the MSB was derived based on Hamilton's principle and the assumed mode method, leading to the determination of its natural frequency. The shear deformation mechanism of the Miura-ori unit cell was then analyzed, and a new formula for calculating the equivalent transverse shear modulus is proposed. Further, the structure's vibration was actively controlled using a velocity feedback control algorithm, and the effectiveness of the vibration control along with the required voltage for the actuator is evaluated from both time and frequency domain perspectives. Additionally, a newly developed finite element method was proposed for the purpose of confirming the effectiveness of the vibration control. The results demonstrate a strong alignment between the simulated natural frequencies and the theoretical predictions, confirming that the velocity feedback control algorithm effectively reduces excessive vibration amplitudes.

Magnetorheological elastomers (MREs) belong to a class of smart materials that incorporate the elasticity of a soft polymer matrix with the magnetic responsiveness of embedded micro-particles. The combination of these distinct properties allows for significant changes in mechanical properties under external magnetic fields, known as the magnetorheological (MR) effect. In this study, computed x-ray microtomography was employed to investigate the microstructure and particle movement within a thermoplastic polyurethane based MRE under varying conditions. The sample was characterized at two different temperatures, both with and without the application of a magnetic field. Particle tracking was performed to analyze the movement of individual particles, and the global particle arrangement was characterized using the direction-dependent pair correlation function. The in-situ observations revealed distinct particle movements and microstructural changes influenced by magnetic fields and temperature. This study offers valuable insights into the translation behavior of particles in addition to the comparison of changes in their global particle structure with the MR effect.

In this paper, a mechanical metastructure with switching Poisson's ratio is proposed by combining the re-entrant honeycomb and octagonal honeycomb. The combined mechanical metastructure can enable the structure to transition from a negative Poisson's ratio to a positive Poisson's ratio (PPR), or from a zero Poisson's ratio to a PPR. Meanwhile, the load-bearing capacity and vibration isolation of the mechanical metastructure change with the Poisson's ratio of the structure varies. The relationship between the Poisson's ratio of the mechanical metastructure and its compressive force with band gap is investigated. The results indicate that the Poisson's ratio variation of the metastructure significantly affects its compressive force and band gap. The compressive force of the mechanical metastructure in either the negative or zero Poisson's ratio state is lower than that in the PPR state. Moreover, broad band gap can be achieved in the combined mechanical metastructure and the structure exhibits different band gap and frequency range in distinct Poisson's ratio states. Transmission spectrum and mode shapes are utilized to demonstrate the underlying mechanisms of wave attenuation. The proposed mechanical metastructure demonstrates significant potential for applications in structural health monitoring and vibration isolation, providing a valuable reference for the multi-functional design of mechanical metastructures.

The propagation characteristics of ultrasonic guided waves within the rim-driven thruster protective layer are more complex due to its anisotropic nature, resulting in low accuracy in damage detection using traditional imaging methods. Therefore, an intelligent optimization probability damage imaging method based on guided waves is proposed. First, a different probability of an individual is given by comparing the differences in the travel time of the individual with the travel time of the scattered signal. The total probability for the individual is derived by superimposing all paths, which serves as the fitness function. Subsequently, the individual with the highest fitness value is iteratively searched by the intelligent optimization algorithm. Finally, the optimized population distribution is considered as the damage location. The experimental results indicate that this method achieves a higher signal-to-noise ratio and detection accuracy compared to other approaches.

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.

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.

This review presents a detailed survey of Dielectric Elastomer Actuators (DEAs) and their emerging role in medical applications. DEAs are distinguished by their flexibility, low weight, and excellent biocompatibility, making them well-suited for a wide range of medical devices. The review explores the fundamental electro-mechanical principles behind DEA operation, which enable their remarkable ability to replicate natural muscle movements. Key applications discussed include biomedical devices, rehabilitation systems, in-vivo implants, and wearable health monitors, where DEAs offer dynamic, lifelike movements and precise control. Their ability to provide highly flexible and responsive actuation is a major advantage in medical technologies. However, challenges persist, particularly in terms of material durability, the need for high-voltage activation, and the integration of DEAs with existing medical technologies. By synthesizing recent research and highlighting ongoing hurdles, this review emphasizes the transformative potential of DEAs, offering a comprehensive look at their current state and future impact on next-generation medical devices.

