Shape Fixity Ratio Research Articles

Development and 4D printing of magneto-responsive PMMA/TPU/Fe3O4 nanocomposites with superior shape memory and toughness properties

This paper introduces 4D printing of composites of polymethyl methacrylate (PMMA) and thermoplastic polyurethane (TPU) reinforced with Fe3O4 particles for the first time. PMMA/TPU blends with 70/30 wt% are selected as matrix with the best compatibility based on dynamic mechanical thermal analysis. Fe3O4 nanoparticles are added to the blends with 10 %, 15 % and 20 % weight ratios. Their addition enables remote actuation of the materials in a high frequency alternating magnetic field. Field emission scanning microscopic images confirms a full dispersion of nanoparticles inside the polymeric matrix. Nanocomposites with 20 wt% of Fe3O4 can perfectly recover the permanent shape within 1.5 min in the magnetic field. They also reveal perfect shape memory properties in the hot water. Moreover, all samples display a perfect shape fixity ratio. The addition of TPU significantly enhances the toughness and flexibility of the PMMA matrix. It is found that Fe3O4 nanoparticles further enhance the mechanical strength by 10 % to 15 %, although they reduce the strain at break from 17 % to 14 %. Finally, a gripper is 4D printed and its excellent performance in the magnetic field is demonstrated.

3D-Printed Shape Memory and Piezoelectric Bifunctional Thermoplastic Polyurethane/Polyvinylidene Fluoride Porous Composite Scaffold for Bone Regeneration.

Physical stimulations such as mechanical and electric stimulation can continuously work on bone defect locations to maintain and enhance cell activity, and it has become a hotspot for research in the field of bone repair. Herein, bifunctional porous composite scaffolds with shape memory and piezoelectric functions were fabricated using thermoplastic polyurethane (TPU) and poly(vinylidene fluoride) through triply periodic minimal surfaces design and selective laser sintering technology. Thereinto, the shape fixity ratio and recovery ratio of the composite scaffold reached 98.6% and 81.2%, respectively, showing excellent shape memory functions. More importantly, its piezoelectric coefficient (d33 = 2.47 pC/N) is close to the piezoelectric constant of bone tissue (d33 = 0.7-2.3 pC/N), and the voltage released during the compression process can reach 0.5 V. Furthermore, cyclic compression experiments showed that the strength of composite scaffold was up to 8.3 times compared with the TPU scaffold. Besides, the composite scaffold showed excellent cytocompatibility. In conclusion, the composite scaffold is expected to continuously generate mechanical and electric stimulation due to shape memory and piezoelectric function, respectively, which provide an effective strategy for bone repair.

Shape memory and shape recovery characterization of thermoplastic urethane

ABSTRACT Polyurethane shape memory polymer, as a smart material, has been becoming more and more popular due to its greater multifunctionality in various industrial and biomedical applications. Here, the authors reported the characterization, and comprehensive methodology and acquired the results of thermoplastic urethane (SMTPU) as a shape memory polymer, with 35°C as the glass transition temperature, by examining its creep. This smart polymer exhibits excellent shape memory behaviour due to its steady, chemically cross-linked network. Such behaviour of shape memory polymer determines its usability in various functional applications. Furthermore, the activation temperature range of SMPTPU is close to body temperature and room temperature as well, so it can be employed in more demanding industrial applications. Thus, it becomes essential to investigate the shape-changing/memory behaviour of commercial SMTPU. A quantitative analysis was done to determine the effects of programming temperature, maximum uniaxial strain, and compressive strain on shape memory characteristics viz. the shape recovery ratios and shape fixity ratios. Along with the excellent shape memory effect, this material also exhibits high creep and elasticity at room temperature, indicating that it may be used for various industrial and biomedical applications.

