Strength of Mechanical Memories is Maximal at the Yield Point of a Soft Glass

TL;DR

This study demonstrates that a soft glass system can encode multiple mechanical memories, with the strongest memory retention occurring at the yield point, influenced by force network evolution during training.

Contribution

It provides experimental evidence that maximum mechanical memory strength occurs at the yield point in a soft glass, highlighting the role of force network dynamics.

Findings

Memory strength peaks near the yield strain.

Multiple memories form without external noise.

Force network evolution influences memory encoding.

Abstract

We show experimentally that both single and multiple mechanical memories can be encoded in an amorphous bubble raft, a prototypical soft glass, subject to an oscillatory strain. In line with recent numerical results, we find that multiple memories can be formed sans external noise. By systematically investigating memory formation for a range of training strain amplitudes spanning yield, we find clear signatures of memory even beyond yielding. Most strikingly, the extent to which the system recollects memory is largest for training amplitudes near the yield strain and is a direct consequence of the spatial extent over which the system reorganizes during the encoding process. Our study further suggests that the evolution of force networks on training plays a decisive role in memory formation in jammed packings.