A Unit Compound Structure Design: Poisson's Ratio Is Autonomously Adjustable from Negative to Positive

Shape Memory Polymer Composites: 4D Printing, Smart Structures, and Applications

Shape memory polymers (SMPs) and their composites (SMPCs) are smart materials that can be stably deformed and then return to their original shape under external stimulation, thus having a memory of their shape. Three-dimensional (3D) printing is an advanced technology for fabricating products using a digital software tool. Four-dimensional (4D) printing is a new generation of additive manufacturing technology that combines shape memory materials and 3D printing technology. Currently, 4D-printed SMPs and SMPCs are gaining considerable research attention and are finding use in various fields, including biomedical science. This review introduces SMPs, SMPCs, and 4D printing technologies, highlighting several special 4D-printed structures. It summarizes the recent research progress of 4D-printed SMPs and SMPCs in various fields, with particular emphasis on biomedical applications. Additionally, it presents an overview of the challenges and development prospects of 4D-printed SMPs and SMPCs and provides a preliminary discussion and useful reference for the research and application of 4D-printed SMPs and SMPCs.

Effect of Crosshead Speed and Volume Ratio on Compressive Mechanical Properties of Mono- and Double-Gyroid Structures Made of Inconel 718

The current development of additive technologies brings not only new possibilities but also new challenges. One of them is the use of regular cellular materials in various components and constructions so that they fully utilize the potential of porous structures and their advantages related to weight reduction and material-saving while maintaining the required safety and operational reliability of devices containing such components. It is therefore very important to know the properties of such materials and their behavior under different types of loads. The article deals with the investigation of the mechanical properties of porous structures made by the Direct Metal Laser Sintering (DMLS) of Inconel 718. Two types of basic cell topology, mono-structure Gyroid (G) and double-structure Gyroid + Gyroid (GG), with material volume ratios of 10, 15 and 20 %, were studied within our research to compare their properties under quasi-static compressive loading. The testing procedure was performed at ambient temperature with a servo-hydraulic testing machine at three different crosshead testing speeds. The recorded data were processed, while the stress-strain curves were plotted, and Young's modulus, the yield strength Re_0.2, and the stress at the first peak of the local maximum σ_LocMax were identified. The results showed the best behavior under compression load among the studied structures displayed by mono-structure Gyroid at 10 %. At the same time, it can be concluded that the wall thickness of the structure plays an important role in the compressive properties but on the other hand, crosshead speed doesn´t influence results significantly.

Flexural Properties of Lattices Fabricated with Planar and Curved Layered Fused Filament Fabrication

The use of curved layers in fused filament fabrication could lead to various advantages in surface finishing and mechanical properties. Here, the influence of three different structural and manufacturing parameters (volume fraction, raster arrangement, and the use of curved or planar layers) on the mechanical properties of lattice structures under three-point bending is studied. Two different raster arrangements were considered, i.e., those with rasters at planes parallel to the principal axes of the samples and those diagonally arranged, all at four different volume fractions. All different samples were additively manufactured using planar and curved layers. Samples were further dimensionally inspected to refine the computational models before their analysis via finite element simulations. The linear elastic region of the load-displacement curves was further analyzed numerically via finite element models. Predictions with finite element models resulted in good agreement with errors below 10%. Samples with diagonal rasters were 70% softer than those parallel to the principal axes.