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Liquid Crystal Elastomers (LCEs) are renowned for their reversible deformation capabilities. Yet, enhancing their mechanical strength while retaining such flexibility has posed a considerable challenge. To overcome this, we utilized 4D printing to develop an innovative composite of LCE with carbon fiber fabric (LCEC). This approach has notably increased the tensile strength of LCE by eightfold, all the while maintaining its exceptional capacity for reversible deformation. By adjusting the alignment angle between carbon fiber and the LCE printing direction from 0° to 90°, the LCEC demonstrates an array of new deformation patterns, including bending, twisting, wrapping, and S-shaped transformations, which are distinct from pure LCE materials. Our study unveils that LCE composites exhibit deformation processes markedly different from their pure material counterparts, with the ability of pure LCE to sustain tensile strains exceeding 1900%. These findings, previously undocumented and unexplored, represent a substantial contribution to the field of smart materials. Employing finite element analysis, we explored the carbon fiber and LCE matrix dynamics, revealing bending mechanics in LCECs. This combined experimental and simulation approach yields crucial insights for crafting durable, high-strength LCECs with diverse deformational properties, advancing smart material technology.

Abstract Unwanted ice formations may cause severe functional degradations of facilities and also have a negative impact on their lifespans. Avoiding and removing ice accumulation is always a hot topic in the industrial and technological field. Bionic functional surfaces have been greatly studied for several decades and have proved to be excellent candidates for passive anti‐/deicing applications. However, the drawbacks limit their potential industrial uses under harsh conditions, like low temperatures and high humidity. Most researches on bionic surfaces are focused on a certain function of natural creatures and their underlined fundamental theories are revealed by taking the interface as the static. Actually, living organisms, either plants or animals, are often sensitive and responsive to their surroundings, avoiding risks and even self‐repairing upon damage. From this prospect, a novel view of the bionic icephobic materials has been proposed in the present review, which is expected to be studied and designed by taking the biological species as a system. As two representative icephobic materials, the anti‐/deicing theories of superhydrophobic and slippery surfaces are first discussed. Further, the recent progress of smart icephobic strategies is summarized from interfaces to substrates. We aim to provide new bionic insights on designing future icephobic strategies.

Once China’s Tianwen-1 Mars probe arrived in a Mars orbit after a seven-month flight in the deep cold space environment, it would be urgently necessary to monitor its state and the surrounding environment. To address this issue, we developed a flexible deployable subsystem based on shape memory polymer composites (SMPC-FDS) with a large folding ratio, which incorporates a camera and two temperature telemetry points for monitoring the local state of the Mars orbiter and the deep space environment. Here, we report on the development, testing, and successful application of the SMPC-FDS. Before reaching its Mars remote-sensing orbit, the SMPC-FDS is designed to be in a folded state with high stiffness; after reaching orbit, it is in a deployed state with a large envelope. The transition from the folded state to the deployed state is achieved by electrically heating the shape memory polymer composites (SMPCs); during this process, the camera on the SMPC-FDS can capture the local state of the orbiter from multiple angles. Moreover, temperature telemetry points on the SMPC-FDS provide feedback on the environment temperature and the temperature change of the SMPCs during the energization process. By simulating a Mars on-orbit space environment, the engineering reliability of the SMPC-FDS was comprehensively verified in terms of the material properties, structural dynamic performance, and thermal vacuum deployment feasibility. Since the launch of Tianwen-1 on 23 July 2020, scientific data on the temperature environment around Tianwen-1 has been successfully acquired from the telemetry points on the SMPC-FDS, and the local state of the orbiter has been photographed in orbit, showing the national flag of China fixed on the orbiter.

In this research work, we present a mathematical analysis of a fractional sixth-order laser model of a resonant which is homogeneously extended three-level optically pumped. We use Caputo fractional order derivative in the proposed model. Our analysis includes an investigation of various chaotic behaviors under fractional order derivative and qualitative theory of the existence of the solution to the proposed model. For our required analysis of qualitative type, we use formal analysis tools. Further, numerical simulations are performed with a clustering method based on the K–Means algorithm and Adams Bashforth scheme. With the help of the aforesaid scheme, we present different chaotic behavior corresponding to various values of fractional order. Finally, we give a comparison of the CPU time of the proposed method with that of the RK4 method.

When studying signal reconstruction, the frames are often selected in advance as encoding tools. However, in practical applications, this encoding frame may be subject to attacks by intermediaries and generate errors. To solve this problem, in this paper, the erasure recovery matrices for data erasures and rearrangements are analyzed. Unlike the previous research, first of all, we introduce a kind of frame and its erasure recovery matrix M so that MI,Λ=Im×m, where Im×m is a unit matrix. In this case, we do not need to invert the matrix of the frame operator and the erasure recovery matrix, and this greatly simplifies reconstruction problems and calculations. Then three different construction algorithms of the above erasure recovery matrix M and the frame are proposed, and each of them has advantages. Furthermore, some restrictions on M so that the constructed frame and erasure recovery matrix M can recover coefficients from rearrangements are imposed. We prove that in some cases, the above M and frame can recover coefficients stably from m rearrangements.

