Shape Memory Polymer Research Articles

Prototyping sutureless shape memory valve stent via integrated 3D printing

Abstract Transcatheter aortic valve replacement (TAVR) has increasingly emerged as a forefront option for treating aortic valve diseases. However, the currently prevalent valve prostheses used in TAVR typically involve stitching biologic leaflets onto metallic stents, which introduces challenges in the durability of leaflets and the biocompatibility of metallic stents. This work proposes an integrated additive manufacturing method for prototyping sutureless prosthetic aortic valves that combine shape memory polymer (SMP) stents and hydrogel valve leaflets. The SMP stent exhibits sufficient toughness to maintain structural integrity upon shape memory programming, while the Fe3+-treated hydrogel leaflets possess sufficient swelling resistance to ensure dimensional stability. Finally, the proof-of-concept valve stent is successfully fabricated by integrated 3D printing and validated via an in vitro hemodynamic experiment. Overall, our approach holds promise for prototyping sutureless polymeric valve stents for future generations.

Programable shape recovery properties and snap-through instabilities of viscoelastic and shape-memory NS metamaterials

The combination of smart material and mechanical metamaterial has the potential to bring novel properties and additional functionalities, which, however, has been ignored for a long time. This work numerically, experimentally, and analytically examines the negative stiffness (NS) metamaterials based on shape memory polymers (SMPs) with a focus on the tunable and temperature-dependent properties induced by the interaction of material and geometry nonlinearity. A universal discrete model of a series of shape-memory NS metamaterial is developed by separating the bending effect and stretching effect, where the viscoelastic material is described by the generalized Maxwell-Wiechert model, and an SMP constitutive model is proposed based on multiplicative decomposition of the deformation gradient. The mechanical and shape-memory properties influenced by temperature, geometry, material and loading rate are experimentally observed through relaxation tests and cyclic compression tests. Then the discrete model and finite element analysis (FEA) is adopted to examine the novel mechanical responses in a wide range of parameters. Results show that viscoelasticity and loading rate play a significant role in mechanical responses, and tunable load-capacity and stability can be achieved for shape-memory metamaterial. A phase diagram of different stabilities is constructed showing strictly monotonic, S-shaped, and snapping responses. Additionally, repeated compression and recovery performance proves the possibility of reusable applications. This work provides new opportunities for functional metamaterial to obtain programmable shape recovery and mechanical responses.

Flexible and durable shape memory EVA/MXene/EVA fiber membrane for programmable EMI shielding

Flexible and lightweight electromagnetic interference (EMI) shielding materials are currently the focus of electromagnetic protection material research. By applying shape memory polymers to the field of electromagnetic shielding, intelligent electromagnetic shielding composites with programmable shielding performance can be prepared. In this study, a flexible EVA/MXene/EVA electromagnetic shielding composite membrane with programmable shielding effectiveness was prepared using electrospinning, vacuum filtration, and hot pressing techniques. Even with a low MXene content, the EMI shielding effectiveness in the X-band still achieved 40.5 dB, and the specific EMI shielding effectiveness was as high as 6.23 × 103 dB cm2 g−1. The composite membrane exhibited excellent shape memory performance, with a shape fixation rate (Rf) of 93.8 % and a shape recovery rate (Rr) of 92.1 %, achieving a programmable shielding effectiveness of 14.1–40.5 dB under 0–30 % tensile strain. Additionally, the composite membrane could serve as a switch for electromagnetic shielding, controlling the reception and shielding of electromagnetic waves. Simultaneously, the composite membrane exhibits excellent hydrophobicity, electrothermal conversion capability, and durability. Importantly, it retains almost the same shielding effectiveness even after undergoing 500 cycles of bending and folding, as well as prolonged exposure to strong acids and alkalis. This work not only offers new insights into the development of multifunctional and intelligent electromagnetic shielding composites suitable for harsh environments but also expands the application scope of shape memory smart materials.