Effect of atomic oxygen and vacuum thermal aging on graphene and glass fibre reinforced cyanate ester-based shape memory polymer composite for deployable thin wall structures

Deployable components and structures are a crucial part of space exploration. Due to fewer parts, low weight and cost, shape memory polymers (SMPs) and their composites (SMPCs) are considered ideal candidates for this. However, lower thermal stability and poor durability in the space environment have limited their applicability. This research work details the development of Graphene Nanoplatelets (GNP) filled Glass Fibre (GF) reinforced cyanate ester-based SMPC with 0/90° and ±45° sandwich fibre lay-up configuration capable of multidirectional shape programming. The SMP matrix was synthesised by mixing Cyanate Ester and Polyethylene Glycol (PEG) with added GNP. SMPC was fabricated by pouring the SMP mixture into a pre-prepared glass mould with the added GF layers. The synthesised SMPC showed shape programming and recovery at 169.01 ± 0.62 °C and stable thermomechanical properties at the temperature of 130 °C. Durability tests at extreme environmental conditions including Atomic Oxygen exposure, thermal vacuum aging, and elevated-temperature behaviour tests were conducted as these tests evaluate the durability and applicability of the SMPC for use in Earth's orbits and lunar environments. The performances of the samples before and after durability tests were measured through mechanical tests, shape memory effect tests and a series of characterisation methods such as microscopic image analysis, FTIR and dynamic mechanical analysis. According to the results, AO exposure affected the SMPCs by eroding their surface. There were no changes in the chemical structure of the SMPC yet the thermomechanical, mechanical and shape memory properties were decreased without compromising their safe operational levels such as storage onset temperatures (128.79 ± 3.08 °C), maximum tensile stress (114.99 ± 21.52 MPa), shape fixity (100 %) and recovery ratios (100 %). The erosion resistance of the GNP-filled SMPCs was improved with ∼54.35 % less erosion than the SMPC without GNP. The vacuum thermal aging slightly slowed shape recovery from 31.17 % to 8.32 % at 160 °C due to PEG crosslink degradation, however, 100 % shape recovery was achieved at the end. Further durability tests under cryogenic temperatures and effects after vacuum thermal cycles are warranted to observe the synergistic effect on the SMPC for future developments. Exploring the scalability and additive manufacturability of the developed SMPC can be advantageous in the future while mitigating challenges such as complex shape programming, long-term materials degradation, resource efficiency and compliance with safety standards.

Self-Healable, Transparent, Biodegradable, and Shape Memorable Polyurethanes Derived from Carbon Dioxide-Based Diols.

A series of CO2-based thermoplastic polyurethanes (TPUs) were prepared using CO2-based poly(polycarbonate) diol (PPCDL), 4,4'-methylenebis (cyclohexyl isocyanate) (HMDI), and polypropylene glycol (PPG and 1,4-butanediol (BDO) as the raw materials. The mechanical, thermal, optical, and barrier properties shape memory behaviors, while biocompatibility and degradation behaviors of the CO2-based TPUs are also systematically investigated. All the synthesized TPUs are highly transparent amorphous polymers, with one glass transition temperature at ~15-45 °C varying with hard segment content and soft segment composition. When PPG is incorporated into the soft segments, the resultant TPUs exhibit excellent self-healing and shape memory performances with the average shape fixity ratio and shape recovery ratio as high as 98.9% and 88.3%, respectively. Furthermore, the CO2-based TPUs also show superior water vapor permeability resistance, good biocompatibility, and good biodegradation properties, demonstrating their pretty competitive potential in the polyurethane industry applications.

Shape memory and mechanical properties of ESO modified epoxy/polyurethane semi-interpenetrating polymer networks for smart plaster

While numerous studies have explored the potential of shape memory materials in medical applications, the current research output is not enough for significant productivity in industrial products. In this research, a type of shape memory orthopedic plaster was fabricated by using epoxy/polyurethane interpenetrating networks modified with epoxidized soybean oil (ESO) and then compared with some commercial plasters. Polymer networks that were produced could be tailored to have glass transition temperatures (Tgs) within the range of 70–90 °C by changing the percentage composition of polyurethane and soybean oil. Shape recovery and fixity ratios in all samples were above 95 and 97 %. DMA results showed that IPNs with variable amount of soybean oil had lower glass transition temperature (Tg) and cross-link densities compared to IPNs without soybean oil. Based on the tensile test results, most samples exhibited an elastic modulus in the range of 280–400MPa, a level deemed somewhat acceptable when compared to commercial samples. Light microscope images had shown that the increase of polyurethane led to the phase separation of polymers, which was improved by the addition of soybean oil.

