Explore the vast range of titles available.

In this article, a first of its kind blend of polyvinyl chloride (PVC) and biocompatible polycaprolactone (PCL) is introduced by melt mixing and then 3D printed successfully via Fused Filament Fabrication (FFF). Experimental tests are carried out on PCL‐PVC blends to assess thermo‐mechanical behaviors, morphology, fracture toughness, shape‐memory effects and printability. Macro and microscopic tests reveal that PVC‐PCL compounds are miscible due to high molecular compatibility and strong interaction. This causes extraordinary mechanical properties specially for PVC‐10 wt% PCL. In addition to the desired tensile strength (45 MPa), this material has a completely rubbery behavior at ambient temperature, and its total elongation is more than 81%. In addition, due to the high formability of PVC‐PCL at ambient temperature, it has capability of being programed via different shape‐memory protocols. Programming tests show that PVC‐PCL blends have an excellent shape‐memory effect and result in 100% shape recovery. SEM results prove a high improvement of PVC printability with the addition of 10 wt% PCL. Toughened PVC by PCL is herein added to the materials library of FFF 3D printers and expected to revolutionize applications of PVC compounds in the field of biomedical 3D and 4D printing due to its appropriate thermo‐mechanical properties, supreme printability, and excellent biocompatibility.

Shape memory polymers (SMPs) are smart materials capable of changing their shapes in a predefined manner under a proper applied stimulus and have gained considerable interest in several application fields. Particularly, two-way and multiple-way SMPs offer unique opportunities to realize untethered soft robots with programmable morphology and/or properties, repeatable actuation, and advanced multi-functionalities. This review presents the recent progress of soft robots based on two-way and multiple-way thermo-responsive SMPs. All the building blocks important for the design of such robots, i.e., the base materials, manufacturing processes, working mechanisms, and modeling and simulation tools, are covered. Moreover, examples of real-world applications of soft robots and related actuators, challenges, and future directions are discussed.

In this study, a Ni 44.8 Ti 45.2 Hf 5 Cu 5 shape memory alloy was fabricated by vacuum arc-melting in a copper mold. The alloy was solution annealed at 1000 °C for 60 min and subsequently aged at a temperature range between 300 °C and 600 °C for different time intervals from 10 to 240 min. The alloy underwent a B2 ↔ B19′ one-stage martensitic transformation. The results showed that martensitic transformation temperatures increased with increasing aging temperature from 300 to 600 °C. Increasing transformation temperatures with aging temperature is considered to be due to the suppression of Ti 2 Ni-type precipitates at higher aging temperatures. Constant stress thermal cycling experiments were carried out under a tensile stress of 200 MPa. The results indicated that aging treatment at a proper temperature could improve the recoverable strain in the alloy. The solution-annealed Ni 44.8 Cu 5 Ti 45.2 Hf 5 alloy showed a recoverable strain of 6%, while after aging at 300 °C for 60 min, a recoverable strain as high as 8% was obtained under 200 MPa. On the other hand, the irrecoverable strain in the alloy was not affected by aging treatment and remained almost constant at close to 1% for all conditions. Furthermore, two-way shape memory effect in Ni 44.8 Ti 45.2 Hf 5 Cu 5 alloy was developed by tensile deformation of martensite with a training strain of 3%. After solution annealing, the alloy exhibited a two-way shape-memory strain of 1.8%. With increasing aging temperature, the two-way shape memory strain increases until it reaches a maximum value of 2.2% at 400 °C and then decreases with further increasing the aging temperature.

—A geometrically nonlinear description of the operation of a multiple-action force actuator, which consists of a shape memory alloy working body and a linear displacement body, is performed. The relative error that appears when this problem is solved in a geometrically linear formulation is shown to increase with phase-structural strain of the working body, and it can exceed 20% for some parameters.

In the present work, a new strategy for preparing authentic two-way shape memory polymer was proposed by using a conventional crosslinked polyurethane (PU) containing crystalline poly(s-caprolactone) (PCL) as the proof-ofconcept material. Lauroyl peroxide (LPO) was added as a chemical crosslinker for inducing secondary crosslinking during the programming. Having been stretched and heat treated without additional ingredients and chemicals, the trained PU showed the desired two-way shape memory effect. The crosslinking network created by LPO was successfully converted into internal stress supplier, which represents the core progress of this research. As the temperature changed, the reversible melting/re-crystallization of the crystalline phases elaborately cooperated with the compressed crosslinking network, leading to the implementation of two-way shape memory effect. Through the optimization of the LPO quality, an average reversible strain of up to ~21% in the direction of stretching was measured. In principle, all semi-crystalline polymers can be imparted with two-way shape memory effect following the above-proposed method. Given the great convenience of material selection, preparation, programming and application, the current research may have opened a new way for the production and usage of the smart materials in practice.