Rubber-assisted and modulated epoxy topological network for developing fatigue-resistant, high-strain-cycle high performance shape memory polymer composites

High performance shape memory polymer (HPSMP) has a wide range of application such as smart device, smart mold. In this study, we designed a rigid-flexible shape memory epoxy with flexible chain segment as the main chain and rigid benzene ring as the side group. Meanwhile, carboxyl-terminated nitrile butadiene rubber (CTBN) was accessed into the epoxy main chain as a fatigue-resistant functional filler. The results showed that the flexible backbone plays a major role in improving the ductility. The superior fatigue-resistant shape memory cycling performance was synergistically achieved by modulating the epoxy topological network through altering the disulfide cross-linker prompted by CTBN, and the materials exhibited good high and low-temperature resistant mechanical properties. Comparatively, it is found that disulfide bonding can significantly improve the tensile property and thermal stability for epoxy. The synergistic effect between the elastic chain segments in CTBN and the flexible backbone achieves excellent shape recovery ratio. Therefore, the rational structural design provides an effective way to develop HPSMP, which can expand the application areas for HPSMP.

A wide angle X-ray diffraction (WAXD) study of thermal and chemical actuation of a shape memory polymer

A wide angle X-ray diffraction (WAXD) study of thermal and chemical actuation of a shape memory polymer

Designing a Self-Healing Shape Memory Polymer with High Stiffness and Toughness: The Role of Nonuniform Chain Networks

Designing a Self-Healing Shape Memory Polymer with High Stiffness and Toughness: The Role of Nonuniform Chain Networks

CFD investigations of a shape-memory polymer foam-based endovascular embolization device for the treatment of intracranial aneurysms.

The hemodynamic and convective heat transfer effects of a patient-specific endovascular therapeutic agent based on shape-memory polymer foam (SMPf) are evaluated using computational fluid dynamics studies for six patient-specific aneurysm geometries. The SMPf device is modeled as a continuous porous medium with full expansion for the flow studies and with various degrees of expansion for the heat transfer studies. The flow simulation parameters were qualitatively validated based on the existing literature. Further, a mesh independence study was conducted to verify an optimal cell size and reduce the computational costs. For convective heat transfer, a worst-case scenario is evaluated where the minimum volumetric flow rate is applied alongside the zero-flux boundary conditions. In the flow simulations, we found a reduction of the average intra-aneurysmal flow of > 85% and a reduction of the maximum intra-aneurysmal flow of > 45% for all presented geometries. These findings were compared with the literature on numerical simulations of hemodynamic and heat transfer of SMPf devices. The results obtained from this study provide a novel and practical framework for optimizing the design of patient-specific SMPf devices, integrating advanced computational models of hemodynamics and heat transfer. This framework could guide the future development of personalized endovascular embolization solutions for intracranial aneurysms with improved therapeutic outcome.

A soft, ultra-tough and multifunctional artificial muscle for volumetric muscle loss treatment

Abstract The escalating prevalence of skeletal muscle disorders highlights the critical need for innovative treatments for severe injuries like volumetric muscle loss. Traditional treatments, such as autologous transplants, are constrained by limited availability and current scaffolds often fail to meet complex clinical needs. This study introduces a new approach to VML treatment using a shape memory polymer (SMP) based on block copolymers of perfluoropolyether and polycaprolactone diol. This SMP mimics the biomechanical properties of natural muscle, exhibiting a low elastic modulus (2–6 MPa), high tensile strength (72.67 ± 3.19 MPa), exceptional toughness (742.02 ± 23.98 MJ m−3), and superior biocompatibility, thereby enhancing skeletal muscle tissue integration and regeneration within 4 weeks. Moreover, the polymer's shape memory behavior and ability to lift over 5000 times its weight showcase significant potential in both severe muscle disorder treatment and prosthetic applications, surpassing existing scaffold technologies. This advancement marks a pivotal step in the development of artificial muscles for clinical use.

A highly visible-transparent thermochromic smart window with broadband infrared modulation for all-season energy savings

Abstract Thermochromic smart windows effectively reduce the energy consumption for building through passive light modulation including the transmission of visible (TVis), near-infrared (TNIR), and the emissivity of mid-infrared (εMIR) in response to the ambient temperature change. However, thermochromic windows that maintain high TVis while modulating TNIR and εMIR simultaneously are highly desirable but still challenging. Here, we develop a thermochromic smart window based on a two-way shape memory polymer to enable reversible transformation and achieve TNIR modulation of 44.0% and εMIR modulation of 76.5% while maintaining high TVis (>50%). Compared to traditional windows based on silica glass, this device shows 4°C lower temperature in summer daytime, 2°C higher in winter daytime, and 1°C higher in spring nighttime. It is expected that our device can achieve greater annual energy savings in comparison with commercial glass anywhere in the world and promote the progress of thermochromic windows for energy-efficient buildings.

