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A structure-level smart deployable truss (SDT) was further studied for on-orbit verification on the SJ18 Geostationary Satellite in this work on the basis of a material-level validation of a shape-memory polymer composite (SMPC) sheet on the SJ17 Geostationary Satellite in 2016. In the SDT, a shape-memory alloy (SMA) mechanism was used to replace traditional pyrotechnic devices for locking and releasing, and SMPC actuation laminates were employed to replace traditional motor or spring driving mechanisms. With a strict parameter constrain of mass, size, and stiffness, the current form of the SDT flight hardware was finally obtained through several cycles of optimization design. Its systematical ground-based experiments were conducted, and the overall structural and functional performance met the demands of the aerospace standards of China. The locking force and expansion breaking force of the SMA releasing mechanism were [Formula: see text] and [Formula: see text], ensuring the locking and unlocking reliability for the movable parts with mass 5 kg. The actuation force of all SMPC laminates decreased from [Formula: see text] (0°) to [Formula: see text] (165°) with a recovery duration of [Formula: see text], which was strong enough for SDT deployment in space. The shape-memory materials show great prospects for smart deployable structures in space.

As an important part of many mechanical equipment, the mechanical transmission system is very important to carry out efficient and accurate fault monitoring and diagnosis. Compared with traditional fault diagnosis techniques, such as spectrum analysis, deep learning has been widely used in the field of mechanical system fault diagnosis due to its powerful data expression ability, and has achieved certain research results. One-dimensional convolutional neural network is a widely used model for deep learning, so in this paper, the one-dimensional convolutional neural network (1D-CNN) in the deep learning theory and the vibration signal analysis method are integrated and applied to the fault identification of mechanical transmission system to achieve accurate diagnosis and classification of faults. The experiment is mainly to collect the vibration signal data of different fault states such as broken teeth, cracking, shaft unbalance, bearing wear, and excessive friction of the driven wheel of the mechanical transmission system, it was divided into training set and testing set according to an appropriate proportion, and 1D-CNN was built using Python. The deep learning model deeply analyzed the influence of different data sample sizes and different model parameters on the recognition accuracy, and obtained an ideal diagnostic model based on variable learning rate through parameter adjustment and comparative analysis. This experimental results show that the recognition method based on one-dimensional convolutional neural network can be effectively applied to the fault diagnosis of related mechanical transmission, and has a high diagnosis accuracy.

Shape memory polymers (SMPs) and SMP composites (SMPCs) have been widely employed in several fields and exhibit excellent self-actuation, deformation, and self-adaption. Establishing reasonable constitutive models is vital for understanding the shape memory mechanism and expanding its applications. Moreover, the mechanical response of SMPs under different conditions can be predicted, facilitating their precise control. The internal mechanism for the shape memory behavior in most SMPs is thermal actuation. This study reviews the theories of thermally actuated SMPs, rheological and phase transition concept models, and models combining the rheology and phase transition concepts. Furthermore, the constitutive models of particulate-reinforced SMPCs, carbon-fiber-reinforced SMPCs, and the buckling behavior of SMPCs are summarized. This study is expected to help solve the remaining issues rapidly and contribute to the establishment of rational constitutive models for SMPs and SMPCs.

Electroadhesion has shown the potential to deliver versatile handling devices because of its simplicity of actuation and rapid response. Current electroadhesion systems have, however, significant difficulties in adapting to external objects with complex shapes. Here, a novel concept of metasurface is proposed by combining the use of natural fibers (flax) and shape memory epoxy polymers in a hygromorphic and thermally actuated composite (HyTemC). The biobased material composite can be used to manipulate adhesive surfaces with high precision and controlled environmental actuation. The HyTemC concept is preprogrammed to store controllable moisture and autonomous desorption when exposed to the operational environment, and can reach predesigned bending curvatures up to 31.9 m

Percutaneous closure of ventricular septal defect (VSD) can effectively occlude abnormal blood flow between ventricles. However, commonly used Nitinol occlusion devices have non-negligible limitations, such as nondegradability leading to life-threatening embolization; limited device size predisposing to displacement and wear; only a few radiopaque markers resulting in inaccurate positioning. Nevertheless, the exploration of customized, biodegradable, and overall radiopaque occluders is still vacant. Here, overall radiopaque, biodegradable, and dynamic reconfigurable 4D printed VSD occluders are developed. Based on wavy bionic structures, various VSD occluders are designed and manufactured to adapt to the position diversity of VSD. The customized configuration, biocompatibility, and biodegradability of the developed 4D printed bionic occluders can eliminate the series of complications caused by traditional occluders. The overall radiopacity of 4D printed VSD occluders is validated ex vivo and in vivo, whereby accurate positioning can be assured. Notably, the preparation strategies for 4D printed occluders are scalable, eliminating the barriers to mass production, and marking a meaningful step in bridging the gap between modeling and clinical application of 4D printed occlusion devices. This work opens attractive perspectives for the rapid manufacturing of customized intelligent medical devices for which overall radiopacity, dynamic reconfigurability, biocompatibility, and biodegradability are sought.

