RESUMEN
Multifunctional materials with distributed sensing and programmed mechanical properties are required for myriad emerging technologies. However, current fabrication techniques constrain these materials' design and sensing capabilities. We address these needs with a method for sensorizing architected materials through fluidic innervation, where distributed networks of empty, air-filled channels are directly embedded within an architected material's sparse geometry. By measuring pressure changes within these channels, we receive feedback regarding material deformation. Thus, this technique allows for three-dimensional printing of sensorized structures from a single material. With this strategy, we fabricate sensorized soft robotic actuators on the basis of handed shearing auxetics and accurately predict their kinematics from the sensors' proprioceptive feedback using supervised learning. Our strategy for facilitating structural, sensing, and actuation capabilities through control of form alone simplifies sensorized material design for applications spanning wearables, smart structures, and robotics.
RESUMEN
In nature, repeated base units produce handed structures that selectively bond to make rigid or compliant materials. Auxetic tilings are scale-independent frameworks made from repeated unit cells that expand under tension. We discovered how to produce handedness in auxetic unit cells that shear as they expand by changing the symmetries and alignments of auxetic tilings. Using the symmetry and alignment rules that we developed, we made handed shearing auxetics that tile planes, cylinders, and spheres. By compositing the handed shearing auxetics in a manner inspired by keratin and collagen, we produce both compliant structures that expand while twisting and deployable structures that can rigidly lock. This work opens up new possibilities in designing chemical frameworks, medical devices like stents, robotic systems, and deployable engineering structures.
RESUMEN
Additive manufacturing by layerwise photopolymerization, commonly called stereolithography (SLA), is attractive due to its high resolution and diversity of materials chemistry. However, traditional SLA methods are restricted to planar substrates and planar layers that are perpendicular to a single-axis build direction. Here, we present a robotic system that is capable of maskless layerwise photopolymerization on curved surfaces, enabling production of large-area conformal patterns and the construction of conformal freeform objects. The system comprises an industrial six-axis robot and a custom-built maskless projector end effector. Use of the system involves creating a mesh representation of the freeform substrate, generation of a triangulated toolpath with curved layers that represents the target object to be printed, precision mounting of the substrate in the robot workspace, and robotic photopatterning of the target object by coordinated motion of the robot and substrate. We demonstrate printing of conformal photopatterns on spheres of various sizes, and construction of miniature three-dimensional objects on spheres without requiring support features. Improvement of the motion accuracy and development of freeform toolpaths would enable construction of polymer objects that surpass the size and support structure constraints imparted by traditional SLA systems.