Regulation of Glass Transition Temperature in Thermo‐Responsive Epoxy Shape Memory Polymers: The Roles of Chemical Crosslinking Density and Chain Flexibility

ABSTRACTShape memory polymers (SMPs) are novel kinds of smart materials whose shape can be changed in external conditions such as heat stimulus. Due to their excellent structural versatility and high elastic strain, they have important applications in the field of biomaterials. Here, a series of amorphous shape memory polymer materials are prepared and their shape memory properties and glass transition temperature (Tg) are also investigated. A special kind of epoxy polymer, whose shape can be changed at around physiological temperature, is synthesized by regulating the crosslinking density and introducing flexible aliphatic epoxy chains. The shape memory function of this epoxy polymer is studied by deformation test. In addition, to explore their application in the field of biomedical materials, the biocompatibility of the materials are evaluated, including the effects on the erythrocyte hemolysis rate and cell activity. The experimental results show that this kind of epoxy polymer has good shape memory function and biocompatibility.

4D printing of smart scaffolds for bone regeneration: a systematic review.


As a novel emerging technology, four-dimensional (4D) printing allows 3D-printed materials to change over time. This systematic review is conducted to evaluate the purpose, materials, physiomechanical, and biological properties of 4D-printed scaffolds used for bone tissue engineering.
Method and materials:
An electronic search was conducted following the PRISMA 2020 guidelines in PubMed, Scopus, Web of Science, and Google Scholar online databases limited to English articles until April 2024. Studies in which scaffolds were fabricated through 3D printing methods responding to external stimulation were included. The quality of in vitro and in vivo studies was evaluated through the modified CONSORT checklist and SYRCLE's risk of bias tool.
Results:
The full text of 57 studies were reviewed, and 15 studies met the inclusion criteria. According to the analyzed studies, most scaffolds responded to temperature changes showing shape memory effect. Polyurethane (PU) and poly(lactic acid) (PLA) were the most common shape memory polymers, and the most common fabrication method used was Fused Deposition Modeling (FDM).
Conclusion:
A comprehensive systematic review of the studies from the past 10 years demonstrated several findings: 1) Shape memory, drug delivery, and shape morphing are three general purposes of 4D printing for bone regeneration. 2) Smart materials used for 4D printing mostly consist of shape memory polymers. 3) Temperature changes account for the majority of stimulation used for 4D printing. 4) incorporating 4D printing principles does not have a negative impact on the physiomechanical properties of the designed scaffold. 5) The 4D-printed scaffolds show a higher osteogenic differentiation capacity than their identical 3D-printed structures in terms of bone regeneration.&#xD.

A 1D micromechanics-based constitutive model for the thermoviscoelastic behavior of crosslinked semicrystalline shape memory polymers: numerical simulation and experimental validation

Abstract The paper develops a 1D thermoviscoelastic constitutive model for the crystallization- and melting-induced one-way and two-way shape memory effects, as well as isothermal yielding behaviors, of crosslinked semi-crystalline polymers. A micromolecular chain model is proposed to characterize the transition between the amorphous and crystalline phases. Structural equations including a modified Eying model that combine phase transition and viscoelasticity equations are employed to predict the shape memory effects. An extensive experimental campaign has been carried out on poly (ethylene-co-vinyl acetate) based semi-crystalline elastomers to characterize the thermoviscoelastic temperature-stress-strain relations of the material under different loading and rate conditions. Some results guide the determination of the model parameters, while the rest validate the model capabilities. Comparisons with the experimental results show that the model can well reproduce the stress-strain-temperature responses, providing valuable insights for application development.

Integrating Photothermal-Responsive Shape Memory and Self-Healing Polymers in 4D-Printed Thermally Comfortable Smart Wearables

Integrating Photothermal-Responsive Shape Memory and Self-Healing Polymers in 4D-Printed Thermally Comfortable Smart Wearables

Harnessing nanostructures and fiber architecture: A synergistic leap in shape memory polymer composites

This research investigates the synergistic effects of carbon fiber orientation and nanostructure reinforcement across 21 configurations of shape memory polymer composites. It examines uni-directional (UD), bi-directional Twill (BDT), and bi-directional Plain (BDP) fiber architectures, along with varying concentrations of MWCNT and GnP at 0.4%, 0.6%, and 0.8%. The fabrication process involves initially preparing nanostructure-modified epoxy nanocomposites through ultrasonication followed by hand layup techniques to fabricate three-phase shape memory polymer composites. Optimal tensile performance is observed in GnP-modified UD composites at a 0.6 wt% concentration, achieving a tensile strength of 728.32 MPa and a modulus of 71.29 GPa. Furthermore, enhancements in thermomechanical and shape memory properties are noted in GnP-modified BDT composites and are further improved in GnP-modified BDP composite configurations. GnP-modified composites outperform MWCNT ones due to GnP’s sheet structure aligning parallel to the load and its larger surface area, which facilitate enhanced interaction with the matrix. These improvements, supported by FESEM analysis, highlight enhanced interfacial bonding and result in high shape recovery ratios, with all configurations exceeding 90%, despite polymer modification.

