Our work demonstrates how power-law interactions within metamaterials can program dynamic recoil dynamics, setting the stage for new materials designs for energy management and conversion in high-rate applications.Ĭurvature impacts physical properties across multiple length scales, ranging from the macroscopic scale, where the shape and size vary drastically with the curvature, to the nanoscale at interfaces and inhomogeneities in materials with structural, chemical, electronic, and magnetic short-range order. We find good agreements in the recoil velocity by comparing our analytical model to experiments of the recoiling metamaterials with magnetic interactions. We further discover that the nonlinear wave speed has a non-monotonic dependence upon the strength of the power-law interaction.

We propose a sequential wave motion during the dynamic recoil, where a linear wave propagates at a large stretch and switches to a nonlinear one below a critical stretch. Our model predicts a “sonic vacuum” response in the recoiling metamaterials, where a near-zero speed of sound is induced by strongly nonlinear interactions and zero initial prestress. Under a weakly nonlinear condition, the governing equation of the dynamic recoil is described by the KdV (Korteweg-de Vries) equation and under the condition of strong nonlinearity by a more general strongly nonlinear wave equation. Starting with a 1D discrete model, we demonstrate how the nonlinear force interactions and the elastic structures in metamaterials control the dynamic performance. Here, we study the dynamic recoil that couples with a general nonlinear power-law interaction within a metamaterial framework. However, a predictive model for understanding the kinematics and recoil dynamics has not been developed. Metamaterials with designed elastic structures and nonlinear interactions (e.g., magnetic interactions) have recently demonstrated the capability to control impulsive motions and manage high-rate energy transfer events. Traditionally, recoil dynamics in unstructured linear elastic systems are based on inertial and elastic properties, with the recoil velocity determined by the materials' speed of sound and the strain at recoil. We start the assembly at high Γ and show still images at various points in the assembly as Γ is decreased.īiological systems can generate motions with high acceleration and velocity via dynamic recoil. We therefore place the nets with the appropriate face-up or face-down orientation.

For the shaking amplitudes we can achieve in our apparatus, the acceleration is not sufficient to completely flip the nets over. To assemble the final structures, we place the nets in our shaker apparatus at random locations. In addition, to enhance selectivity of the binding, we vary the panel orientations relative to the nets: enlarged regions in A. We vary the width of the net elements so that some elements bend and others remain flat. In the leftmost column, we show the engineering design for each pair of nets. Using the different binding energies of the different panels, their orientation, as well as the width, length, and thickness of the 2D net elements, we assemble various 3D structures: a book (A), a tetrahedron (B), a cube (C), and a bowl (D). Hierarchical self-assembly of 2D nets into 3D structures. We envision that magnetic encoding of assembly instructions into primary structures of panels, strands, and nets will lead to the formation of secondary and even tertiary structures that transmit information, act as mechanical elements, or function as machines on scales ranging from the nano to the macro. Using a centimeter-sized version of these panels, we demonstrate 3 canonical hallmarks of assembly: controlled polymerization of individual building blocks assembly of 1-dimensional strands made of panels connected by elastic backbones into secondary structures and hierarchical assembly of 2-dimensional nets into 3-dimensional objects. Because the ratios of the different panel-binding energies are scale-invariant, this approach can, in principle, be applied down to the nanometer scale. Our building blocks consist of panels with different patterns of magnetic dipoles that are capable of specific binding. Here, we introduce a platform based on magnetic encoding of information to drive programmable self-assembly that works across length scales. Programmable self-assembly of smart, digital, and structurally complex materials from simple components at size scales from the macro to the nano remains a long-standing goal of material science.

Handshaker cornell