2D material-enhanced multi-fold self-sensing and programmable deployable lattice structure

The development of intelligent and programmable smart composite structure that can remember and restore their original shape after being extensively deformed is highly sought after for a wide variety of applications, such as deployable and morphing structures, soft robots, and smart infrastructure. Despite recent advancements, there remains a plethora of unexplored possibilities in the field of deployable structures utilizing shape programmable and intelligent composite materials. The aim of this research is to manufacture a deployable structure that is intelligent enough to monitor the deployment and programmable to be deployed in specific way. Here, a smart deployable auxetic structure is reported that not only possesses thermal and piezoresistive sensing properties but also acts as a thermally activated intelligent shape memory polymer composite (iSMPC). We have fabricated an intelligent fabric and embedded it as reinforcement within a polyurethane-based shape memory polymer matrix to make an intelligent auxetic (A-iSMPC) structure. It has been demonstrated that the intelligent fabric enhances the overall mechanical properties of the auxetic structure and allows monitoring the temperature variation and strain changes during shape programming and recovery. The A-iSMPC offered a negative Poisson’s ratio of − 0.44, shape recovery ratio of 96%, shape fixity ratio of 88% and compaction ratio of 62%. With its shape memory, auxetic, thermal and piezoresistive sensing capabilities, this iSMPC has the potential to be a multifunctional and multipurpose structure for a variety of applications.

Influence of Infill Patterns on the Shape Memory Effect of Cold-Programmed Additively Manufactured PLA.

In four-dimensional additive manufacturing (4DAM), specific external stimuli are applied in conjunction with additive manufacturing technologies. This combination allows the development of tailored stimuli-responsive properties in various materials, structures, or components. For shape-changing functionalities, the programming step plays a crucial role in recovery after exposure to a stimulus. Furthermore, precise tuning of the 4DAM process parameters is essential to achieve shape-change specifications. Within this context, this study investigated how the structural arrangement of infill patterns (criss-cross and concentric) affects the shape memory effect (SME) of compression cold-programmed PLA under a thermal stimulus. The stress-strain curves reveal a higher yield stress for the criss-cross infill pattern. Interestingly, the shape recovery ratio shows a similar trend across both patterns at different displacements with shallower slopes compared to a higher shape fixity ratio. This suggests that the infill pattern primarily affects the mechanical strength (yield stress) and not the recovery. Finally, the recovery force increases proportionally with displacement. These findings suggest a consistent SME under the explored interval (15-45% compression) despite the infill pattern; however, the variations in the mechanical properties shown by the stress-strain curves appear more pronounced, particularly the yield stress.

Enhanced shape memory performance and numerical simulation of knitted‐fabric reinforced polymer composites with weft yarns

AbstractFabric‐reinforced shape memory polymeric composites (SMPC) have shown great potential in the design of intelligent deformation structures. In this work, the weft‐knitted fabric inserted with weft yarns was developed as reinforcement to fabricate the shape memory epoxy polymer (SMEP) composites. The effects of weft yarn, loop density and direction on the shape memory performance of SMPC under different bending radii were experimentally investigated. The results show that the SMPC have good shape fixity ratios and shape recovery ratios of around 98%. As compared with those of SMPCs without inserting weft yarns, the SMPCs with weft yarns have shorter shape recovery time, and the recovery force of SMPCs with weft yarns in the 0° and 90° directions shows an increase of 86.4% and 79.5%, respectively. The recovery force of SMPC improve 3.7 times compared to SMEP. The multiscale models of SMPC were established with basis of the results of micro‐computed tomography scanning of specimens and viscoelastic theory. The surface buckling behaviors of SMEP and SMPC specimens after U‐bending load were discussed. Finally, the deformation of loops and weft yarns of SMPC were analyzed to reveal the shape memory mechanism.Highlights Shape memory polymeric composites (SMPC) with weft yarns has shorter shape recovery time. Recovery force of SMPC with weft yarns was obvious enhanced. Multi‐scale viscoelastic models of SMPC were established. Surface buckling behaviors of SMPC after U‐bending load were revealed.