The target tracking by space-based surveillance systems is difficult due to the long distances, weak energies, fast speeds, high false alarm rates, and low algorithmic efficiencies involved in the process. To mitigate the impact of these difficulties, this article proposes a target tracking algorithm based on image processing and Transformer, which employs a two-dimensional Gaussian soft-thresholding method to reduce the image noise, and combines a Laplace operator-weighted fusion method to augment the image, so as to improve the overall quality of the image and increase the accuracy of target tracking. Based on the SiamCAR framework, the Transformer model in the field of natural language processing is introduced, which can be used to enhance the image features extracted from the backbone network by mining the rich temporal information between the initial and dynamic templates. In order to capture the information of the target’s appearance change in the temporal sequence, a template update branch is introduced at the input of the algorithm, which realizes the dynamic update of the templates by constructing a template memory pool, and selecting the best templates for the candidate templates in the memory pool using the cosine similarity-based selection, thus ensuring the robustness of the tracking algorithm. The experimental results that compared with the SiamCAR algorithm and the mainstream algorithms, the TrD-Siam algorithm proposed in this article effectively improves the tracking success rate and accuracy, addressing poor target tracking performance under space-based conditions, and has a good value of application in the field of optoelectronic detection.

ABSTRACTResearch on microcapsules has been conducted in recent years given trends in miniaturization and novel functionalization. In this work, we designed and prepared a series of unique shape memory polyurethane (SMPU) microcapsules with stimuli-responsive functions. The microcapsule has a core-shell structure in which the surface morphology can be adjusted, and it has a certain load-bearing capacity. In addition, the SMPU microcapsule has a stimuli-responsive function for shape memory and solvent response. The temperature of its shape recovery is approximately body temperature, and it can swell to rupture under the stimulation of organic solvents. Thus, the SMPU microcapsule has potential applications in biomedical fields, such as drug release.

ABSTRACTArtificial architected metamaterials equipped with unique mechanical and physical properties that are naturally inaccessible can be obtained by rational design. In this work, the innovative three-dimensional (3D) chiral and anti-chiral metamaterials are developed referring to the face-rotating polyhedral (FRP) structure present in the virus. Through assembling planar triangular units into the regular octahedron cells, several typical forms of chiral and anti-chiral metamaterials can be obtained by different assembly methods. By changing the topology parameters, the Poisson’s ratio can be adjusted between [0, 2.8]. The metamaterials are fabricated by 3D printing utilizing shape memory polymer, and the mechanical properties are analyzed via Finite Element Analysis (FEA) and experiments, including Young’s modulus, Poisson’s ratio, and tension-twist coupling behavior. In addition, target metamaterial with specific local deformation behavior is obtained by programmatic calculations and distributions to meet special requirements or achieve unique applications. The shape memory property endows the mechanical metamaterials with more potential applications.

Shape memory polymers (SMPs) are smart materials that can alter their shape from a temporary shape to a permanent shape upon external stimuli. This unique property of SMP has shown enormous potential and breakthrough discoveries in biomedical engineering. A significant number of SMP based research publications in the recent past have demonstrated the researchers’ thirst to introduce SMP based devices to the biomedical fields. SMPs favour minimally invasive surgeries and showed enormous potential in vascular stents. However, SMP-based vascular stents have not been realised to date, indicating a lack of high-quality research outputs. Most studies either repeat or provide only minor extensions to ongoing research. This article reviews SMP materials used for vascular stent development and briefly introduces SMP, architecture, and history.Followed by SMP vascular stent fabrication methods, responsive physical behaviour, the performance of the vascular stents, limitations, and vitro and vivo clinical results. Finally, challenges and future directions of SMP vascular stents are identified and highlighted.

With the continuous increase in human demand to improve aircraft performance, intelligent aircraft technologies have become a popular research field in recent years. Among them, the deformable skin structure has become one of the key technologies to achieve excellent and reliable performance. However, during the service, deformable skin structures may encounter problems such as surface impact and adhesion of droplets in rainy weather or surface icing in low-temperature environments, which can seriously affect the flight safety of the aircraft. One way to overcome these issues is to use superhydrophobic shape memory materials in the structure. In this regard, first, shape memory composites were prepared with shape memory epoxy resin as the matrix and carbon fiber orthogonal woven fabric as the reinforcement material. Superhydrophobic shape memory composites (SSMCs) were then obtained by casting the kirigami composite with superhydrophobic carbon nanotube–polydimethylsiloxane (CNT@PDMS) mixture, and the surface was processed by laser micromachining. Shape memory performance and surface wetting performance were determined by material testing methods. The results showed that the shape memory recovery rate can reach 85.11%, the surface is superhydrophobic, the average water contact angle is 156.9 ± 4.4°, and the average rolling angle is 3 ± 0.5°. The three-point bending test of the specimens with different kirigami cell configurations showed that the shape memory composite based on the rectangular structure has the best deformability with an aspect ratio of 0.4. From the droplet impact test, it was found that the impact speed of water droplets and the curvature of the surface can greatly affect the dynamic performance of water. This work is expected to be of significant research value and importance for developing functional deformable skin materials.

