Local rules for fabricating allosteric networks

TL;DR

This paper introduces local-stress-based algorithms for designing allosteric responses in disordered networks, enabling experimental realization of tailored mechanical behaviors without relying on global cost functions.

Contribution

It develops novel in-situ pruning algorithms based solely on local stress information, bridging the gap between simulation design and experimental implementation of allosteric networks.

Findings

Local stress measurements can guide bond pruning effectively.

Pruning strategies vary in success when applied experimentally.

Designed networks exhibit targeted allosteric responses in real materials.

Abstract

Mechanical properties of disordered networks can be significantly tailored by modifying a small fraction of their bonds. This procedure has been used to design and build mechanical metamaterials with a variety of responses. A long-range 'allosteric' response, where a localized input strain at one site gives rise to a localized output strain at a distant site, has been of particular interest. This work presents a novel approach to incorporating allosteric responses in experimental systems by pruning disordered networks $\textit{in-situ}$. Previous work has relied on computer simulations to design and predict the response of such systems using a cost function where the response of the entire network to each bond removal is used at each step to determine which bond to prune. It is not feasible to follow such a design protocol in experiments where one has access only to local response at each site. This paper presents design algorithms that allow determination of what bonds to prune based purely on the local stresses in the network without employing a cost function; using only local information, allosteric networks are designed in simulations and then built out of real materials. The results show that some pruning strategies work better than others when translated into an experimental system. A method is presented to measure local stresses experimentally in disordered networks. This approach is then used to implement pruning methods to design desired responses $\textit{in-situ}$. Results from these experiments confirm that the pruning methods are robust and work in a real laboratory material.