Biobased photothermal responsive shape memory polythioether/MXene nanocomposites with self-extinguishing performance

Thermosetting shape memory polymers (TS-SMPs) have a higher shape fixity ratio (Rf) and shape recovery (Rr) due to their structure integrity and thermal stability, and the glass transition temperature (Tg) usually influences the transition temperature (Ttrans) of TS-SMPs. Therefore, it is significant to tailor the Tg range and mechanical properties for TS-SMPs. In this work, the inherently flame-retarding bio-based MXene-reinforced polythioether nanocomposites with excellent shape memory performance, driven by photothermal response, were designed. Firstly, a photopolymerizable MXene nanomonomer (MPS-MXene) was obtained by introducing 3-(methacryloxy) propyltrimethoxysilane onto the surface of the MXene monolayer. Then, the bis(4-allyl-2-methoxyphenyl) phenyl phosphonate (BEP) was synthesized by eugenol (a lignin derivative) with phenyl phosphonic dichloride. The polythioether/MXene composites (BEP-T-xM) were synthesized through in-situ thiol-ene photopolymerization of MPS-MXene, BEP, and tris[2-(3-mercaptopropionyloxy)ethyl]isocyanurate. Surprisingly, compared with neat polythioether, the Tg of BEP-T-0.2 M composite increased from 19.6 to 34.6 °C, when only 0.2 wt% MPS-MXene was added. The photothermal conversion efficiency (η = 73.8 %) and shape memory performance with Rr (>98 %) were greatly improved. Consequently, the interesting phenomena such as “sunflowers growing towards the sunlight” and “thermal shrinkage” can be observed. Meanwhile, the tensile strength and Young’s modulus increased significantly by 141 % and 91 %, respectively, due to the good dispersion of rigid MPS-MXene nanosheets. Furthermore, all the polythioether/MXene composites showed self-extinguishing performance. This study will provide a novel strategy for designing biobased photothermal-responsive TS-SMPs.

Enhancing Tensile Modulus of Polyurethane-Based Shape Memory Polymers for Wound Closure Applications through the Addition of Palm Oil.

Thermo-responsive, biocompatible polyurethane (PU) with shape memory properties is highly desirable for biomedical applications. An innovative approach to producing wound closure strips using shape memory polymers (SMPs) is of significant interest. In this work, PU composed of polycaprolactone (PCL) and 1,4-butanediol (BDO) was synthesized using two-step polymerization. Palm oil (PO) was added to PU for enhancing the Young's modulus of the PU beyond the set criterion of 130 MPa. It was found that PU had the ability to crystallize at room temperature and the segments of individual PCL and BDO polyurethanes crystallized separately. The crystalline domains and hard segment of PU greatly affected the tensile properties. The reduction of crystalline domains by the addition of PO and deformation at the higher melting temperature of the crystalline PCL polyurethane phase improved the shape fixity and shape recovery ratios. The new irreversible phase, raised from the permanent deformation upon stretching at the between melting temperature of the crystalline PCL and BDO polyurethanes of 70 °C, resulted in a decrease in shape fixity ratio after the first thermomechanical stretching-recovering cycles. The demonstration of PU as a wound closure strip showed its efficiency and potential until the surgical wound healed.

Bending shape memory properties and multi-scale viscoelastic behaviors of knitted-fabric reinforced polymer composites

Knitted fabrics with easily deformable loop structure have the potential in the development of shape memory polymeric composites with large recovery deformations. The knitted fabric reinforced shape memory epoxy polymer composites (SMPC) were prepared in this work. The effects of loop densities, orientations and bending radii on shape memory properties of SMPC were investigated. The shape fixity ratio and shape recovery ratio of SMPC subjected to U-shaped bending radius of 5 mm are above 98 %. The shape recovery force of SMPC can reach up to 5.9 N. The thermodynamic properties of SMP were also characterized to obtain mechanical parameters and a user-defined material subroutine (UMAT) of shape memory epoxy polymer (SMEP) was written. Based on viscoelastic theory and the multi-scale geometrical structures, the macroscopic homogeneous thermodynamic model and mesoscopic thermodynamic model of knitted fabric reinforced SMPC were established to study the macro-scale stress distribution and meso-scale deformation evolution during shape memory process, respectively. The neutral surface position of SMPC during bending deformation is offset inner. The unique anisotropic loop structure of knitted fabric determines the shape memory behavior of the SMPC. Finally, micro-CT characterizations of knitted fabric reinforced SMPC were conducted to further understand the loop deformation mechanism during shape memory process. This study will provide important theoretical and technical support for large deformation structure design and deformation prediction of smart composites.