Electrostatic layer jamming represents a lightweight, low energy consumption, electrically tunable, and cost-effective variable stiffness structure. Flexible parallel electroadhesive structures are the simplest form of electrostatic layer jamming. There is a lack of comprehensive and experimentally validated theoretical variable stiffness models of flexible parallel electroadhesive structures. Here we present the first variable stiffness model of flexible parallel electroadhesive structures under three-point bending, cantilever beam bending subjected to tip concentrated forces, and cantilever beam bending subjected to uniformly distributed forces, using the Euler–Bernoulli beam theory and considering friction and slip between layers by integrating the Maxwell stress tensor into the model. We find that: (1) three-point bending and cantilever beam bending under tip concentrated forces only have pre-slip and full-slip, whereas cantilever beam bending under uniformly distributed forces has an additional partial-slip which can be used for stiffness modulation; (2) the stiffness during the pre-slip stage is four times larger than the stiffness in the full-slip stage; and (3) increasing the voltage, dielectric permittivity, and coefficient of friction can elongate the pre-slip stage, thus enhancing the structural load capability. A customized three-point bending and a cantilever beam bending experimental setup were developed and the experimental deflection–force curve agreed relatively well with the theoretical one. The model, which considered electrode thickness and Young’s modulus, and the results presented in this work are useful insights for understanding the variable stiffness mechanism of electroadhesive layer jamming and are helpful for their structural optimization towards practical applications.

Shape memory polymer (SMP) and SMP composites (SMPC) can memorize the permanent shape and recover from the temporary shape to the permanent shape when stimulated by the appropriate stimuli. Because of the unique shape memory effect, coupled with its low cost, low density, high specific strength, biodegradability, biocompatibility, and other characteristics, SMP and SMPC have become possible materials to solve the problems currently faced by space deployable structures, biomedical devices, mold manufacturing, release devices, etc. This work reviews the research and developments of SMP and SMPC, including the achievements in constitutive theory, the applications, and prospects in aerospace, biomedical medicine, intelligent mold, and release devices.

In engineering component design, material models are increasingly used in finite element simulations for an expeditious and less costly analysis of the design prototypes. As such, researchers strive to formulate models that are less complex, robust, and accurate. In the realm of hyperelastic materials, phenomenological-based Carroll's model is highly promising due to its simplicity and accuracy. This work proposes its further improvement by modifying the strain energy density function to comply with the restriction that it should vanish at reference configuration and adding a compressible term to capture the practical behavior of elastomeric materials and to avoid numerical problems during finite element implementation. The model constants for both the original and the modified versions were obtained by fitting their respective expressions to the classical Treloar's experimental data using the Levenberg–Marquardt algorithm. The modified model was implemented using Abaqus CAE 2016 via a vectorized user material (VUMAT) subroutine. Comparisons of the model predictions with Treloar's experimental data demonstrated the superiority of the modified version particularly in the equibiaxial loading mode. Moreover, the simulated and the experimentally observed behavior agreed to a great accuracy thus making the modified model suitable for simulating the loading response of components fabricated of elastomeric materials. In this work, the Carroll's hyperelastic model strain energy density expression is modified to comply with the mathematical restriction that it should vanish at the undeformed configuration. Furthermore, a compressible term is added to capture the practical behavior of elastomers and to avoid numerical problems during finite element implementation. Numerical and finite element predictions are compared with classical experimental data upon which the modified model demonstrated superior predictive capabilities particularly in the equibiaxial loading mode.

When the electric field caused by voltage reaches a certain level, the charge on the compliant electrodes will not increase owing to the polarization saturation, which would limit the deformation of the dielectric elastomer. Some experiments show that temperature also has a significant effect on the deformation of dielectric elastomer. In this work, a free energy model coupling temperature and polarization saturation is developed to characterize the thermoelectromechanical instability of dielectric elastomer. The results reveal that both the polarization saturation parameters and electric field have a significant influence on the actuation ability of the dielectric elastomer, and the increase of temperature enhances thermoelectromechanical stability. It is hoped that this work could guide the development of dielectric elastomer materials and application devices operating in variable temperatures.

The significant mismatch of mechanical properties between the implanted medical device and biological tissue is prone to cause wear and even perforation. In addition, the limited biocompatibility and nondegradability of commercial Nitinol-based occlusion devices can easily lead to other serious complications, such as allergy and corrosion. The present study aims to develop a 4D printed patient-specific absorbable left atrial appendage occluder (LAAO) that can match the deformation of left atrial appendage (LAA) tissue to reduce complications. The desirable bioinspired network is explored by iterative optimization to mimic the stress-strain curve of LAA tissue and LAAOs are designed based on the optimal network. In vitro degradation tests are carried out to evaluate the effects of degradation on mechanical properties. In addition, 48 weeks of long-term subcutaneous implantation of the occluder shows favorable biocompatibility, and the 20-cycle compression test demonstrates outstanding durability of LAAO. Besides, a rapid, complete, and remote-controlled 4D transformation process of LAAO is achieved under the trigger of the magnetic field. The deployment of the LAAO in an isolated swine heart initially exhibits its feasibility for transcatheter LAA occlusion. To the best of our knowledge, this is the first demonstration of the 4D printed LAA occlusion device. It is worth noting that the bioinspired design concept is not only applicable to occlusion devices, but also to many other implantable medical devices, which is conducive to reducing complications, and a broad range of appealing application prospects can be foreseen.

