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Biological materials generally have better properties than engineered materials due to their intricate architecture, e.g., high strength-to-weight ratio, stiffness, toughness and adaptability. It has proven difficult to synthesize materials with biomimetic architecture. Recently, 3D printing techniques show great promise in bioinspired structural materials. In this paper, we propose an approach to fabricate composite materials with aligned steel fibers using a self-made 3D printer and characterized the mechanical properties of the prepared materials. To do so, we developed a DLP-based 3D printing process that can align short steel fibers in the resin matrix via magnetic assembly during the printing process. Using the developed process and raw materials, samples with ordered fibers were prepared. The mechanical properties of the printed materials, including the strength and friction, as well as morphology, were characterized. The results show that magnetically assisted scraper shear-induced 3D printing can realize the ordered arrangement of fibers. The tensile and compressive strength consistent with the direction of aligned fibers are higher than that of other directions. The friction performance perpendicular to the direction of aligned fibers is better than that of other directions. The mechanical and frictional properties of the composite contenting 5% fibers are better than that of 10% or 15%. This study provides a basis for the manufacture of biomimetic materials. A magnet-assisted assembly 3D print technology is developed to produce steel fiber-resin composites with ordered architecture by programming the traveling paths of a magnet. To demonstrate the feasibility of the proposed method, a helicoidal ladder structure with ordered reinforced fibers is printed. Finally, the mechanical properties of printed composite materials with various patterns of aligned fibers are characterized.

Tactile sensors are instrumental for developing the next generation of biologically inspired robotic prostheses with tactile feedback. Despite significant advancements made in current sensing technology, several limitations still exist including the reduced sensing sensitivity under high pressure, lack of compliance of the planar sensor with working surfaces and the demand for sophisticated manufacturing processes. In this study, we investigate the feasibility of using the 3D printing technology for the rapid and simple fabrication of a new conformal tactile sensor with an improved linear sensing range. The auxetic structure is integrated with a biomimetic inter-locked papilla feature which allows to detect multi-directional stimuli. Using the proposed design, the linear sensing range is extended to 0.5MPa and responsive to normal and shear forces with the sensitivities of 2.42KPa^(-1)and 2.20N^(-1) respectively. The proposed tactile sensor was printed on the fingertip of a prosthetic robotic hand to perform the sensorimotor control, or on the proximal femur head and lumbar vertebra for monitoring the bone-on-bone load. The results have shown promising application prospects of the proposed tactile sensor.

For prey, seeding, and protection, plants exhibit ingenious adaptive motions that respond autonomously to environmental stimuli by varying cellular organization, anisotropic orientation of cellulose fibers, mechanical instability design, etc. Notably, plants do not leverage muscle and nerves to produce and regulate their motions. In contrast, they harvest energy from the ambient environment and compute through embodied intelligence. These characteristics make them ideal candidates for application in self-morphing devices. Four-dimensional (4D) printing is a bottom-up additive manufacturing method that builds objects with the ability to change shape/properties in a predetermined manner. A versatile motion design catalog is required to predict the morphing processes and final states of the printed parts. This review summarizes the morphing and actuation mechanisms of plants and concludes with the recent development of 4D-printed smart materials inspired by the locomotion and structures of plant systems. We provide analyses of the challenges and our visions of biomimetic 4D printing, hoping to boost its application in soft robotics, smart medical devices, smart parts in aerospace, etc.

Shape memory polymers (SMPs) generally change shape from a temporary state to a permanent state, and the permanent shape is only determined by its initial form, which leads to the lack of design freedom for SMPs. In order to enrich morphing behavior and extend applications of SMPs, bioinspired design and fabrication methods need to be developed. Many biological dynamic materials enable shape changes ranging from bending, twisting to spiraling using site-specific aligned cellulose microfibers orientations. Here, we proposed an approach integrating bioinspired fiber architectures and varying 3D printing parameters into SMPs, to achieve tunable permanent shape and shape memory properties. The self-folded flower and sequentially deployed smart robotic hand have been developed to demonstrate the feasibility of our method. The proposed bioinspired SMPs, which is rarely seen in the previous reports, have intriguing fundamental properties and hold great potential for applications in soft actuators, smart textiles, wearable equipment, medical devices, and other intelligent apparatus.

Fiber is a crucial element in biological micro-structural materials. Replication of fiber-reinforced composites with analogous architectures of their natural counterparts has caused widespread academic concern. Recent researches indicate 3D printing technology has the potential to produce biomimetic structural materials. The aim of this study is to develop a process to fabricate fiber-reinforced composites with ordered yet spatially tunable fiber arrangement. Specifically, we present a method to align fibers during the 3D printing of fiber-reinforced composites. A modified slurry-based stereolithography process was developed, and the fibers in the fiber–resin mixture were aligned by Shear force produced during the spreading of slurry. We investigated the influence of relative factors on fiber orientation, and two models were used to uncover the internal mechanism. By controlling the speed and the direction of the moving blade, the patterns that fibers were arranged can be freely programmed. Therefore, we have extracted bioinspired sinusoidal and zigzag design motifs to analyze their mechanical properties compared with non-bioinspired motifs. The proposed method is relatively material agnostic, more efficient and more facile. It thus provides a promising route to fabricate fiber-reinforced composites, and has potential to be adopted in biological structures researches and industrial applications.

In the natural composites, the reinforcement particles are subtly organized into complex structures in matrix, and its various microstructures endow the biomaterials with a variety of excellent mechanical behaviors. Among the various reinforcement building blocks used in biomaterials, short fibers are the most ubiquitous reinforcement elements. Unfortunately, because of the limitation of fabrication technique, replication of these fiber-reinforced biological composites can be extremely difficult in practice. In this paper, we developed a fiber assembly 3D printing process, which can manipulate the orientation of fibers during 3D printing procedure. Benefiting from this technology, the reinforcement particles were manipulated remotely and the arrangement of reinforcement particles with higher degree of freedom was achieved. Subsequently, based on the herringbone-modified helicoidal architecture of mantis shrimp, the bio-inspired composites with various microstructures were reconstructed by 3D magnetic printing. In addition, the influence of microstructure type and parameters of bio-inspired composites on the properties of composites was studied systematically, and the quantitative relationship between microstructure and properties of the composites was established. The results show that the impact resistance and compression resistance of the composites can be significantly improved by the simple internal microstructures design, and the regression model established in this article can be used for accurate prediction of composites properties and the reliability is higher. In a word, this study opens a new route for the design of composites with unusual features.