Jamming memory into acoustically trained dense suspensions under shear

TL;DR

This paper demonstrates how acoustic perturbations can embed structural memories in dense suspensions, enabling tunable rheological properties and shear jamming behaviors, which could lead to new adaptable material designs.

Contribution

It introduces a novel method of using acoustic training to embed and control memory effects in dense suspensions, affecting their shear response and jamming behavior.

Findings

Suspensions shear jam with stress contributions reflecting acoustic training axes.

Training alters susceptibility to acoustic perturbations and viscosity changes.

Flowing states below shear jamming threshold can be shear jammed via acoustic training.

Abstract

Systems driven far from equilibrium often retain structural memories of their processing history. This memory has, in some cases, been shown to dramatically alter the material response. For example, work hardening in crystalline metals can alter the hardness, yield strength, and tensile strength to prevent catastrophic failure. Whether memory of processing history can be similarly exploited in flowing systems, where significantly larger changes in structure should be possible, remains poorly understood. Here, we demonstrate a promising route to embedding such useful memories. We build on work showing that exposing a sheared dense suspension to acoustic perturbations of different power allows for dramatically tuning the sheared suspension viscosity and underlying structure. We find that, for sufficiently dense suspensions, upon removing the acoustic perturbations, the suspension shear jams with shear stress contributions from the maximum compressive and maximum extensive axes that reflect the acoustic training. Because the contributions from these two orthogonal axes to the total shear stress are antagonistic, it is possible to tune the resulting suspension response in surprising ways. For example, we show that differently trained sheared suspensions exhibit: 1) different susceptibility to the same acoustic perturbation; 2) orders of magnitude changes in their instantaneous viscosities upon shear reversal; and 3) even a shear stress that increases in magnitude upon shear cessation. To further illustrate the power of this approach for controlling suspension properties, we demonstrate that flowing states well below the shear jamming threshold can be shear jammed via acoustic training. Collectively, our work paves the way for using acoustically induced memory in dense suspensions to generate rapidly and widely tunable materials.