4D Printing of High-Performance Shape Memory Polymer with Double Covalent Adaptive Networks

Achieving 4D printing of shape memory polymers with both high strength and high transition temperature remains challenging due to the inherent incompatibility between the rigid molecular structure required for high strength and the molecular structure that moves on demand necessary for the shape memory effect, the limitations of high-performance polymer reaction kinetics, as well as internal stress during the printing process. Here, a direct ink writing (DIW) printed high-precision cyanate ester-urethane (CU) shape memory polymer with excellent performance was accomplished by incorporating two dynamic covalent bonds (carbamate and cyanuric acid) through copolymerizing cyanate ester with polyurethane acrylates. During curing, carbamate and cyanuric acid enable stress relaxation and polymer network rearrangement, facilitating the permanent reconfiguration of CU to form a novel triazine network structure. As a result, a high mechanical properties CU with excellent strength (83 MPa) and superior Young's modulus (2.37GPa) were obtained, besides, the transition temperature (near 250 oC) is the highest in comparison to currently reported 4D-printed shape memory polymers. Furthermore, this reconfigurability was demonstrated by imprinting various surface patterns at microscopic level. Moreover, the reconfigurability of CU provides a novel strategy for smart molds in deformation and easy demolding. Overall, this study opens up a new avenue for the development of high-performance 4D printed shape memory polymers.

The new additive era of orthodontics: 3D-printed aligners and shape memory polymers—the latest trend—and their environmental implications

The era of printed aligners has just began in the orthodontic field. Orthodontists have become more interested in 3D-printed in-office aligners. Treatment due to this technology can become faster and more efficient. Advantages highlighted by newly introduced materials for manufacturing processes of 3D aligners present the possibility of overcoming limitations faced by thermoformed aligners, making them a potential replacement of thermoformed aligner. Advances in aligner material, especially shape memory polymers, have the potential to bring about radical transformations in the clinical applications of clear aligner therapy. Safety and cytotoxicity of printable resins along with its mechanical properties must be scientifically studied extensively before it is cleared for clinical use. In addition, with the increased use of aligners, awareness of the environmental burden of plastic waste should be emphasized. Attention should be directed into the development of recyclable materials for aligners along with establishing clear recycling guidelines and patient education programs on proper recycling methods. With the introduction of Graphy’s clear biocompatible photocurable resin, which is equipped with a shape–memory function and is printed in an environmental friendly way by reducing carbon emissions. Direct 3D printing represents the future of clear aligner therapy, and more studies to test these new technologies and materials are required.

A 3D Nerve Guidance Conduit Surface With a Wrinkled Protein Coating Toward Peripheral Nerve Injury Repair

ABSTRACTPeripheral nerve injuries (PNIs) resulting in myelin breakdown and axonal degeneration at both the proximal and distal nerve stumps are major clinical concerns that can induce functional loss and diminished quality of life. In biomaterials science, considerable attention has been given to artificial nerve guidance conduits (NGCs), since the engineered tubular structures have the potential to supply a supportive nerve microenvironment to longitudinally align the regenerating axons for bridging the injured nerve sites. Although NGCs may become promising alternatives to nerve autografts, the fabrication approaches available to incorporate directional cues for dictating neuronal behavior and nerve reconnection have been limited to conventional micro/nano‐fabrication techniques that are complex and time‐consuming due to manual processing steps. Thus, our goal here was to develop a simple manufacturing approach for introducing topographical cues onto NGCs. To achieve this goal, we used an established mechanically actuated silk wrinkling approach to create topographically functionalized surfaces as a potential NGC material platform for guided directional alignment of neurons. We 3D‐printed thermo‐responsive shape‐memory polymer (SMP)‐based NGCs that can produce silk fibroin (SF)‐wrinkled topographies on the micro and nano‐meter length scale. Since SF is a commonly used biomaterial surface coating with excellent neuro‐compatibility, we studied the ability to develop NGCs that can autonomously actuate silk wrinkles upon heat‐induced contraction of the SMP and evaluated the effects of the topographically functionalized construct on neuronal behavior. Using an immortalized dorsal root ganglion neuronal cell line, we found that the silk‐wrinkled conduits displayed high neuronal viability and adhesion compared to uncoated conduits and tissue‐culture polystyrene controls. We also found that the wrinkled conduits enabled the neurons to elongate and align parallel to the direction of the wrinkled topography. Longer neurite extension was also observed on the wrinkled conduits compared to their respective controls. These findings demonstrate the potential for functional wrinkled protein coatings to provide directional cues in the fabrication of artificial NGCs for peripheral nerve repair.

