Mechanical Tuning of Residual Stress, Memory, and Aging in Soft Glassy Materials

Abstract

Glassy materials rapidly quenched from a liquid to a solid state upon flow cessation or cooling solidify in an out-of-equilibrium configuration, trapping residual stresses and retaining the memory of the processing conditions for very long times, which compromises their physical characterization and can adversely affect processing operations. Erasing the mechanical history encoded in disordered materials constitutes a great challenge. Here, we address this problem using experiments and particle dynamic simulations for the case of colloidal glasses made of soft particles densely packed at high volume fractions. We propose a conceptual framework that connects residual stresses, directional memory, and aging of colloidal glasses to the distribution of local shear stresses in the shearing plane. The mean value of the distribution corresponds to the macroscopic stress, the skewness carries information about directional memory, and the standard deviation is related to mechanical aging. Periodically training soft particle glasses near the yield point with a sequence of stress-controlled oscillations provides a fine-tuning of the particle stress distribution. Asymmetric shear stress distributions resulting from previous flow are transformed into symmetric distributions, thereby successfully erasing residual stresses and directional memory. The same methodology is successfully applied to colloidal and polymer gels with thixotropic properties, suggesting that it is general and may be extended to other classes of disordered materials. Published by the American Physical Society 2025