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Multifunctional polyurethane shape memory polymers (PU-SMPs) have been of increasing interest in various applications. Here we report structure characterization, detailed methodology, and obtained results on the identification of functional properties of a thermoset PU-SMP (MP4510) with glass transition temperature of 45 °C. The stable, chemically crosslinked network of this thermoset PU-SMP results in excellent shape memory behavior. Moreover, the proximity of the activation temperature range of this smart polymer to room and body temperature enables the PU-SMP to be used in more critical industrial applications, namely fast-response actuators. The thermomechanical behavior of a shape memory polymer determines the engineering applications of the material. Therefore, investigation of the shape memory behavior of this class of commercial PU-SMP is of particular importance. The conducted structural characterization confirms its shape memory properties. The shape fixity and shape recovery properties were determined by a modified experimental approach, considering the polymer’s sensitivity to external conditions, i.e., the temperature and humidity variations. Three thermomechanical cycles were considered and the methodology used is described in detail. The obtained shape fixity ratio of the PU-SMP was approximately 98% and did not change significantly in the subsequent cycles of the thermomechanical loading due to the stability of chemical crosslinks in the thermoset materials structure. The shape recovery was found to be approximately 90% in the first cycle and reached a value higher than 99% in the third cycle. The results confirm the effect of the thermomechanical training on the improvement of the PU-SMP shape recovery after the first thermomechanical cycle as well as the effect of thermoset material stability on the repeatability of the shape memory parameters quantities.

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.

To change the situation of shape memory polymers (SMPs) that can only remember very few shapes and enable discretional morphing for practical application, the authors report a reversible stepless multiple SMP derived from ultrahigh molecular weight polyethylene (UHMWPE). As the crystals of semi‐crystalline polymers are assembled by those with slightly different melting temperatures, and each type of crystal can remember a single shape, the crystalline region of UHMWPE is allowed to remember plenty of temporary shapes after programming. Changing the temperature of the programmed polymer within the melting/crystallization temperature ranges would lead to releasing/recovery of the memorized temporary shapes. Accordingly, multiple shape memory effects can be easily realized without an elaborate design of material structure and training process in advance as before. The temperature‐dependent adjustability of the analog capacitor and soft lens with embedded programmed UHMWPE as actuators, characterized by the continuous/random/proportional responsivity, further reveals the utilization prospects of the controllable reversible stepless discretionary morphing effect. Moreover, the maximum work density of the programmed UHMWPE is found to be 210 kJ/m3, which is more than 10 times of piezoelectric ceramics, so that it can serve as a proof‐of‐concept mechanical driver for reversibly pumping of ethanediol‐droplet upon heating/cooling. Reversible stepless discretionary morphing polymer is produced by simply training commercial ultrahigh molecular weight polyethylene (UHMWPE) via thermal treatment associated stretching. The key issue is that the crystals of UHMWPE memorize lots of temporary shapes as independent switching phases. A discretionary number of shape memory effects can be easily realized by changing the temperature of the programmed polymer within the melting/crystallization temperature ranges.

Polymer smart materials are a broad class of polymeric materials that can change their shapes, mechanical responses, light transmissions, controlled releases, and other functional properties under external stimuli. A good understanding of the aspects controlling various types of shape memory phenomena in shape memory polymers (SMPs), such as polymer structure, stimulus effect and many others, is not only important for the preparation of new SMPs with improved performance, but is also useful for the optimization of the current ones to expand their application field. In the present era, simple understanding of the activation mechanisms, the polymer structure, the effect of the modification of the polymer structure on the activation process using fillers or solvents to develop new reliable SMPs with improved properties, long lifetime, fast response, and the ability to apply them under hard conditions in any environment, is considered to be an important topic. Moreover, good understanding of the activation mechanism of the two-way shape memory effect in SMPs for semi-crystalline polymers and liquid crystalline elastomers is the main key required for future investigations. In this article, the principles of the three basic types of external stimuli (heat, chemicals, light) and their key parameters that affect the efficiency of the SMPs are reviewed in addition to several prospective applications.

Shape-memory polymers (SMPs) show great potential in various emerging applications, such as artificial muscles, soft actuators, and biomedical devices, owing to their unique shape recovery-induced contraction force. However, the factors influencing this force remain unclear. Herein, we designed a simple polymer blending system using a series of tetra-branched poly(ε-caprolactone)-based SMPs with long and short branch-chain lengths that demonstrate decreased crystallinity and increased crosslinking density gradients. The resultant polymer blends possessed mechanical properties manipulable across a wide range in accordance with the crystallinity gradient, such as stretchability (50.5–1419.5%) and toughness (0.62–130.4 MJ m−3), while maintaining excellent shape-memory properties. The experimental results show that crosslinking density affected the shape recovery force, which correlates to the SMPs’ energy storage capacity. Such a polymer blending system could provide new insights on how crystallinity and crosslinking density affect macroscopic thermal and mechanical properties as well as the shape recovery force of SMP networks, improving design capability for future applications.