A Systematic Study on Biobased Epoxy-Alcohol Networks: Highlighting the Advantage of Step-Growth Polyaddition over Chain-Growth Cationic Photopolymerization.

Vanillyl alcohol has emerged as a widely used building block for the development of biobased monomers. More specifically, the cationic (photo-)polymerization of the respective diglycidyl ether (DGEVA) is known to produce materials of outstanding thermomechanical performance. Generally, chain transfer agents (CTAs) are of interest in cationic resins not only because they lead to more homogeneous polymer networks but also because they strikingly improve the polymerization speed. Herein, the aim is to compare the cationic chain-growth photopolymerization with the thermally initiated anionic step-growth polymerization, with and without the addition of CTAs. Indeed, CTAs lead to faster polymerization reactions as well as the formation of more homogeneous networks, especially in the case of the thermal anionic step-growth polymerization. Resulting from curing above the TG of the respective anionic step-growth polymer, materials with outstanding tensile toughness (>5MJ cm-3) are obtained that result in the manufacture of potential shape-memory polymers.

Tendon‐Driven Stiffness‐Tunable Soft Actuator via Thermoelectric‐based Bidirectional Temperature Control

AbstractSoft robots have excellent spatial adaptability and high flexibility, but they are limited by the low stiffness of their constituent materials when faced with high‐load tasks. In recent years, there have been many works on the development of stiffness‐tunable soft actuators by introducing variable stiffness materials into soft actuators, but the existing solutions usually suffer from the problems of slow response, complex structure, and the need of many auxiliary devices to support the completion of the stiffness tuning cycle. This paper proposes a tendon‐driven stiffness‐tunable soft actuator that addresses these issues. Benefiting from the bidirectional temperature control of thermoelectric modules and the excellent in‐plane thermal conductivity of graphene, the actuator is capable of achieving the heating and cooling process by transferring the heat flow through the graphene structure into and out of the shape‐memory polymer (SMP) layer of the tendon‐driven actuator. This enables stiffness tuning via a single device, reducing the dependence on complex external cooling systems. The use of tendon‐driven actuators further eliminates the complex bellow structure of conventional pneumatic actuators and dramatically reduces the size and manufacturing difficulty of individual actuators. Finally, the high load capacity and shape adaptability of the actuator are demonstrated by a gripper equipped with three actuators, which successfully grips objects of various shapes and weights, ranging from less than 10 g to up to 1.6 kg.

Model-based design of a mechanically intelligent shape-morphing structure

Soft robotics has significant interest within the industrial applications due to its advantages in flexibility and adaptability. Nevertheless, its potential is challenged by low stiffness and limited deformability, particularly in large-scale application scenarios such as underwater and offshore engineering. The integration of smart materials and morphing structures presents a promising avenue for enhancing the capabilities of soft robotic systems, especially in large deformation and variations in stiffness. In this study, we propose a multiple smart materials based mechanically intelligent structure devised through a model-based design framework. Specifically, the intelligent structure incorporates smart hydrogel and shape memory polymer (SMP). Employing the finite element method (FEM), we simulated the complex interactions among smart material to analyze the performance characteristics of the intelligent structure. The results demonstrate that, utilizing smart hydrogel and shape memory polymer (SMP) can effectively attain large deformation and exhibit variable stiffness due to the shape memory effect. Besides, the shape-morphing structures exhibit customized behaviours including bending, curling, and elongation, all while reducing reliance on external power sources. In conclusion, utilizing multiple smart materials within the model-based design framework offers an efficient approach for developing mechanically intelligent structure capable of complex deformations and variable stiffness, thereby providing support for underwater or offshore engineering applications.