Inter-particle adhesion induced strong mechanical memory in a dense granular suspension

TL;DR

This study demonstrates that dense suspensions with inter-particle adhesion can encode strong, multi-level mechanical memories of cyclic shear, with memory strength depending on training amplitude and boundary localization effects.

Contribution

It reveals that inter-particle adhesion enables robust mechanical memory in dense suspensions, including multi-input memory, which was not previously demonstrated.

Findings

Memory strength decreases with increasing training amplitude.

Boundary strain localization influences memory encoding.

System can remember multiple inputs if trained in a specific order.

Abstract

Repeated/cyclic shearing can drive amorphous solids to a steady-state encoding a memory of the applied strain amplitude. However, recent experiments find that the effect of such memory formation on the mechanical properties of the bulk material is rather weak. Here we study the memory effect in a yield stress solid formed by a dense suspension of cornstarch particles in paraffin oil. Under cyclic shear, the system evolves towards a steady-state showing training-induced strain stiffening and plasticity. A readout reveals that the system encodes a strong memory of the training amplitude as indicated by a large change in the differential shear modulus. We observe that memory can be encoded for a wide range of training amplitude both above and below the yielding, albeit, the strength of the memory decreases with increasing the training amplitude. In-situ boundary imaging shows strain localization close to the shearing boundaries, while the bulk of the sample moves like a solid plug. In the steady-state, the average particle velocity (<v>) inside the solid-like region slows down with respect to the moving plate as the strain approaches the training amplitude, however, as the readout strain crosses the amplitude, <v> suddenly increases. We demonstrate that inter-particle adhesive interaction is crucial for such a strong memory effect. Interestingly, our system can also remember more than one input only if the training strain with a smaller amplitude is applied last.