Although several force application concepts are known that can be used to deform shape memory polymers (SMPs) within the scope of programming, controlled deformation is challenging in the case of samples with a cylinder-like shape, which need to be homogeneously compressed starting from the lateral surface. To solve this problem, this contribution follows a material approach that takes advantage of four-dimensional (4D) printing. Fused filament fabrication (FFF) was used as an additive manufacturing (AM) technique to produce a thermoresponsive tool in a cylindrical shape from a polyether urethane (PEU) having a glass transition temperature (Tg) close to 55 °C, as determined by differential scanning calorimetry (DSC). Once it was 4D-printed, a sample of laser cut polyester urethane urea (PEUU) foam with a cylindrical wall was placed inside of it. Subsequent heating to 75 °C and keeping that temperature constant for 15 min resulted in the compression of the foam, because the internal stresses of the PEU were transferred to the PEUU, whose soft segments were completely molten at 65 °C as verified by DSC. Upon cooling to −15 °C and thus below the offset temperature of the soft segment crystallization transition of the PEUU, the foam was fixed in its new shape. After 900 days of storage at temperatures close to 23 °C, the foam recovered its original shape upon reheating to 75 °C. In another experiment, a 4D-printed cylinder was put into hibernation for 900 days before its thermoresponsiveness was investigated. In the future, 4D-printed tools may be produced in many geometries, which fit well to the shapes of the SMPs to be programmed. Beyond programming SMP foams, transferring the forces released by 4D-printed tools to other programmable materials can further expand technical possibilities.

The use of bio-based materials in the production of shape memory polymer composite materials (SMPCs) has attracted intense interest from researchers in recent years. In this study, bio-based SMPCs production was aimed with utilizing shape memory polymer containing alkaline lignin was used as matrix phase and hemp/cotton fiber was used as reinforcement element. In order to shed light on their potential for usage as an alternative to synthetic SMPCs, the properties of hemp/fiber reinforced versus glass fiber reinforced SMPCs’ comparison was made. The analysis results revealed that among all the samples produced, the alkaline pretreated hemp/cotton fiber reinforced SMPCs that produced at 100 °C (Sample 4) has the closest thermomechanical, morphological and shape memory properties to the glass fiber reinforced SMPCs that produced at 100 °C (control sample). The results from DSC and DMA analysis demonstrated that the hemp cotton fiber reinforced SMPCs (Sample 4) have a Tg temperature of 99 °C and a storage modulus of 2375 MPa, while the control sample has a Tg temperature of 108 °C and a storage modulus of 7360 MPa. TGA analysis showed that glass fiber reinforced SMPCs had the highest thermal strength among all samples, with a maximum thermal decomposition temperature of 380 °C and the highest coal residue (52%). The key findings from the shape recovery test results are that all samples have a shape stability rate of 97–99%. The control sample has a shape recovery ratio of 98.07% and a shape recovery rate of 0.0227, while Sample 4 showed that the shape recovery ratio of 93.14% and the shape recovery rate of 0.0106 that have the closest properties to the control sample. When all the results were examined, it was concluded that SMPCs produced using alkaline pre-treated hemp/cotton fiber and 1-layer carbon fiber reinforcement have promising properties to have a place in the remotely controllable smart materials that can be activated by temperature.

Shape-Memory Polymers (SMPs) are considered a kind of smart material able to modify size, shape, stiffness and strain in response to different external (heat, electric and magnetic field, water or light) stimuli including the physiologic ones such as pH, body temperature and ions concentration. The ability of SMPs is to memorize their original shape before triggered exposure and after deformation, in the absence of the stimulus, and to recover their original shape without any help. SMPs nanofibers (SMPNs) have been increasingly investigated for biomedical applications due to nanofiber’s favorable properties such as high surface area per volume unit, high porosity, small diameter, low density, desirable fiber orientation and nanoarchitecture mimicking native Extra Cellular Matrix (ECM). This review focuses on the main properties of SMPs, their classification and shape-memory effects. Moreover, advantages in the use of SMPNs and different biomedical application fields are reported and discussed.

In most macroscale robotic systems, propulsion and controls are enabled through a physical tether or complex onboard electronics and batteries. A tether simplifies the design process but limits the range of motion of the robot, while onboard controls and power supplies are heavy and complicate the design process. Here, we present a simple design principle for an untethered, soft swimming robot with preprogrammed, directional propulsion without a battery or onboard electronics. Locomotion is achieved by using actuators that harness the large displacements of bistable elements triggered by surrounding temperature changes. Powered by shape memory polymer (SMP) muscles, the bistable elements in turn actuate the robot’s fins. Our robots are fabricated using a commercially available 3D printer in a single print. As a proof of concept, we show the ability to program a vessel, which can autonomously deliver a cargo and navigate back to the deployment point.

Soft actuator materials change their shape or size in response to stimuli like electricity, heat, light, chemical or pH. These actuator materials are compliant and well suited for soft mechatronics and robots. This paper introduces the definition of soft materials and the position of soft actuator materials in comparison with conventional actuators and other solid state actuator materials. A thorough review of selected soft actuator materials is carried out, including responsive gels/hydrogels, ionic polymer metal composites, conducting polymers, carbon nanotubues/graphenes, dielectric elastomers, shape memory polymers and biopolymers. This review will give insights for applications of soft actuator materials via better understanding of the materials in terms of their preparation, performance and limitation.