The knee joint possesses immense biomechanical energy, and harnessing this energy offers the potential to deliver clean and sustainable power for portable wearable devices. Nevertheless, efficient methods for harvesting knee joint energy remain a great challenge. This study introduces a rope-driven energy harvesting device (REH) that employs a mechanical motion switch (MMS) to effectively capture the negative work generated by the knee joint. The MMS-REH utilizes coaxially reverse-wound ropes to drive the MMS, which incorporates a sliding gear, thereby transforming the knee joint's low-frequency oscillatory motion into high-speed unidirectional rotation of an electromagnetic power generation unit. This device is characterized by its simple design, insignificant impact on human motion, and high efficiency in harvesting the knee joint's negative work. Under a 240 Ω load, as human movement speed increases from 1 to 7 km/h, the MMS-REH output voltage rises from 3.6 to 7 V, and the output power increases from 10 to 80.1 mW. By integrating the signal characteristics generated by the MMS-REH with deep learning techniques, the device can not only generate power but also function as a sensor. This dual capability not only presents an innovative energy solution for wearable devices but also highlights its potential applications in motion monitoring, rehabilitation therapy, and elderly health management.

Due to the influence of various factors on bridge sensors, the signals obtained often contain multiple signal components, including temperature and vehicle induced effect. It is necessary to separate and analyze individual signals in bridge health detection. In order to separate temperature and vehicle response components from complex signals, this article proposes an improved VMD algorithm based on recursive methods, which takes the mean value of each recursive block as the eigenvalue, fits the eigenvalues of each recursive block using the least squares method, and separates the first intrinsic mode function. The applicability of this method in the field of bridges was first verified through modal decomposition of simulated deflection and strain data. Then based on the health monitoring data of the Jingtai Expressway viaduct, the rapid separation of temperature response and vehicle response of the bridge has been achieved. The results indicate that the recursive method is faster than directly using the traditional VMD algorithm. The mean square error obtained by separating simulation data is smaller than VMD. There is a high correlation coefficient between the separated measured data and temperature, proving the algorithm's ability to be used on bridge performance evaluation.

Soft actuators are increasingly drawing attention in robotic application with human-robot interaction. To tackle the challenging actuation problem confronted in the field of soft robotics or bionic engineering, combining origami technique with 3D printing manufacturing method, we propose an origami-inspired 3D-printed soft foldable actuator with the Kresling pattern that can be made in one go. The SFA is composed of a four-layer origami chamber made from soft materials with high resilience and high strength, which is capable of lifting a maximum weight of 2000 g with a contraction ratio of 62%, enduring a vacuum pressure up to 99.8 kPa while tuning longitudinal contraction deformation. Besides, it can generate a high stroke and a large driving force throughout the whole deformation process. Based on the principle of work equilibrium and combined with geometric theory, an analytical theoretical model that can evaluate large contraction deformation and actuation performance is established and validated experimentally, which is helpful for designing other similar soft actuators. Moreover, we analyze the effect of different structural parameters on actuation characteristics of the actuator and obtain an optimized SFA with best matched structural parameters. The SFA possessing multifunctional features is conducive to flexion and extension movement of a bionic anthropomorphic leg and can complete effective actions in some application scenarios including kicking ball, running exercise and grasping target objects, which opens up new opportunities for human-robot interaction and collaboration.

The superelasticity of shape memory alloys (SMA) can be used to provide self-centering and 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 (DSC) 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., superelastic limit. Low-cycle fatigue loading with different applied peak strains (2%, 3%, 4% and 5%) was performed at different temperatures (-40℃, -10℃, 10℃, 25℃ and 50℃). The effect of plastic deformation, testing temperature, and number of cycles on the stress-induced martensitic phase transformation (SIMT), degradation of superelastic properties, and fatigue life was 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.

