Kirigami, the traditional paper-cutting craft, holds immense potential for revolutionizing robotics by providing multifunctional, lightweight, and adaptable solutions. Kirigami structures, characterized by their bending-dominated deformation, offer resilience to tensile forces and facilitate shape morphing under small actuation forces. Kirigami components such as actuators, sensors, batteries, controllers, and body structures can be tailored to specific robotic applications by optimizing cut patterns. Actuators based on kirigami principles exhibit complex motions programmable through various energy sources, while kirigami sensors bridge the gap between electrical conductivity and compliance. Kirigami-integrated batteries enable energy storage directly within robot structures, enhancing flexibility and compactness. Kirigami-controlled mechanisms mimic mechanical computations, enabling advanced functionalities such as shape morphing and memory functions. Applications of kirigami-enabled robots include grasping, locomotion, and wearables, showcasing their adaptability to diverse environments and tasks. Despite promising opportunities, challenges remain in the design of cut patterns for a given function and streamlining fabrication techniques.

We introduce a novel fully convolutional neural network (FCN) architecture for predicting the secondary structure of ribonucleic acid (RNA) molecules. Interpreting RNA structures as weighted graphs, we employ deep learning to estimate the probability of base pairing between nucleotide residues. Unique to our model are its massive 11-pixel kernels, which we argue provide a distinct advantage for FCNs on the specialized domain of RNA secondary structures. On a widely adopted, standardized test set comprised of 1,305 molecules, the accuracy of our method exceeds that of current state-of-the-art (SOTA) secondary structure prediction software, achieving a Matthews Correlation Coefficient (MCC) over 11-40% higher than that of other leading methods on overall structures and 58-400% higher on pseudoknots specifically.

Shape morphing that transforms morphologies in response to stimuli is crucial for future multifunctional systems. While kirigami holds great promise in enhancing shape-morphing, existing designs primarily focus on kinematics and overlook the underlying physics. This study introduces a differentiable inverse design framework that considers the physical interplay between geometry, materials, and stimuli of active kirigami, made by soft material embedded with magnetic particles, to realize target shape-morphing upon magnetic excitation. We achieve this by combining differentiable kinematics and energy models into a constrained optimization, simultaneously designing the cuts and magnetization orientations to ensure kinematic and physical feasibility. Complex kirigami designs are obtained automatically with unparallel efficiency, which can be remotely controlled to morph into intricate target shapes and even multiple states. The proposed framework can be extended to accommodate various active systems, bridging geometry and physics to push the frontiers in shape-morphing applications, like flexible electronics and minimally invasive surgery.

Scientists have created incredible robotic grippers inspired by the Japanese art of Kirigami that are delicate enough to lift a raw egg yolk without breaking it. Kirigami is a Japanese art similar to origami, except it makes use of intricate cuts to paper, rather than relying on folding alone, to create striking 3D art. The plastic grippers, created by experts at North Carolina State University, are also precise enough to lift a human hair and a live fish without hurting it. Footage shows that they lift blobs of shampoo foam and even pine nuts off the top of a raw egg yolk without puncturing it. The grippers are demonstrated in a new paper as a concept for now, but they could have applications for biomedical technologies, such as joint implants.

Whatever you call them, you've gotta respect them. I mean, have you tried getting around without any arms or legs? The snake's ambulatory secret is its special belly scales, which grip a surface like cleat spikes to help the reptile push forward. And now that secret has made it into robotics. Researchers report today in Science Robotics that they've designed an inflatable robot with its own scales that automatically pop out to get that grip.