Soft porous organic crystals with stimuli‐responsive single‐crystal‐to‐single‐crystal (SCSC) transformations are important tools for unraveling their structural transformations at the molecular level, which is of crucial importance for the rapid development of stimuli‐responsive systems. Carefully balancing the crystallinity and flexibility of materials is the prerequisite to construct advanced organic crystals with SCSC, which remains challenging. Herein, a squaraine‐based soft porous organic crystal (SPOC‐SQ) with multiple gas‐induced SCSC transformations and temperature‐regulated gate‐opening adsorption of various C1‐C3 hydrocarbons is reported. SPOC‐SQ is featured with both crystallinity and flexibility, which enable pertaining the single crystallinity of the purely organic framework during accommodating gas molecules and directly unveiling gas‐framework interplays by SCXRD technique. Thanks to the excellent softness of SPOC‐SQ crystals, multiple metastable single crystals are obtained after gas removals, which demonstrates a molecular‐scale shape‐memory effect. Benefiting from the single crystallinity, the molecule‐level structural evolutions of the SPOC‐SQ crystal framework during gas departure are uncovered. With the unique temperature‐dependent gate‐opening structural transformations, SPOC‐SQ exhibits distinctly different absorption behaviors towards C3H6 and C3H8, and highly efficient and selective separation of C3H6/C3H8 (v/v, 50/50) is achieved at 273 K. Such advanced soft porous organic crystals are of both theoretical values and practical implications. By balancing the crystallinity and flexibility, multiple gases‐induced single‐crystal‐to‐single‐crystal (SCSC) transformations of a novel soft porous organic crystal (SPOC) are discovered for not only elucidation of gas‐framework interplays and molecular‐scale shape‐memory effect at molecular level but also highly selective separation of propylene/propane, demonstrating the crucial significance of stimuli‐responsive SCSC transformations in guiding development of stimuli‐responsive systems.

Shape memory materials have been playing an important role in a wide range of bioengineering applications. At the same time, recent developments of graphene-based nanostructures, such as nanoribbons, have demonstrated that, due to the unique properties of graphene, they can manifest superior electronic, thermal, mechanical, and optical characteristics ideally suited for their potential usage for the next generation of diagnostic devices, drug delivery systems, and other biomedical applications. One of the most intriguing parts of these new developments lies in the fact that certain types of such graphene nanoribbons can exhibit shape memory effects. In this paper, we apply machine learning tools to build an interatomic potential from DFT calculations for highly ordered graphene oxide nanoribbons, a material that had demonstrated shape memory effects with a recovery strain up to 14.5% for 2D layers. The graphene oxide layer can shrink to a metastable phase with lower constant lattice through the application of an electric field, and returns to the initial phase through an external mechanical force. The deformation leads to an electronic rearrangement and induces magnetization around the oxygen atoms. DFT calculations show no magnetization for sufficiently narrow nanoribbons, while the machine learning model can predict the suppression of the metastable phase for the same narrower nanoribbons. We can improve the prediction accuracy by analyzing only the evolution of the metastable phase, where no magnetization is found according to DFT calculations. The model developed here allows also us to study the evolution of the phases for wider nanoribbons, that would be computationally inaccessible through a pure DFT approach. Moreover, we extend our analysis to realistic systems that include vacancies and boron or nitrogen impurities at the oxygen atomic positions. Finally, we provide a brief overview of the current and potential applications of the materials exhibiting shape memory effects in bioengineering and biomedical fields, focusing on data-driven approaches with machine learning interatomic potentials.

This study investigated the effect of stress-induced martensite aging under tensile and compressive stresses on the functional and viscoelastic properties in Ni50.3Ti32.2Hf17.5 polycrystals containing dispersed H-phase particles up to 70 nm in size obtained by preliminary austenite aging at 873 K for 3 h. It was found that stress-induced martensite aging at 428 K for 12 h results in the appearance of a two-way shape memory effect of −0.5% in compression and +1.8% in tension. Moreover, a significant change in viscoelastic properties can be observed: an increase in internal friction (by 25%) and a change in elastic modulus in tensile samples. The increase in internal friction during martensitic transformation after stress-induced martensite aging is associated with the oriented growth of thermal-induced martensite. After stress-induced martensite aging, the elastic modulus of martensite (EM) increased by 8 GPa, and the elastic modulus of austenite (EA) decreased by 8 GPa. It was shown that stress-induced martensite aging strongly affects the functional and viscoelastic properties of material and can be used to control them.

Admired for their extraordinary stimuli-sensitive behavior and shape-changing capabilities, shape-memory polymers (SMPs) and multifunctional composites are among the most important smart materials. They continue to be widely applied in many diverse fields to create things such as self-deployable spacecraft structures, morphing structures, SMP foams, smart textiles, and intelligent medical devices. Written by renowned authors, this book is a broad overview of the systematic progress associated with this emerging class of materials. The book presents an overview of SMPs and a detailed discussion of their structural, thermo-mechanical, and electrical properties, and their applications in fields including aeronautics, astronautics, biomedicine, and the automotive industry. Covering topics ranging from synthesis procedures to ultimate applications, this is a sound instructional text that serves as a guide to smart materials and offers an in-depth exploration of multifunctional SMPs and SMP composites, outlining their important role in the materials field. In each chapter, industry experts discuss different key aspects of novel smart materials, from their properties and fabrication to the actuation approaches used to trigger shape recovery. This comprehensive analysis explores the different functions of SMPs, the fundamentals behind them, and the ways in which polymers may reshape product design in general.

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.