For heat-triggered shape-changing 3D prints, active and restrictive segments need to be 3D printed next to each other to obtain the desired morphing of an object. Current single-material methods rely on locally controlling the orientation of the printing lines to adjust the amount and direction of shrinkage. This approach, however, limits design freedom as it restricts the shape and fabrication of the objects. Moreover, it results in undesirable deformations in more complex and larger designs. Addressing these challenges, we introduce Foam2Form, a method that forms active and restrictive segments by programming the shape-memory properties of foaming PLA during the printing process.We propose to use the material in a non-foamed state for active segments and in a foamed state for restrictive and passive segments, which results in more stable 4D designs free from unwanted deformations. We present the first results of this low-cost 4D printing method and demonstrate its capabilities with various application examples.

The emergence of the field of soft robotics has led to an interest in suction cups as auxiliary structures on soft continuum arms to support the execution of manipulation tasks. This application poses demanding requirements on suction cups with respect to sensorization, adhesion under non-ideal contact conditions, and integration into fully soft systems. The octopus can serve as an important source of inspiration for addressing these challenges. This review aims to accelerate research in octopus-inspired suction cups by providing a detailed analysis of the octopus sucker, determining meaningful performance metrics for suction cups on the basis of this analysis, and evaluating the state-of-the-art in suction cups according to these performance metrics. In total, 47 records describing suction cups are found, classified according to the deployed actuation method, and evaluated on performance metrics reflecting the level of sensorization, adhesion, and integration. Despite significant advances in recent years, the octopus sucker outperforms all suction cups on all performance metrics. The realization of high resolution tactile sensing in suction cups and the integration of such sensorized suction cups in soft continuum structures are identified as two major hurdles toward the realization of octopus-inspired manipulation strategies in soft continuum robot arms.

Structural electronics has garnered significant attention in the past decade. However, there remains a lack of a systematic approach in designing and manufacturing sensors that leverage both mechanical and electronic properties of materials for different applications. In this paper, we introduce a method for designing piezoresistive force sensors utilizing structural electronics and 3D printing techniques. Based on the principles of piezoresistive force sensing, we defined the geometric profile of the sensor by simultaneously maximizing strain and ensuring as uniform as possible stress distribution across the geometry. CAD models of the sensors were then formulated based on the optimized profile and fabricated using conductive filaments and the material extrusion 3D printing technique. Subsequently, we evaluated the accuracy, the sensitivity, and part-to-part variations of the sensors during loading and unloading. The influence of environmental temperature and humidity on the sensor's response were also investigated and compensated. Experiment results demonstrated the feasibility of the proposed method and revealed potential application domains, as well as limitations of the sensors.

Living organisms use functional gradients (FGs) to interface hard and soft materials (e.g., bone and tendon), a strategy with engineering potential. Past attempts involving hard (or soft) phase ratio variation have led to mechanical property inaccuracies because of microscale-material macroscale-property nonlinearity. This study examines 3D-printed voxels from either hard or soft phase to decode this relationship. Combining micro/macroscale experiments and finite element simulations, a power law model emerges, linking voxel arrangement to composite properties. This model guides the creation of voxel-level FG structures, resulting in two biomimetic constructs mimicking specific bone-soft tissue interfaces with superior mechanical properties. Additionally, the model studies the FG influence on murine preosteoblast and human bone marrow-derived mesenchymal stromal cell (hBMSC) morphology and protein expression, driving rational design of soft-hard interfaces in biomedical applications.

We propose a new approach to obtain local property variations in 3D-printed objects using a single-nozzle 3D printer and one filament. We use foaming filaments which expand at different rates due to different temperatures. We present an approach to harness this varying expansion by including parameters of the 3D printing process in the design space. This makes the foaming programmable and allows for achieving a wide variety of properties from a single material. We show how objects with locally varying shade, translucency, gloss, and texture can be fabricated. Our approach turns single-nozzle 3D printers into more versatile systems while eliminating the challenges of multi-material 3D printing. This is in contrast to the drive towards an increasing number of printable materials and more complex 3D printers. We demonstrate the capability of our approach by 3D printing objects with embedded barcodes, QR codes, and varying tactile properties.

Durable interfacing of hard and soft materials is a major design challenge caused by the ensuing stress concentrations. In nature, soft-hard interfaces exhibit remarkable mechanical performance, with failures rarely happening at the interface. Here, we mimic the strategies observed in nature to design efficient soft-hard interfaces. We base our geometrical designs on triply periodic minimal surfaces (i.e., Octo, Diamond, and Gyroid), collagen-like triple helices, and randomly distributed particles. A combination of computational simulations and experimental techniques, including uniaxial tensile and quad-lap shear tests, are used to characterize the mechanical performance of the interfaces. Our analyses suggest that smooth interdigitated connections, compliant gradient transitions, and either decreasing or constraining strain concentrations lead to simultaneously strong and tough interfaces. We generate additional interfaces where the abovementioned toughening mechanisms work synergistically to create soft-hard interfaces with strengths approaching the upper achievable limit and enhancing toughness values by 50%, as compared to the control group.

The geometric shapes and the relative position of coils influence the performance of a three-dimensional (3D) inductive power transfer system. In this paper, we propose a coil design method for specifying the positions and the 3D shapes of a pair of coils to transmit the desired power. Given region of interests (ROIs) for designing the transmitter and the receiver coils on two surfaces, the transmitter coil is generated around the center of its ROI. The center of the receiver coil is estimated as a random seed position in the corresponding 3D surface. At this position, we use the heatmap method with electromagnetic constraints to iteratively extend the coil until the desired power can be transferred via the set of coils. In each step, the shape of the extension, i.e., a new turn of the receiver coil, is found as a spiral curve based on the convex hulls of the 2D projected adjacent turns along their normal direction. Then, the optimal position of the receiver coil is found by maximizing the efficiency of the system. In the next step, the position and the shape of the transmitter coil are optimized based on the fixed receiver coil using the same method. This optimization process iterates until an optimum is reached. Simulations and experiments with digitally fabricated prototypes were conducted and the effectiveness of the proposed 3D coil design method was verified.

Bio-inspired composites are a great promise for mimicking the extraordinary and highly efficient properties of natural materials. Recent developments in voxel-by-voxel 3D printing have enabled extreme levels of control over the material deposition, yielding complex micro-architected materials. However, design complexity, very large degrees of freedom, and limited computational resources make it a formidable challenge to find the optimal distribution of both hard and soft phases. To address this, a nonlinear coarse-graining approach is developed, where foam-based constitutive equations are used to predict the elastoplastic mechanical behavior of biomimetic composites. The proposed approach is validated by comparing coarse-grained finite element predictions against full-field strain distributions measured using digital image correlation. To evaluate the degree of coarse-graining on model accuracy, pre-notched specimens decorated with a binarized version of a renowned painting were modeled. Subsequently, coarse-graining is used to predict the fracture behavior of bio-inspired composites incorporating complex designs, such as functional gradients and hierarchical organizations. Finally, as a showcase of the proposed approach, the inverse coarse-graining is combined with a theoretical model of bone tissue adaptation to optimize the microarchitecture of a 3D-printed femur. The predicted properties were in exceptionally good agreement with the corresponding experimental results. Therefore, the coarse-graining method allows the design of advanced architected materials with tunable and predictable properties.