Photopolymerization-based 4D-printing of shape-memory materials containing high-performance polymers

High-performance aromatic heterochain polymers are engineering thermoplastics with exceptional mechanical and thermal properties that have attracted great interest in various areas ranging from aerospace to biomedicine. However, there have been a number of difficulties to 3D-print materials based on such polymers with new promising performance characteristics. Herein, a number of new photosensitive compositions (PSCs) based on high-performance polyetherimide (PEI) or polysulfone (PSU), reactive functional monomer (N,N-dimethylacrylamide) and oligomer (bisphenol A ethoxylate diacrylate) has been developed. It has been shown that the use of the developed PSCs allows the formation of 3D-structures with high printing resolution by LCD 3D-printing. Subsequent thermal post-curing of 3D-printed green-state samples at 250°С for 1 h led to the fabrication of materials with the highest tensile strength (up to 41.9 ± 3.1 MPa), glass transition temperature (141 °C) and thermal stability (above 350 °C). In addition, 3D-printed structures demonstrate high-temperature shape memory effect with shape fixity ratio > 99% and shape recovery ratio up to 97.1%.

Analysing the shape memory behaviour of GnP-enhanced nanocomposites: a comparative study between experimental and finite element analysis

Shape memory polymers (SMPs) are capable of enduring significant deformations and returning to their original form upon activation by certain external stimuli. However, their restricted mechanical and thermal capabilities have limited their broader application in engineering fields. To address this, the integration of graphene nanoplatelets (GnPs) with SMPs has proven effective in enhancing their mechanical and thermal properties while maintaining inherent shape memory functions. The study evaluated shape memory nanocomposites (SMNCs) using dynamic mechanical, thermogravimetric, and static tensile, flexural, and shape memory tests, along with scanning electron microscopy to analyse tensile fractures. The results indicate that the optimal content of GnP is 0.6 wt%, resulting in excellent shape memory, thermal, and mechanical properties. Specifically, this composition demonstrates a shape recovery ratio of 94.02%, a storage modulus of 4580.07 MPa, a tensile strength of 61.42 MPa, and a flexural strength of 116.37 MPa. Additionally, the incorporation of GnPs into epoxy reduces recovery times by up to 52% at the 0.6 wt% concentration. While there is a slight decrease in the shape fixity ratio from 98.77% to 93.02%, the shape recoverability remains consistently high across all samples. Current finite element (FE) models often necessitate complex, problem-specific user subroutines, which can impede the straightforward application of research findings in real-world settings. To address this, the current study introduces an innovative finite element simulation method using the widely used ABAQUS software to model the thermomechanical behaviour of SMNCs, importantly incorporating the time-dependent viscoelastic behaviour of the material. The effectiveness of this new approach was tested by comparing experimental results from bending test of SMNCs cantilever beam with outcomes derived from FE simulations. The strong agreement between the experimental data and simulation results confirmed the precision and reliability of this novel technique.

Effect of dual dispersion of carbon fiber and silica nanoparticles on recovery performance of shape memory epoxy