Shape memory polymers, with intrinsic enhanced strength and high thermal stability, are highly demanded in aerospace, engineering manufacturing, and spatial structures. In this paper, we develop a series of thermoplastic shape memory poly(ether ether ketone)s (PEEKs) for the first time, achieving an excellent shape memory ability, high strength, and great thermal stability via a condensation polymerization. Through tuning the proportion of different bisphenol monomers, the flexibility of molecular main chains is adjusted, resulting in the regulation of transition temperature and mechanical performances. Synthesized PEEKs possess the tunable Tg from 143.3°C to 178.6°C, the enhanced tensile strength from 48.4 to 65.1 MPa, and Young’s modulus from 0.45 to 1.8 GPa, in addition to the excellent heat-triggered shape memory effect, as indicated by high recovery ratio (94%–98.9%) and fixity ratio (over 99.5%). Furthermore, after incorporating the magnetocaloric Fe3O4 particles, the composites exhibit remotely noncontact magnetic-triggered shape memory behaviors (Fe3O4 content over 10 wt%). These synthesized Tg tunable shape memory PEEKs and the composites have wide utilization potential in fields of engineering and aerospace structures, owing to the excellent mechanical properties, thermal stability, unique programmable deformation ability, and remote actuation.

Shape memory polymers (SMPs) and their composites (SMPCs) are smart materials that can be stably deformed and then return to their original shape under external stimulation, thus having a memory of their shape. Three-dimensional (3D) printing is an advanced technology for fabricating products using a digital software tool. Four-dimensional (4D) printing is a new generation of additive manufacturing technology that combines shape memory materials and 3D printing technology. Currently, 4D-printed SMPs and SMPCs are gaining considerable research attention and are finding use in various fields, including biomedical science. This review introduces SMPs, SMPCs, and 4D printing technologies, highlighting several special 4D-printed structures. It summarizes the recent research progress of 4D-printed SMPs and SMPCs in various fields, with particular emphasis on biomedical applications. Additionally, it presents an overview of the challenges and development prospects of 4D-printed SMPs and SMPCs and provides a preliminary discussion and useful reference for the research and application of 4D-printed SMPs and SMPCs.

The use of shape memory polymer composites as novel materials for next generation space deployable structures requires the study of the effect of space environment upon their properties. The resistance of carbon fiber/epoxy shape memory polymer composite to vacuum thermal cycling, ultraviolet radiation and atomic oxygen has been evaluated separately by using ground-based simulation facilities. The thermal cycling condition has a temperature range of −100 °C to +100 °C with cycle times of 0, 15, 30, and 45. The irradiation times of ultraviolet with a wavelength range of 250 nm–400 nm are 0, 80, 160, and 240 h. The atomic oxygen radiation has a translational energy of about 5 eV and a flux of about 2 × 1015 atoms/cm2 at the sample position, and the irradiation times are 0, 33, 66, and 100 h. The shape memory polymer composite specimens are compared in terms of morphology, tensile modulus, breaking strength and elongation at break before and after irradiation. Results show that thermal cycling increases tensile modulus but decreases the breaking strength and the elongation at break of material after 45 cycles. The effect of ultraviolet radiation on mechanical properties of materials depends on the radiation dose received. Atomic oxygen can negatively but slightly affect the mechanical properties of the material.

Abstract In this paper, we establish Parseval identities and surprising new inequalities for weaving frames in Hilbert spaces which involve scalar λ ∈ R $\lambda \in {\mathcal{R}}$ . With suitable choices of λ, one obtains the previous results as special cases. Our results generalize and improve the remarkable results obtained by Balan et al. and Găvruţa.

As a kind of medical treatment device, shape memory tracheal stent has a good application prospect. The biodegradable stent can effectively reduce the damage to patients and improve the therapeutic performance of stents. In this work, a series of shape memory polylactic acid (Fe3O4) composite tracheal stents were manufactured by 4D printing. The composite tracheal stents with different structures were designed. Moreover, with the addition of magnetic particles Fe3O4, the shape memory PLA/Fe3O4 composite tracheal stent has a magnetic driving effect. Under the magnetic field, the shape recovery process is completed within 40 s, and the shape recovery rate is more than 99%. Moreover, the 4D printed tracheal stent was also triggered by the irradiation of infrared lamp to realize the remote controlling recovery. The research on the structure design and driving method of 4D printing tracheal stent expands the application scope of shape memory polymer composites in biomedical field, provides a new way for personalized implantable medical devices and minimally invasive surgery. It is of great significance for better precision medical treatment.

