A dynamically reprogrammable metasurface with self-evolving shape morphing

TL;DR

This paper introduces a reprogrammable metasurface capable of rapid, precise, and adaptive 3D shape morphing, using a feedback-controlled, Lorentz-force driven system for applications in soft robotics and smart devices.

Contribution

It presents a novel, reprogrammable mechanical metasurface with self-evolving shape morphing capabilities guided by an optimization-based feedback system.

Findings

Achieves shape morphing within 0.1 seconds

Demonstrates high-precision target shape adaptation

Supports morphing against environmental perturbations

Abstract

Dynamic shape-morphing soft materials systems are ubiquitous in living organisms; they are also of rapidly increasing relevance to emerging technologies in soft machines, flexible electronics, and smart medicines. Soft matter equipped with responsive components can switch between designed shapes or structures, but cannot support the types of dynamic morphing capabilities needed to reproduce natural, continuous processes of interest for many applications. Challenges lie in the development of schemes to reprogram target shapes post fabrication, especially when complexities associated with the operating physics and disturbances from the environment can prohibit the use of deterministic theoretical models to guide inverse design and control strategies. Here, we present a mechanical metasurface constructed from a matrix of filamentary metal traces, driven by reprogrammable, distributed Lorentz forces that follow from passage of electrical currents in the presence of a static magnetic field. The resulting system demonstrates complex, dynamic morphing capabilities with response times within 0.1 s. Implementing an in-situ stereo-imaging feedback strategy with a digitally controlled actuation scheme guided by an optimization algorithm, yields surfaces that can self-evolve into a wide range of 3-dimensional (3D) target shapes with high precision, including an ability to morph against extrinsic or intrinsic perturbations. These concepts support a data-driven approach to the design of dynamic, soft matter, with many unique characteristics.