Shape memory polymers are utilized in diverse fields, including deployable structures and components, owing to their advantageous properties like low density, cost-effectiveness, and ease of processing. The current study investigates the effect of dual dispersion of carbon fibers (CF) and silica nanoparticles (SN) on the recovery performance of shape memory epoxy composites. CF (0.25 wt.%) reinforced epoxy composite, SN (0.25 wt.%) reinforced epoxy composite, and dual (CF and SN 0.25 wt.% each) dispersed epoxy composite were developed using magnetic stirring and ultrasonic mixing to study the mechanical properties and shape memory behaviour. Flexural strength, tensile strength and fracture toughness of pristine epoxy was found to be 134.38, 52.15 MPa and 1.91 MPa∙m1/2, respectively. The addition of CF resulted in a flexural strength of 135.70 MPa and a tensile strength of 53.01 MPa, while the incorporation of SN led to a flexural and tensile strength of 138.40 and 53.69 MPa, respectively. The fracture toughness of composites after adding CF and SN was found to be 2.22 and 2.39 MPa∙m1/2, respectively. With dual dispersion, the flexural strength of 139.82 MPa, tensile strength of 54.64 MPa, and fracture toughness of 2.75 MPa∙m1/2 were achieved. Dual dispersion has shown improved mechanical properties compared to single dispersion. The introduction of CF slightly decreased the shape fixity ratio (Rf ) and shape recovery ratio (Rr ) of the pristine epoxy from 98.67% and 96.62% to 96.67% and 95.15%, respectively. Similarly, the addition of SN further reduced these ratios to 98.00% and 91.83%, respectively. With a dual dispersion approach Rf and Rr were observed to be about 97.33% and 93.83%, respectively. The addition of fillers led to a reduction in Rf and Rr due to inhibition of polymeric chains, resulting in partial shape recovery. However, recovery time improved from 28 to 23 and 26 s with addition of CF and SN, respectively, in epoxy. With dual dispersion, a speedy recovery was achieved with a recovery time of 21 s. The findings of this study demonstrate the potential of dual dispersed fillers to improve the mechanical and shape memory properties of epoxy, which could find applications in the smart materials and structural engineering.

Photothermal-responsive lignin-based polyurethane with mechanically robust, fast self-healing, solid-state plasticity and shape-memory performance

In light of the depletion of petrochemical resources and increase in environmental pollution, there has been a significant focus on utilizing natural biomass, specifically lignin, to develop sustainable and functional materials. This research presents the development of a lignin-based polyurethane (DLPU) with photothermal-responsiveness by incorporating lignin and oxime-carbamate bonds into polyurethane network. The abundant hydrogen bonds between lignin and the polyurethane matrix, along with its cross-linked structure, contribute to DLPU's excellent mechanical strength (30.2 MPa) and toughness (118.7 MJ·m−3). Moreover, the excellent photothermal conversion ability of DLPU (54.4 %) activates dynamic reversible behavior of oxime-carbamate bonds and hydrogen bonds, thereby endowing DLPU with exceptional self-healing performance. After 15 min of near-infrared irradiation, DLPU achieves self-healing efficiencies of 96.0 % for tensile strength and 96.3 % for elongation at break. Additionally, DLPU exhibits photocontrolled solid-state plasticity as well as an excellent phototriggered shape-memory effect (70 s), with shape fixity and recovery ratios reaching 98.8 % and 95.3 %, respectively. By exploiting the spatial controllability and photothermal-responsiveness of DLPU, we demonstrate multi-dimensional responsive materials with self-healing and shape-shifting properties. This work not only promotes the development of multi-functional polyurethanes but also provides a pathway for the high-value utilization of lignin.

Analysing the shape memory behaviour of MWCNT-enhanced nanocomposites: a comparative study between experimental and finite element analysis

Shape memory polymers (SMPs) are known for their unique ability to withstand large deformations and revert to their original shape under specific external stimuli. However, their broader application in biomedical and structural applications is restricted by limited mechanical and thermal properties. Introducing multi-walled carbon nanotubes (MWCNTs) into SMPs has proven to significantly enhance these characteristics without affecting their inherent shape memory features. This study investigates shape memory nanocomposites (SMNCs) through dynamic and thermogravimetric analyses, along with tensile, flexural, and shape memory testing, and explores fracture interfaces using scanning electron microscopy. Findings indicate optimal shape memory, thermal, and mechanical properties with 0.6 wt% MWCNT content, showcasing a shape recovery ratio of 93.11%, storage modulus of 4127.63 MPa, tensile strength of 55 MPa, and flexural strength of 107.94 MPa. Moreover, incorporating MWCNTs into epoxy demonstrated a reduction in recovery times by up to 50% at 0.6 wt% concentration. Despite a slight decrease in shape fixity ratio from 98.77% to 92.11%, shape recoverability remained nearly consistent across all samples. The study also introduces a novel finite element (FE) method in ABAQUS for modeling the thermomechanical behavior of SMNCs, incorporating viscoelasticity, validated by matching experimental results with FE simulations, highlighting its accuracy and practical applicability in engineering.

