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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 recent years, four-dimensional (4D) fabrication has emerged as a powerful technology capable of revolutionizing the field of tissue engineering. This technology represents a shift in perspective from traditional tissue engineering approaches, which generally rely on static—or passive—structures (e.g., scaffolds, constructs) unable of adapting to changes in biological environments. In contrast, 4D fabrication offers the unprecedented possibility of fabricating complex designs with spatiotemporal control over structure and function in response to environment stimuli, thus mimicking biological processes. In this review, an overview of the state of the art of 4D fabrication technology for the obtainment of cellularized constructs is presented, with a focus on shape-changing soft materials. First, the approaches to obtain cellularized constructs are introduced, also describing conventional and non-conventional fabrication techniques with their relative advantages and limitations. Next, the main families of shape-changing soft materials, namely shape-memory polymers and shape-memory hydrogels are discussed and their use in 4D fabrication in the field of tissue engineering is described. Ultimately, current challenges and proposed solutions are outlined, and valuable insights into future research directions of 4D fabrication for tissue engineering are provided to disclose its full potential.

The need of accurately reproducing the behaviour of elastoplastic materials in computational environments for the solution of engineering problems motivates the development of efficient and robust numerical schemes. These engineering problems often involve complex designs and/or conditions and are further complicated by the necessity of employing highly nonlinear and nonsmooth elastoplastic constitutive equations and constraints to describe material behaviour. Therefore, the numerical solution of such problems is not trivial and requires careful analyses to guarantee algorithm robustness, accuracy, and convergence in a reasonable amount of time. The aim of the present paper is to provide the reader with both an analysis and discussion, helpful in choosing the suitable numerical scheme when considering the implementation of a plasticity model. After a brief overview of the fundamental concepts for classical plasticity theory, we revise the state-of-the-art of computational methods by discussing conventional and less-conventional algorithms, formulated in a unified setting to allow for a comparison. Several approaches are implemented and discussed in representative numerical simulations.

This paper presents a unified modelling effort to describe partial phase transformation during cyclic thermo-mechanical loading in Shape Memory Alloys (SMA). To this purpose, a three-dimensional (3D) finite strain constitutive model considering TRansformation-Induced Plasticity (TRIP) is combined with a modified hardening function to enable the accurate and efficient prediction of partial transformations during cyclic thermo-mechanical loading. The capabilities of the proposed model are demonstrated by predicting the behavior of the material under pseudoelastic and actuation operation using finite element analysis. Numerical results of the modified model are presented and compared with the original model without considering the partial transformation feature as well as with uniaxial actuation experimental data. Various aspects of cyclic material behavior under partial transformation are analyzed and discussed for different SMA systems.

Lattice structures have great potential for several application fields ranging from medical and tissue engineering to aeronautical one. Their development is further speeded up by the continuing advances in additive manufacturing technologies that allow to overcome issues typical of standard processes and to propose tailored designs. However, the design of lattice structures is still challenging since their properties are considerably affected by numerous factors. The present paper aims to propose, discuss, and compare various modeling approaches to describe, understand, and predict the correlations between the mechanical properties and the void volume fraction of different types of lattice structures fabricated by fused deposition modeling 3D printing. Particularly, four approaches are proposed: (i) a simplified analytical model; (ii) a semi-empirical model combining analytical equations with experimental correction factors; (iii) an artificial neural network trained on experimental data; (iv) numerical simulations by finite element analyses. The comparison among the various approaches, and with experimental data, allows to identify the performances, advantages, and disadvantages of each approach, thus giving important guidelines for choosing the right design methodology based on the needs and available data.

Shape memory polymers are attractive smart materials that have many practical applications and academic interest. Three-dimensional (3D) printable shape memory polymers are of great importance for the fabrication of soft robotic devices due to their ability to build complex 3D structures with desired shapes. We present a 3D printable shape memory polymer, with controlled melting and transition temperature, composed of methacrylated polycaprolactone monomers and N-Vinylcaprolactam reactive diluent. Tuning the ratio between the monomers and the diluents resulted in changes in melting and transition temperatures by 20, and 6 °C, respectively. The effect of the diluent addition on the shape memory behavior and mechanical properties was studied, showing above 85% recovery ratio, and above 90% fixity, when the concentration of the diluent was up to 40 wt %. Finally, we demonstrated multi-material printing of a 3D structure that can be activated locally, at two different temperatures, by two different stimuli; direct heating and light irradiation. The remote light activation was enabled by utilizing a coating of Carbon Nano Tubes (CNTs) as an absorbing material, onto sections of the printed objects.

Computer-based simulations are nowadays widely exploited for the prediction of the mechanical behavior of different biomedical devices. In this aspect, structural finite element analyses (FEA) are currently the preferred computational tool to evaluate the stent response under bending. This work aims at developing a computational framework based on linear and higher order FEA to evaluate the flexibility of self-expandable carotid artery stents. In particular, numerical simulations involving large deformations and inelastic shape memory alloy constitutive modeling are performed, and the results suggest that the employment of higher order FEA allows accurately representing the computational domain and getting a better approximation of the solution with a widely-reduced number of degrees of freedom with respect to linear FEA. Moreover, when buckling phenomena occur, higher order FEA presents a superior capability of reproducing the nonlinear local effects related to buckling phenomena.

The great success of stents in treating cardiovascular disease is actually undermined by their long-term fatigue failure. The high variability of stent failure incidence suggests that it is due to several correlated aspects, such as loading conditions, material properties, component design, surgical procedure, and patient functional anatomy. Numerical and experimental non-clinical assessments are included in the recommendations and requirements of several regulatory bodies and they are thus exploited in the analysis of stent fatigue performance. Optimization-based simulation methodologies have been developed as well, to improve the fatigue endurance of novel designs. This paper presents a review on the fatigue issue in metallic stents, starting from a description of clinical evidence about stent fracture up to the analysis of computational approaches available from the literature. The reported discussion on both the experimental and numerical framework aims at providing a general insight into stent lifetime prediction as well as at understanding the factors which affect stent fatigue performance for the design of novel components.