Unraveling Transient Behaviors in Soft Matters from Dynamics in Non-Equilibrium

Soft matters in industrial applications and natural phenomena frequently transition to non-equilibrium states under external stimuli such as temperature shifts, mechanical forces, or chemical reactions. In these conditions, microscopic dynamics play a critical role in shaping macroscopic responses, resulting in complex transient behaviors such as metastable transitions, aging, rupture, avalanches, and phase re-entrance. Enhancing the prediction and control of these processes requires a thorough understanding of how dynamics govern macroscopic responses, and, consequently, influence material properties. In this study, we integrate the combined effects of internal and external forces into a Markov chain framework, introducing a universal parameter—the transport coefficient—to characterize non-equilibrium dynamics. Utilizing X-ray photon correlation spectroscopy (XPCS), we capture subtle changes during yielding and stress relaxation, offering experimental validation for theoretical and simulation-based predictions on phenomena such as delayed yielding and resolidification. Our findings provide new insights into dynamical heterogeneity and cooperativity, generating large datasets that facilitate the development of artificial intelligence models. These results strengthen the connection between microscopic dynamics and macroscopic properties, enhance predictive models for transient behaviors, and open new opportunities for optimizing soft materials in industrial processes and natural systems.