Abstract Dozens of hyperelastic models have been formulated and have been extremely handy in understanding the complex mechanical behavior of materials that exhibit hyperelastic behavior (characterized by large nonlinear elastic deformations that are completely recoverable) such as elastomers, polymers, and even biological tissues. These models are indispensable in the design of complex engineering components such as engine mounts and structural bearings in the automotive and aerospace industries and vibration isolators and shock absorbers in mechanical systems. Particularly, the problem of vibration control in mechanical system dynamics is extremely important and, therefore, knowledge of accurate hyperelastic models facilitates optimum designs and the development of three‐dimensional finite element system dynamics for studying the large and nonlinear deformation behavior. This review work intends to enhance the knowledge of 15 of the most commonly used hyperelastic models and consequently help design engineers and scientists make informed decisions on the right ones to use. For each of the models, expressions for the strain‐energy function and the Cauchy stress for both arbitrary loading assuming compressibility and each of the three loading modes (uniaxial tension, equibiaxial tension, and pure shear) assuming incompressibility are provided. Furthermore, the stress–strain or stress–stretch plots of the model's predictions in each of the loading modes are compared with that of the classical experimental data of Treloar and the coefficient of determination is utilized as a measure of the model's predictive ability. Lastly, a ranking scheme is proposed based on the model's ability to predict each of the loading modes with minimum deviations and the overall coefficient of determination.

This data article presents four experimental sets of results related to flax fibre composites with epoxy shape memory polymer matrix: water vapor absorption, mass diffusion immersed in water, hygroscopic expansion, mechanical properties. The water vapor absorption tests are described in raw data related to four types of laminates with weights measured at different relative humidity (0%, 9%, 33%, 44%,75%, 85% and 100%). The mass diffusion experiments are related to weights of immersed samples over time. The unidirectional composite hygroscopic expansion is also measured along the fibre longitude and transverse directions. The mechanical properties of flax composite at various temperatures (20°C, 40°C, 60°C, 80°C and 100°C) and humidity environments (50% and immersed) are also described. Load-displacement diagrams of the hygromorph composites are converted into stress-strain diagrams via a compliance calibration, from which the tensile moduli are extracted. The data presented in this article can provide a benchmark for the development of new models, or for the determination of other properties via post processing. The detailed interpretation of the data can be found in [1]. The data is available in the Mendeley Data repository at [2].

Macadamia (Macadamia integrifolia) trees are an important source of revenue in rainforest ecosystems. Their nuts are rich in vitamins, minerals, fiber, antioxidants, and monounsaturated oils. The fungus Lasiodiplodia theobromae, however, is a major disease problem, causing kernel rot and other disease symptoms. In the present study, a dual confrontation assay was used to evaluate the inhibitory effect of an endophytic strain of Trichoderma hamatum C9 from macadamia root against L. theobromae. Volatiles and cell-free culture filtrate of T. hamatum were also used to assess their antifungal activity against L. theobromae. Results suggested that T. hamatum exhibited a significant inhibitory effect against L. theobromae in vitro. Further results of a biocontrol assay indicated that a spray treatment of T. hamatum conidial suspension significantly decreased the size of lesions caused by artificially inoculated L. theobromae on macadamia leaves, as well as the disease index in young trees inoculated with L. theobromae, relative to sterile water controls. Collectively, our findings indicate that T. hamatum C9 represents a potential biocontrol agent that can be used to manage L. theobromae on macadamia.

Shape memory polymers (SMPs) with intelligent deformability have shown great potential in the field of aerospace, and the research on their adaptability to space environments has far-reaching significance. Chemically cross-linked cyanate-based SMPs (SMCR) with excellent resistance to vacuum thermal cycling were obtained by adding polyethylene glycol (PEG) with linear polymer chains to the cyanate cross-linked network. The low reactivity of PEG overcame the shortcomings of high brittleness and poor deformability while endowing cyanate resin with excellent shape memory properties. The SMCR with a glass transition temperature of 205.8 °C exhibited good stability after vacuum thermal cycling. The SMCR maintained a stable morphology and chemical composition after repeated high–low temperature cycle treatments. The SMCR matrix was purified by vacuum thermal cycling, which resulted in an increase in its initial thermal decomposition temperature by 10–17 °C. The continuous vacuum high and low temperature relaxation of the vacuum thermal cycling increased the cross-linking degree of the SMCR, which improved the mechanical properties and thermodynamic properties of SMCR: the tensile strength of SMCR was increased by about 14.5%, the average elastic modulus was greater than 1.83 GPa, and the glass transition temperature increased by 5–10 °C. Furthermore, the shape memory properties of SMCR after vacuum thermal cycling treatment were well maintained due to the stable triazine ring formed by the cross-linking of cyanate resin. This revealed that our developed SMCR had good resistance to vacuum thermal cycling and thus may be a good candidate for aerospace engineering.

