Adaptable force chains in granular assemblies using variable stiffness particles

Under an externally applied load, force chain networks form in granular assemblies that depend on, among other things, the contact network and stiffness of the grains. In this work, we fabricate variable stiffness particles, whose stiffness can be reversibly changed on demand to tune the force network in a packing. Each variable stiffness particle is made of a silicone shell that encapsulates a Field’s metal core. This eutectic alloy of bismuth, indium, and tin with a low melting point, exhibits a large drop in its elastic moduli after changing from solid to liquid. By sending electric current through co-located copper heaters, the Field’s metal can melt via Joule heating, which softens the particle. In the cool state, the Field’s metal particle modulus is 4 MPa but reduces to 1 MPa in the soft, heated state. To optimize the mechanical response of granular packings containing mixtures of soft and stiff particles, we employ evolutionary algorithms coupled with discrete element method simulations to dictate the patterning of grains that will yield a particular force output on the assembly boundary. The predicted designs were replicated in experiments using variable stiffness particles in a photoelastic container to measure the output forces between the particles and the boundary, with good matching between simulation and reality. We view this result as a first step toward making granular metamaterials made of robotic grains that can dynamically adapt their force chains, bulk moduli, and frequency response on demand.