Reprogrammable Surfaces Through Star Graph Metamaterials
This work addresses the need for adaptive surfaces in applications like micro devices, tactile displays, manufacturing, and robotic systems, offering a novel approach beyond fixed-state or fully driven systems.
The researchers tackled the problem of creating reprogrammable surfaces that can change shape without continuous inputs, by discovering a subset of auxetic metamaterials with a star-graph structure that allows local shifts in Poisson's ratio to produce different shapes under loading, resulting in a surface capable of displaying arbitrary 2D information and complex 3D shapes.
The ability to change a surface's profile allows biological systems to effectively manipulate and blend into their surroundings. Current surface morphing techniques rely either on having a small number of fixed states or on directly driving the entire system. We discovered a subset of scale-independent auxetic metamaterials have a state trajectory with a star-graph structure. At the central node, small nudges can move the material between trajectories, allowing us to locally shift Poisson's ratio, causing the material to take on different shapes under loading. While the number of possible shapes grows exponentially with the size of the material, the probability of finding one at random is vanishingly small. By actively guiding the material through the node points, we produce a reprogrammable surface that does not require inputs to maintain shape and can display arbitrary 2D information and take on complex 3D shapes. Our work opens new opportunities in micro devices, tactile displays, manufacturing, and robotic systems.