3D-printing tough conductive hydrogels (TCHs) with complex structures is still a challenging task due to their inherent contrasting multinetworks, uncontrollable and slow polymerization. Here the authors show an orthogonal photochemistry-assisted printing strategy to make 3D TCHs in one pot.

The demand for stretchable, soft and wearable multifunctional devices based on conductive polymer composites is rapidly growing because of their compelling applications, including physical and physiological measurements on the human body. This paper reports a simple and cost-effective technique to fabricate electrically conductive flexible films with graphite (GRP) flakes and an elastomer, silicone rubber (SR). The mechanical, thermal, electromechanical and electrothermal characterisations of the composites were conducted. While the dynamic electromechanical response of the composites demonstrated their potential applications as wearable sensors, the electrothermal characteristics of the devices showed their suitability to be used as flexible protective circuits and flexible temperature sensors. The synergistic effect of GRP flakes with carbon black (CB) particles was also studied. GRP-SR composites showed a thermal conductivity (TC) of 1.08 W m−1 K−1 and were thermally stable up to up to 300 °C. The good TC and thermal stability along with their deformability, make them suitable to be used as thermal interface devices in arbitrarily shaped surfaces.

Shape memory materials draw much attention due to various promising potential applications. This work prepares a novel shape memory composite via grading photo-thermal curing method, which has not yet been reported. Expectedly, it merges advantages of epoxy-based shape memory polymer (EP) and polyvinyl alcohol-based shape memory polymer (PVA), which has applicable stiffness and multi-stimuli responsive performance. The unsatisfactory mechanical properties of most water-driven shape memory polymer (SMP) is expected to be solved by this fabrication strategy, so that the application range of water-driven SMP could be further extended. The synergistic plasticization of PVA and EP dominates water-driven shape memory behavior of this composite. Interestingly, its water-driven shape memory performance is able to be further improved by immersed in HCl/EtOH solution. The glassy-to-rubbery modulus ratio (E′g/E′r) of the PVA/EP-HCl/EtOH is about 650 after immersed in 0.1 mol/L HCl/EtOH for 6 h. In addition, this immersed method also can solve the post curing problem of such cationic photocuring. It is an easy, efficient, economical strategy for improving synergistic water-driven shape memory performance. Furthermore, this shape memory composite is expected to provide new perspective and practical approach to realize the intellectualization of underwater deployment and release structure.

Shape memory polymers (SMPs) have historically attracted attention for their unique stimulation-responsive and variable stiffness and have made notable progress in aerospace, civil industry, and other fields. In particular, epoxy resin (EP) has great potential due to its excellent mechanical properties, fatigue resistance, and radiation resistance. Herein, we focus on the molecular design and network construction of shape memory epoxy resins (SMEPs) to provide opportunities for performance and functional regulation. Multifunctional and high-performance SMEPs are introduced in detail, including multiple SMEPs, two-way SMEPs, outstanding toughness, and temperature resistance. Finally, emerging applications of SMEPs and their composites in aerospace, four-dimensional printing, and self-healing are demonstrated. Based on this, we point out the challenges ahead and how SMEPs can integrate performance and versatility to meet the needs of technological development.

Stent placement is an effective palliation therapy for malignant colorectal obstruction. However, recurrent obstruction is a common severe complication caused by tumor ingrowth into the stent lumen. Conventional covered stents play a part in preventing the tumor from growing inward but at the expense of significantly increasing the risk of stent migration. Therefore, there is an urgent demand to develop stents with sustained antitumor and antimigration abilities. Herein, we propose a facile method for fabricating multifunctional bioinspired colorectal stents using 3D printing technology. Inspired by high-adhesion biological structures (gecko feet, tree frog toe pads, and octopus suckers) in nature, different types of bioinspired colorectal stents are designed to reduce migration. After functionalization with graphene oxide (GO), bioinspired colorectal stents show excellent and controllable photothermal performance, which is validated by effective ablation of colon cancer cells in vitro and tumors in vivo. Besides, the bioinspired colorectal stents demonstrate the feasibility of transanal placement and opening of the obstructed colon. More importantly, the facile manufacturing process of multifunctional bioinspired colorectal stents is appealing for mass production. Hence, the developed multifunctional bioinspired colorectal stents exhibit a highly promising potential in clinical applications.