This investigation examined the mechanical strength and failure behaviour of various 3D printed lattices for implantation in bones, consisting of Octahedral, Double Pyramid, Diamond and Cubic lattices. The combination of this research methodology includes a Finite Element Analysis and fatigue testing. Low-cycle compressive fatigue tests were performed using specialised equipment, in addition to the employment of a scanning electron microscope (SEM) for the properties of the surface and failure modes. The results of this study show that the octahedral lattice provides improved structural performance, a small amount of deformation, uniform stress distribution, and the greatest levels of fatigue resistance. Both Diamond and Double Pyramid lattices indicate moderate deformation and fatigue strength; therefore, they are recommended where flexibility, together with high performance, is a concern. However, the cubic lattice was the worst case, resulting in the highest localised stress and poor ductility. Based on this extensive comparison of identifiers when using fused lattices configured for PLA materials, further studies must introduce physiological stimuli and use versatile biomaterials such as PEEK and titanium. The findings around lattice structure re-emphasise the criticality of lattice choice in the overall improvement of implant outcomes, with the octahedral lattice identified to have impressive fatigue properties that will work well in weight-bearing implants. This study furthers the field of biomedical implant science which could help improve the prognosis of patients through the use of robust bone implants.

Magnetorheological elastomers (MREs) belong to a class of smart materials that incorporate the elasticity of a soft polymer matrix with the magnetic responsiveness of embedded micro-particles. The combination of these distinct properties allows for significant changes in mechanical properties under external magnetic fields, known as the magnetorheological (MR) effect. In this study, computed x-ray microtomography was employed to investigate the microstructure and particle movement within a thermoplastic polyurethane based MRE under varying conditions. The sample was characterized at two different temperatures, both with and without the application of a magnetic field. Particle tracking was performed to analyze the movement of individual particles, and the global particle arrangement was characterized using the direction-dependent pair correlation function. The in-situ observations revealed distinct particle movements and microstructural changes influenced by magnetic fields and temperature. This study offers valuable insights into the translation behavior of particles in addition to the comparison of changes in their global particle structure with the MR effect.

The superelasticity of shape memory alloys (SMA) can be used to provide self-centering and 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 (DSC) 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., superelastic limit. Low-cycle fatigue loading with different applied peak strains (2%, 3%, 4% and 5%) was performed at different temperatures (-40℃, -10℃, 10℃, 25℃ and 50℃). The effect of plastic deformation, testing temperature, and number of cycles on the stress-induced martensitic phase transformation (SIMT), degradation of superelastic properties, and fatigue life was 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.

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.

Piezoelectric (PZT) energy harvesting technologies have regained popularity due to the increasing global demand for renewable electricity capacity and the sustainability requirements to be met by 2028. The evolution of this technology involves exploring various geometries to meet the natural frequency and power spectral density requirements. The rise of additive manufacturing has unlocked new possibilities for producing more complex geometries to further meet these requirements. This research focuses on the design, fabrication, and testing of a low-frequency, PZT-based vibration energy harvesting unit that employs additively manufactured substrates. The proposed unit is biologically inspired by the geometry of a golden tortoise beetle wing, known for its high flexibility, strength, and robust protection. The design features a rim structure divided into six equally sized sections, each with a PZT unit shaped in a meandering pattern made of beams with nonuniform thicknesses. The symmetry of each unit prevents charge cancellation caused by torsional effects. The substrate was 3D printed using the laser powder bed fusion technique. A two-step heat treatment process was employed to enhance the substrate's mechanical properties, such as yield strength. The PZT material was fabricated using dicing techniques and bonded to the substrate using electrically conductive epoxy. In addition to the conducted experiments to obtain the power spectrum for excitations at the fundamental natural frequency, the harvester was modeled using COMSOL software to obtain the natural frequency and power plots. The model and test results were in good agreement and the power density demonstrates its excellence compared to notable similar works in the literature.

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.

