Comment on "Fickian Non-Gaussian Diffusion in Glass-Forming Liquids"

Unraveling relationship between complex lifetimes and microscopic diffusion in deep eutectic solvents

Aqueous mixtures of deep eutectic solvents (DESs) have emerged as a subject of interest in recent years for their tailored physicochemical properties. However, a comprehensive understanding of water's multifaceted influence on the microscopic dynamics, including its impact on improved transport properties of the DES, remains elusive. Additionally, the diffusion mechanisms within DESs manifest heterogeneous behavior, intricately tied to the formation and dissociation kinetics of complexes and hydrogen bonds. Therefore, it is imperative to explore the intricate interplay between bond kinetics, diffusion mechanism, and dynamical heterogeneity. This work employs water as an agent to explore their relationships by studying various relaxation phenomena in a DES based on acetamide and lithium perchlorate over a wide range of water concentrations. Notably, acetamide exhibits Fickian yet non-Gaussian diffusion across all water concentrations with Fickian (τf) and Gaussian (τg) timescales following a power-law relationship, τg∝τfγ, γ ∼ 1.4. The strength of coupling between bond kinetics and different diffusion timescales is estimated through various power-law relationships. Notably, acetamide-water hydrogen bond lifetime is linked to diffusive timescales through a single power-law over the entire water concentration studied. However, the relationship between diffusive timescales and the lifetime of acetamide-lithium complexes shows a sharp transition in behavior at 20 wt. % water, reflecting a change from vehicular diffusion below this concentration to structural diffusion above it. Our findings emphasize the critical importance of understanding bond dynamics within DESs, as they closely correlate with and regulate the molecular diffusion processes within these systems.

Entropic timescales of dynamic heterogeneity in supercooled liquid

Non-Gaussian displacement distributions are universal predictors of dynamic heterogeneity in slowly varying environments. Here, we explore heterogeneous dynamics in supercooled liquid using molecular dynamics simulations and show the efficiency of the relative-entropy based measure, negentropy, in quantifying dynamic heterogeneity over the widely used non-Gaussian parameter. Our analysis shows that the heterogeneity quantified by the negentropy is significantly different from the one obtained using the conventional moment-based definition that considers deviation from Gaussianity up to lower-order moments. We extract the timescales of dynamic heterogeneity using the two methods and show that the differential changes diverge as the system experiences strong intermittency near the glass transition. Further, we interpret the entropic timescales and discuss the general implications of our work.

Different glassy characteristics are related to either caging or dynamical heterogeneity

Despite the enormous theoretical and application interests, a fundamental understanding of the glassy dynamics remains elusive. The static properties of glassy and ordinary liquids are similar, but their dynamics are dramatically different. What leads to this difference is the central puzzle of the field. Even the primary defining glassy characteristics, their implications, and if they are related to a single mechanism remain unclear. This lack of clarity is a severe hindrance to theoretical progress. Here, we combine analytical arguments and simulations of various systems in different dimensions and address these questions. Our results suggest that the myriad of glassy features are manifestations of two distinct mechanisms. Particle caging controls the mean, and coexisting slow- and fast-moving regions govern the distribution of particle displacements. All the other glassy characteristics are manifestations of these two mechanisms; thus, the Fickian yet non-Gaussian nature of glassy liquids is not surprising. We discover a crossover, from stretched exponential to a power law, in the behavior of the overlap function. This crossover is prominent in simulation data and forms the basis of our analyses. Our results have crucial implications on how the glassy dynamics data are analyzed, challenge some recent suggestions on the mechanisms governing glassy dynamics, and impose strict constraints that a correct theory of glasses must have.