The compatibility of polylactic acid (PLA)/polybutylene succinate (PBS) blends was studied by molecular dynamics and mesoscopic dynamics, which is a controversial issue in experiments. Six simulation models of PLA/PBS with different composition ratios (100/0, 90/10, 80/20, 70/30, 60/40, 0/100) were constructed. The radial distribution function, hydrogen bond, free energy density, order parameter and iso-density surface morphology of the PLA/PBS systems were simulated and analyzed. Due to the formation of hydrogen bonds and van der Waals bonds between different elements of PLA chains and PBS chains, the PLA/PBS blends exhibit good compatibility at all composition ratios.

Due to the inherent rigidity of hard materials, the adaptability and flexibility of traditional robots are limited. Recently, soft robots became one of the most attractive areas. The intrinsic compliance and adaptability of soft materials enable soft robots to achieve unexpected functions. Dielectric elastomers (DE) can exhibit large deformation, fast response, and high energy density under the action of external electrical stimuli, becoming one of the most promising materials in soft robots. Herein, the key points of DE actuators (DEAs) are first introduced, including the working principle, DE materials, compliant electrodes, and typical configurations. Then, the soft robots driven by DEAs are reviewed. Some recent highlights are described and discussed in detail. Finally, the main challenges are summarized for the real‐world application of soft robots based on DEAs.

Assume that a frame is given for encoding in a communication system. J. Leng et al. investigated its dual frames for signal decoding which minimize the maximal error when the probabilistic erasures occur in the transmission process. In this paper, we present a new sufficient condition such that the canonical dual is the unique probability optimal dual for erasures. The determination conditions in our results reduces the computational complexity. We also give a necessary and sufficient condition under which a kind of alternative dual frames are probability optimal dual, and study the relation between the optimal duals of equivalent frames. Moreover, we present several examples which show that the general optimal dual frame is not a probability optimal dual frame and compare the reconstruction effects when the general optimal dual frames, the new probability optimal, and the existing probability optimal dual frames are used for decoding.

Abstract Dynamic control of liquid wetting behavior on smart surfaces has attracted considerable concern owing to their important applications in directional motion, confined wetting and selective separation. Despite much progress in this regard, there still remains challenges in dynamic liquid droplet manipulation with fast response, no loss and anti‐contamination. Herein, a strategy to achieve dynamic droplet manipulation and transportation on the electric field adaptive superhydrophobic elastomer surface is demonstrated. The superhydrophobic elastomer surface is fabricated by combining the micro/nanostructured clusters of hydrophobic TiO2 nanoparticles with the elastomer film, on which the micro/nanostructure can be dynamically and reversibly tuned by electric field due to the electric field adaptive deformation of elastomer film. Accordingly, fast and reversible transition of wetting state between Cassie state and Wenzel state and tunable adhesion on the surface via electric field induced morphology transformation can be obtained. Moreover, the motion states of the surface droplets can be controlled dynamically and precisely, such as jumping and pinning, catching and releasing, and controllable liquid transfer without loss and contamination. Thus this work would open the avenue for dynamic liquid manipulation and transportation, and gear up the broad application prospects in liquid transfer, selective separation, anti‐fog, anti‐ice, microfluidics devices, etc.

Abstract 4D printing has attracted academic interest in the recent years because it endows static printed structures with dynamic properties with the change of time. The shapes, functionalities, or properties of the 4D printed objects could alter under various stimuli such as heat, light, electric, and magnetic field. Briefly, 4D printing is the development of 3D printing with the fourth dimension of time. Among the fabrication techniques that have been employed for 4D printing, the direct ink writing technique shows superiority due to its open source for various types of materials. Herein, the state‐of‐the‐art achievements about the topic of 4D printing through direct ink writing are summarized. The types of materials, printing strategies, actuated methods, and their potential applications are discussed in detail. To date, most efforts have been devoted to shape‐shifting materials, including shape memory polymers, hydrogels, and liquid crystal elastomers, showing great prospects in areas ranging from the biomedical field to robotics. Finally, the current challenges and outlook toward 4D printing based on direct ink writing are also pointed out to leave open a significant space for future innovation.

It has been found that the research of a special kind of frames, named K-frames where K is an operator, is significant in theory and application. In this paper, first of all, in theory, we discuss some properties about the existence and structure of the K-frames and the relationship between operator K and K-frames. And these properties provide a method to construct K-frames in the following text. Next, in application, in order to use K-frames to deal with the data erasures of communication, we establish a probability model. Based on this probability model and the above-mentioned properties of K-frames, we construct a probability uniform Parseval K-frame, such that its canonical dual is the unique probability optimal dual when kKf k \ kf k = c and kK+f k \ kf k = a, where both a and c are constants, where K+ is the pseudoinverse for K. We use kf k to represent the norm of f , wheref is any vector in Hilbert space. Moreover, the existence of the probability uniform Parseval K-frame is discussed and then uses it to handle the problem of data erasures. Furthermore, we obtain the conditions for operator K to form the K-frame, which lead to the reduction of restrictions on frame sequences, and make the construction become more flexible compared with traditional frames in coding. Finally, we use three figures obtained by numerical experiments to compare the decoding effects.

