2025/01/17 by Stefano Aime, Domenico Truzzolillo, Aime, Stefano +1
Engineering · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Material Science and Thermodynamics #Materials Science (cond-mat.mtrl-sci) #Soft Condensed Matter (cond-mat.soft)
paper · pdf · doi:10.48550/arxiv.2501.10039
openalex publication_date 2025/01/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Glassy materials yield under large external mechanical solicitations. Under oscillatory shear, yielding shows a well-known rheological fingerprint, common to samples with widely different microstructures. At the microscale, this corresponds to a transition between slow, solid-like dynamics and faster liquid-like dynamics, which can coexist at yielding in a finite range of strain amplitudes. Here, we capture this phenomenology in a lattice model with two main parameters: glassiness and disorder, describing the average coupling between adjacent lattice sites, and their variance, respectively. In absence of disorder, our model yields a law of correspondent states equivalent to trajectories on a cusp catastrophe manifold, a well-known class of problems including equilibrium liquid-vapour phase transitions. Introducing a finite disorder in our model entails a qualitative change, to a continuous and rounded transition, whose extent is controlled by the magnitude of the disorder. We show that a spatial correlation length ξ emerges spontaneously from the coupling between disorder and bifurcating dynamics. With vanishing disorder, ξ diverges and yielding becomes discontinuous, suggesting that the abruptness of yielding can be rationalized in terms of a lengthscale of dynamic heterogeneities.