This work presents innovations in polymer science through the development of antimicrobial and reprocessable shape-memory vitrimers from biobased vanillin and glycerol acrylates, incorporating pentaerythritol tetrakis(3-mercaptopropionate). The addition of this thiol increased the viscosity of the resin and reduced shrinkage and rigidity, without significantly affecting the polymerization rate. Samples containing 20 wt.% of thiol exhibited self-welding and 40% self-healing efficiency after just 10 min of heating at 180 °C and without additional pressure, significantly improving mechanical properties. The ability of vitrimers to maintain a temporary shape and return to a permanent shape under temperature changes showed shape-memory behavior, making them suitable for medicine, electronics, and robotics. The mechanical properties remained consistent after three reprocessing cycles, highlighting the sustainability of the vitrimers. The antimicrobial activity of these vitrimers showed efficacy up to 100%, suitable for antimicrobial films, coatings, and 3D printed parts. Microimprint lithography enabled micrometer-scale patterns, highlighting broad practical applications of the vitrimers.

In this work, a new experimental shunt tuning procedure is proposed for piezoelectric shunts targeting a single vibration mode of a flexible structure. The procedure is based on measurements of the dynamic capacitance of the piezoelectric transducer, eliminating the need for additional sensors or actuators. It is demonstrated that all required electromechanical parameters for shunt calibration can be determined from two extremum points on the dynamic capacitance curve. Corrections for the influence of residual modes are included to enable the consistent application of existing tuning expressions for various shunt topologies. The hardware of a digital shunt is used for the measurement of the dynamic capacitance allowing for low-cost implementation. The proposed method is validated numerically and experimentally through the calibration of a series RL shunt using both analog and digital components.

Polydimethylsiloxane (PDMS) based ferroelectrets are an attractive material for the fabrication of human-based applications given their soft and compliant mechanical properties. The typical fabrication approach is to exploit specifically engineered void geometries fabricated by moulding and bonding layers together. Charge instability can be addressed by the addition of Polytetrafluoroethylene (PTFE) particles but this prevents the bonding of PDMS films. This paper illustrates a new approach to obtaining PDMS ferroelectret with random voids by promoting and trapping bubbles to create cavities within a PDMS film. A mathematical model is presented to explore the connection between the percentage of trapped bubbles in the PDMS and the equivalent piezoelectric coefficient, d_33e. The process is compatible with the addition of PTFE powder to the PDMS formulation and a ratio of PTFE to PDMS of 1:3 by weight was found to increase performance achieving an initial d_33e of 384 pC/N which reached a steady state value of 186 pC/N measured after 2 months after poling. The energy harvesting potential of the random void PDMS/PTFE ferroelectret was explored by cyclically compressing with a force of 300 N applied at 1 Hz. The output of the ferroelectret was found to charge a 10μF capacitor to 0.26 V after 40 s. The ferroelectret's performance as a pressure sensor from 0 to 300 N was explored, and the optimum formulation achieved a sensitivity of 25.2 mV/N, a nonlinearity of 4%, and hysteresis of 4.2%, demonstrating a considerable improvement over the pure PDMS ferroelectret.

This paper describes and evaluates the embedding of sensors and electronic sensor nodes into fiber metal laminate (FML) plates to achieve material-integrated, guided ultrasonic wave based structural health monitoring for hybrid materials. It evaluates how embedded electronics can enhance the process of sensor data acquisition and at the same time critically investigates the drawbacks that accompany the embedding approach regarding the influence on the received signal. A FML specimen with single sensors in one half of the plate and sensors with attached electronic sensor nodes for wireless readout in the other half is manufactured, introducing the detailed embedding process for such systems. Ultrasonic through-thickness scans of the manufactured plate are presented and analyzed to assess the achieved embedding quality. Together with electric sensor signals from both, wireless and wirebound micro-electromechanical system vibrometers and data from a scanning laser Doppler vibrometer (SLDV) the influence of material-integrated components on the wave propagation around the locations of integration is discussed. Further, the signals of wirebound sensors are successfully correlated with measurements performed using the SLDV and directly compared to data provided by wirelessly readout sensor nodes having the same type of sensor attached. This work shows how reflections occurring due to a material integration of components influence the recorded sensor data. At the same time, it is discussed how, for baseline-based damage detection methods, the influence of this is assumed to be a minor problem, and proof for advantages provided by the integration of complete sensor systems directly into the host material is provided.