Sparsity is one of the key concepts that allows the signal recovery at a significantly lower subsample rate than required by the Nyquist-Shannon sampling theorem. By using a multistate transform, such as wavelets and shearlets system, the sparse representation of signals can be obtained. To further exploit the sparsity of the reconstructed signal, a generalized gradient regularizer is introduced to the proposed model. Motivated by the idea of iterative support detection (ISD), an optimization algorithm framework for image deblurring is given. The algorithm aims to solve a reweighted ℓ0-minimization problem in split Bregman framework, and the weights used for the next iteration are decided by an ISD process. The advantage of this process is that it forms an iterative-feedback mechanism, which improves the effectiveness for solution searching. A series of experiments are presented to demonstrate the availability of the proposed framework. Experimental results show that this method yields significant improvement in peak signal-to-noise ratio when compared to other counterparts. However, the numerical experiments also show that more computing time is required due to the utilization of the redundant multiscale system.

Abstract Probabilistic frames have some properties which are similar to those of frames in Hilbert space. Some equalities and inequalities have been established for traditional frames. In this paper, we give some equalities and inequalities for probabilistic frames. Our results generalize and improve the remarkable results which have been obtained.

The deployable structures based on shape memory polymer composites (SMPCs) have been developed for its unique properties, such as high reliability, low-cost, lightweight, and self-deployment without complex mechanical devices compared with traditional deployable structures. In order to increase the inflatable structure system’s robustness and light the weight of it, a cubic deployable support structure based on SMPC is designed and analyzed preliminarily. The cubic deployable support structure based on SMPC consists of four dependent spatial cages, each spatial cage is composed of 12 three-longeron SMPC truss booms and end connections. The shape recovery of arc-shaped deployable laminates drive the three-longeron SMPC truss booms to unfold, thus realize the expansion of the deployable support structure. The concept and operation of the cubic deployable support structure are described in detail. A series of experiments are performed on the three-longeron deployable laminates unit and the simplified cubic deployable support structure to investigate the shape recovery behavior in the deployment process. Results indicate that the cubic deployable support structure has a high deployment-tgo-stowage volume ratio and can achieve self-deployment, package, and deploy without complex mechanical devices.

Optimal frames have been used in signal processing to minimize the reconstruction errors when erasures occurred during the frame coefficient transmission, and much of the recent work has been focused either on characterizations or on the constructions of optimal frames (or dual frames) prior to signal encoding. In this paper, we propose a new approach, based on the method of optimal directions, which can search adaptively optimal dual frames in the process of signal reconstruction. We provide concrete algorithms for constructing adaptive optimal dual frames and the reconstruction of signals. In addition, several numerical experiments are presented to demonstrate the efficiency and comparison of the new method with the existed methods.

Shape-memory polymers (SMPs) can adjust their stiffness, lock a temporary shape, and recover the permanent shape upon an appropriate stimulus. They are applied in the field of morphing skins. This work presents a variable-stiffness corrugated sheet based on a carbon fiber felt (CFF)-reinforced epoxy-based SMP composite that shows variable stiffness and extreme mechanical anisotropy for potential morphing skin applications. The corrugated sheet exhibits a variable stiffness with a change in temperature, which can help the skin adjust its stiffness according to different service environments. The corrugated sheet can be electrically heated rapidly and homogeneously due to its high electrical conductivity and enhanced heat transfer efficiency. Its Joule-heating effect acts as an effective active stimulation of the variable stiffness and shape-memory effect. The CFF-reinforced epoxy-based SMP composite was manufactured into a corrugated shape to obtain extreme mechanical anisotropy. The corrugated sheet shows a low in-plane stiffness to minimize the actuation energy, while it also possesses high out-of-plane stiffness to transfer the aerodynamic pressure load. Its mechanical properties, electrical heating performance, and shape-memory effect were investigated using experiments. The results show that the proposed SMP composite exhibits extreme mechanical anisotropy, considerable deformation ability, and variable stiffness induced by Joule heating without an external heater.

Since the shape memory effect (SME) has been confirmed in micron and submicron sized polyurethane (PU) shape memory polymer (SMP), it might be used in novel micro/nano devices even for surgery/operation inside a single cell. In this study, micron sized protrusive PU SMP composite chains are fabricated via mixing ferromagnetic nickel micro powders with PU SMP/dimethylformamide solution and then cured under a low magnetic field. Depending on the amount of nickel content, vertical protrusive chains with a diameter from 10 to 250 µm and height from 200 to 1500 µm are obtained. The SME in these chains is investigated to confirm the SME in SMP composites at microscale. An array of such protrusive chains may be utilized to obtain re-configurable surface patterns in a simple manner for applications, such as remarkable change in wetting and friction ability. Finally, its potential applications for micro electro mechanical systems (MEMS) and biomedical device are proposed.

