Evolving Programmable Computational Metamaterials

TL;DR

This paper demonstrates how to embed Boolean logic gates into granular metamaterials through evolutionary placement of grains, showing potential for programmable mechanical computing devices.

Contribution

It introduces an evolutionary approach to design granular metamaterials with embedded logic functions, highlighting differences in evolvability between mass and stiffness contrast materials.

Findings

Materials with stiffness contrast are more evolvable.

Evolutionary search can identify gradients of logic-ability.

Embedded logic gates are confirmed within the metamaterials.

Abstract

Granular metamaterials are a promising choice for the realization of mechanical computing devices. As preliminary evidence of this, we demonstrate here how to embed Boolean logic gates (AND and XOR) into a granular metamaterial by evolving where particular grains are placed in the material. Our results confirm the existence of gradients of increasing "AND-ness" and "XOR-ness" within the space of possible materials that can be followed by evolutionary search. We measure the computational functionality of a material by probing how it transforms bits encoded as vibrations with zero or non-zero amplitude. We compared the evolution of materials built from mass-contrasting particles and materials built from stiffness-contrasting particles, and found that the latter were more evolvable. We believe this work may pave the way toward evolutionary design of increasingly sophisticated, programmable, and computationally dense metamaterials with certain advantages over more traditional computational substrates.