Relationships among structure, memory, and flow in sheared disordered materials

Abstract

A fundamental challenge for disordered solids is predicting macroscopic yield from the microscopic arrangements of constituent particles. Yield is accompanied by a sudden and large increase in energy dissipation due to the onset of plastic rearrangements. This suggests that one path to understanding bulk rheology is to map particle configurations to their mode of deformation. Here, we perform laboratory experiments and numerical simulations that are designed to do just that: 2D dense colloidal systems are subjected to oscillatory shear, and particle trajectories and bulk rheology are measured. We quantify particle microstructure using excess entropy. Results reveal a direct relation between excess entropy and energy dissipation, that is insensitive to the nature of interactions among particles. We use this relation to build a physically-informed model that connects rheology to microstructure. Our findings suggest a framework for tailoring the rheological response of disordered materials by tuning microstructural properties.

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Cited by in corpus (13)

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• Cooperative effects driving the multi-periodic dynamics of cyclically sheared amorphous solids
• Ultra-stable shear jammed granular material
• Geometric control and memory in networks of hysteretic elements
• Tuning residual stress, directional memory and aging in soft glassy materials
• Rigidity transition of a highly compressible granular medium
• Machine Learning-Informed Scattering Correlation Analysis of Sheared Colloids
• Kovacs-like memory effect in a sheared colloidal glass: role of non-affine flows
• Yielding and memory in a driven mean-field model of glasses
• A catastrophic approach to designing interacting hysterons
• Inverse Bauschinger to Bauschinger Crossover under Steady Shear in Amorphous Solids
• Memories of amplitude and direction coexist and compete in non-Brownian suspensions