As a kind of smart material, shape memory polymer (SMP) shows great application potential in the biomedical field. Compared with traditional metal-based medical devices, SMP-based devices have the following characteristics: 1) The adaptive ability allows the biomedical device to better match the surrounding tissue after being implanted into the body by minimally invasive implantation; 2) it has better biocompatibility and adjustable biodegradability; 3) mechanical properties can be regulated in a large range to better match with the surrounding tissue. 4D printing technology is a comprehensive technology based on smart materials and 3D printing, which has great application value in the biomedical field. 4D printing technology breaks through the technical bottleneck of personalized customization and provides a new opportunity for the further development of the biomedical field. This paper summarizes the application of SMP and 4D printing technology in the field of bone tissue scaffolds, tracheal scaffolds, and drug release, etc. Moreover, this paper analyzes the existing problems and prospects, hoping to provide a preliminary discussion and useful reference for the application of SMP in biomedical engineering.

With a 10% reversible compressive strain in more than 10 deformation cycles, the shape memory polymer composites (SMPCs) could be used for deployable structure and releasing mechanism. In this paper, without traditional electro-explosive devices or motors/controllers, the deployable SMPC flexible solar array system (SMPC-FSAS) is studied, developed, ground-based tested, and finally on-orbit validated. The epoxy-based SMPC is used for the rolling-out variable-stiffness beams as a structural frame as well as an actuator for the flexible blanket solar array. The releasing mechanism is primarily made of the cyanate-based SMPC, which has a high locking stiffness to withstand 50 g gravitational acceleration and a large unlocking displacement of 10 mm. The systematical mechanical and thermal qualification tests of the SMPC-FSAS flight hardware were performed, including sinusoidal sweeping vibration, shocking, acceleration, thermal equilibrium, thermal vacuum cycling, and thermal cycling test. The locking function of the SMPC releasing mechanisms was in normal when launching aboard the SJ20 Geostationary Satellite on 27 Dec., 2019. The SMPC-FSAS flight hardware successfully unlocked and deployed on 5 Jan., 2020 on geostationary orbit. The triggering signal of limit switches returned to ground at the 139 s upon heating, which indicated the successful unlocking function of SMPC releasing mechanisms. A pair of epoxy-based SMPC rolled variable-stiffness tubes, which clapped the flexible blanket solar array, slowly deployed and finally approached an approximate 100% shape recovery ratio within 60 s upon heating. The study and on-orbit successful validation of the SMPC-FSAS flight hardware could accelerate the related study and associated productions to be used for the next-generation releasing mechanisms as well as space deployable structures, such as new releasing mechanisms with low-shocking, testability and reusability, and ultra-large space deployable solar arrays.

Shape memory polymers (SMPs) have received immense attention from materials research community thanks to their unrivaled properties such as high recoverable strains (up to 400%), low weight, tailorable properties, easy processing, and multiple activation methods. Researchers in both academia and industry have been proposing, experimenting, analyzing, and reporting on various aspects of these materials from synthesis to their applications. Such efforts have led to skyrocketing research output in terms of published papers, especially in the last half a decade. Despite the flourishing research, numerous challenges that hinder advanced applications still exist with the predominant one being the low mechanical properties. To circumvent these challenges, various types of reinforcements have been utilized, leading to significant enhancements and widened potential applications. This work presents an overview of the present research on active composites. Areas covered include the background of SMPs, reinforcements, fabrication techniques, stimulus methods, and applications. Our review is particularly unique in that we included discussions on the various fabrication techniques for SMP composites including their merits and demerits which, to the best of our knowledge, is the first review to include such discussion, thus making it a complete reference material.

Synchrotron radiation X-ray micro-computed tomography (SR-µCT) is a 3D imaging technique that is widely employed for the characterization of defects in advanced materials and structures. In this study, we characterize several typical defects in octettruss and re-entrant 3D lattice structures by using SR-µCT. The 3D micro-lattice structures are manufactured using projection micro litho stereo exposure (PµLSE) additive manufacturing technology. The as-fabricated 3D lattice samples are characterized using optical microscopy, and subsequently, by SR-µCT. Further more, a statistical analysis is performed to characterize the surface roughness and internal defects qualitatively, whereby the statistical geometrical parameters of struts along different directions and strut joints are analyzed and classified. Consequently, several typical defects are identified: (1) holes at the joints of the strut and irregular diameter deviations of the strut in the octet-truss lattice structure; (2) irregular diameter variations, bulges, dislocations, grooves, accumulations, and torsion in the re-entrant lattice structure. All of these defects are related to the building direction, the weight of the structure, bubbles, dust, and impurities during the PµLSE additive manufacturing process.