Harnessing leather waste in polymer matrix for sustainable smart shape‐stable phase change materials

AbstractThe utilization of leather waste (LW) in a polyurethane (PU) matrix makes a smart and novel shape stable phase change material (SSPCM). This is essential for sustainability as it reduces landfill waste after use. The PU is synthesized in bulk with a 90% yield, using biodegradable polycaprolactone diol and bio‐based polyol (castor oil), along with tolylene‐2,4‐diisocyanate. PL and PLG composites are prepared by blending of constituent components PU (P), LW (L), and poly(glycidyl methacrylate) (PGMA, G), as specified by their code names. Role of LW (hydrogen bonding and chemical crosslinking) and morphology are elucidated by FTIR and SEM, respectively. Self‐healing time (2 h), shape fixity ratios (Rf) (PL: 60–80% and PLG: 60–70%) and shape recovery ratios (Rr) (100% for both) are determined at 60°C. PLG displays faster shape recovery in water (<30 s) compared to air (>300 s). Shape stability and thermal properties of the SSPCM are examined using the temperature responsive leakage study, TGA, and DSC. This research introduces a new approach for using leather waste (LW) in SSPCM, with self‐healing and 100% Rr. This material may find application where SSPCM with high durability and flexibility is essential such as textile and footwear materials.

4D printing of lattice structures to test their behavior by repetitive shape processing cycles

This study thoroughly investigated the shape memory effects of 4D printed lattice structures influenced by repetitive shape processing cycles and materials variability. The structures were fabricated by an amorphous and semicrystalline type shape memory material (SMP) and subjected to time-temperature-based thermomechanical memory cycles. Shape programming and recovery characteristics for 4D printing were done inside an environmental chamber at a loading rate of 2 mm. min−1. The shape memory effects driven by SMP’s viscoelastic behavior and performance factors were studied by stress-free strain recovery experiments upon the interaction of thermal stimuli. The stress-free strain recovery analysis expressed, that the influence of repetitive cycles was exceptional and significant for both materials. Extensive investigation on shape memory reactive strain components (i.e., programming strain, residual strain, and thermal strain) reflected, with the increasing number of cycles, the shape recovery ratios of the first to fourth cycles increased from 82 → 100% of amorphous and 79 → 95% of semicrystalline SMP and then tend to stable thereafter. Contrarily, the shape fixity ratios of semicrystalline structures have shown a decreased tendency during the consecutive cycles from 100 → 80%. The successful execution of data-oriented shape processing cycles enhanced the potential of SMP-based lattice structures for their monotonous applications as intelligent devices. The time and temperature-dependent shape memory characteristics of repetitive cycles presented in this study are advantageous to model the viscoelastic behavior of such artful structures.

A dynamic trap well model of hydrothermal shape-memory effect in amorphous polymers undergoing tailorable shape recovery behaviour

A dynamic trap well model is developed to describe the complex relaxations of functional segments, and explore the working principles behind the hydrothermal coupling effect in shape memory polymers (SMPs). A constitutive relationship among shape fixity strain, shape recovery strain and relaxation time has been formulated to characterize the hydrothermal coupling effect using geometrical parameters (i.e. width and height) of trap wells. Moreover, effects of temperature and solvent absorption on dynamic relaxation behaviours of SMPs have been formulated based on the Flory-Huggins theory and Fokker-Plank probability equation. The trap well model effectively analyzes the shape fixity ratio and shape recovery ratio within ranges of 50–100% and 0–100%, respectively. Finally, an extended Maxwell model is proposed to formulate the dynamic mechanical behaviours of SMPs with hydrothermal shape-memory effect (SME), and the analytical results have been verified using the experimental results reported in literature. A good agreement between the analytical results obtained from the proposed model and the experimental data is present, where the correlation coefficient ( R 2 ) is 95%. The present study firstly introduces the dynamic trap well model for shape memory behaviours and intricate relaxations, and then accurately predicts the dynamic shape recovery of SMP in response to hydrothermal stimulus.