Emergent reprogrammable mechanical memory in soft rods network via friction tuning

TL;DR

This paper demonstrates a reprogrammable mechanical memory in soft rod networks, where friction tuning enables shape change storage under strain, with potential applications in soft robotics and adaptive materials.

Contribution

It introduces a novel soft cellular material system that exhibits reprogrammable mechanical memory through friction-controlled state transitions.

Findings

Memory state can be erased and reprogrammed by removing global strain.

The system transitions from elastic to plastic state under strain, enabling shape storage.

A simple friction-based model explains the observed behavior.

Abstract

We present emergent mechanical memory storage behavior in soft cellular materials. The cellular materials are a network of soft hyperelastic rods which store shape changes, specifically local indentation. This happens under an applied global compressive strain on the material. The material transits under strain from an elastic state (capable of `forgetting' any applied indentation after un-indentation) to plastic state (indefinitely storing the shape change due to indentation). The memory can be erased via removal of applied global strains and is therefore re-programmable. We characterise this behaviour experimentally and present a simple model that makes use of friction for understanding this behavior.