In this paper, an upper bound on the spectral radius ρ ( A ∘ B ) for the Hadamard product of two nonnegative matrices (A and B) and the minimum eigenvalue τ ( C ★ D ) of the Fan product of two M-matrices (C and D) are researched. These bounds complement some corresponding results on the simple type bounds. In addition, a new lower bound on the minimum eigenvalue of the Fan product of several M-matrices is also presented. These results and numerical examples show that the new bounds improve some existing results.

This paper summarizes the research progress of dielectric elastomer (DE) and its composite materials, including the introduction of materials, theoretical research development, and typical applications. First of all, the DE composite materials are introduced. Then, the theoretical research development of DEs is summarized. Finally, some applications as well as research prospects about DEs are listed.

Self-healing composites are able to restore their properties automatically. Impressive healing efficiencies can be achieved when conditions are favourable. On the other hand, healing might not be possible under adverse circumstances such as very low ambient temperature. Here, we report a structural composite able to maintain its temperature to provide a sustainable self-healing capability—similar to that in the natural world where some animals keep a constant body temperature to allow enzymes to stay active. The composite embeds three-dimensional hollow vessels with the purpose of delivering and releasing healing agents, and a porous conductive element to provide heat internally to defrost and promote healing reactions. A healing efficiency over 100% at around −60°C was obtained. The effects of the sheets on the interlaminar and tensile properties have been investigated experimentally. The proposed technique can be implemented in a majority of extrinsic self-healing composites to enable automatic recovery at ultra-low temperatures.

In this paper, we will construct a new multilevel system in the Fourier domain using the harmonic wavelet. The main advantages of harmonic wavelet are that its frequency spectrum is confined exactly to an octave band, and its simple definition just as Haar wavelet. The constructed multilevel system has the circular shape, which forms a partition of the frequency domain by shifting and scaling the basic wavelet functions. To possess the circular shape, a new type of sampling grid, the circular-polar grid (CPG), is defined and also the corresponding modified Fourier transform. The CPG consists of equal space along rays, where different rays are equally angled. The main difference between the classic polar grid and CPG is the even sampling on polar coordinates. Another obvious difference is that the modified Fourier transform has a circular shape in the frequency domain while the polar transform has a square shape. The proposed sampling grid and the new defined Fourier transform constitute a completely Fourier transform system, more importantly, the harmonic wavelet based multilevel system defined on the proposed sampling grid is more suitable for the distribution of general images in the Fourier domain.

On a global scale many countries are still heavily dependent on crude oil to produce energy and fuel for transport, with a resulting increase of atmospheric pollution. A possible solution to obviate this problem is to find eco-sustainable energy sources. A potential choice could be the use of biodiesel as fuel. The work presented aims to characterise the transesterification reaction of waste peanut frying oil using colour analysis and wavelet analysis. The biodiesel production, with the complete absence of mucilages, was evaluated through a suitable set of energy wavelet coefficients and scalograms. The physical characteristics of the biodiesel are influenced by mucilages. In particular the viscosity, that is a fundamental parameter for the correct use of the biodiesel, might be compromised. The presence of contaminants in the samples can often be missed by visual analysis. The low and high frequency wavelet analysis, by investigating the energy change of wavelet coefficient, provided a valid characterisation of the quality of the samples, related to the absence of mucilages, which is consistent with the experimental results. The proposed method of this work represents a preliminary analysis, before the subsequent chemical physical analysis, that can be develop during the production phases of the biodiesel in order to optimise the process, avoiding the presence of impurities in suspension in the final product.

We first investigate the construction of a fusion frame system in a finite-dimensional Hilbert space 𝔽n when its fusion frame operator matrix is given and provides a corresponding algorithm. The matrix representations of its local frame operators and inverse frame operators are naturally obtained. We then study the related properties of the constructed fusion frame systems. Finally, we implement the construction of fusion frame systems which behave optimally for erasures in some special sense in signal transmission.

The experimental data transmission is an important part of high energy physics experiment. In this paper, we connect fusion frames with the experimental data transmission implement of high energy physics. And we research the utilization of fusion frames for data transmission coding which can enhance the transmission efficiency, robust against erasures, and so forth. For this application, we first characterize a class of alternate fusion frames which are duals of a given fusion frame in a Hilbert space. Then, we obtain the matrix representation of the fusion frame operator of a given fusion frame system in a finite-dimensional Hilbert space. By using the matrix representation, we provide an algorithm for constructing the dual fusion frame system with its local dual frames which can be used as data transmission coder in the high energy physics experiments. Finally, we present a simulation example of data coding to show the practicability and validity of our results.