Looking at the dynamical heterogeneity in a supercooled polymer system through isoconfigurational ensemble

From disorder to order: A dynamic approach to mesophase formation in soft sphere model

This study explores the dynamics of self-assembly and mesophase formation through molecular dynamics simulations of hexagonal and lamellar systems using a simplified coarse-grained model. We focus on characterizing the order-disorder transitions driven by temperature variations and emphasize the often overlooked disordered regime, which serves as a precursor to periodic mesoscale ordering. Our findings not only underscore the morphological richness of the disordered regime, comparable to that of its periodic counterparts, but also reveal the presence of clustering regimes within isotropic phases, thus corroborating prior experimental and theoretical observations. By employing the dynamic correlation coefficient, this work introduces a novel approach to understanding the fundamental mechanisms of mesophase formation, providing new insights into the complex dynamics of self-assembly.

The influence of molecular shape on glass-forming behavior in a minimalist trimer model

In this study, we employed molecular dynamics simulations to probe the influence of molecular morphological changes on the dynamic behavior of a model consisting of trimer molecules. This model, comprising a chain of three particles, facilitates the exploration of variations in the internal angle between these particles. Our findings highlight the significant impact of molecular conformation: systems with more linear conformations, characterized by larger internal angles, exhibit relaxation times several orders of magnitude greater than their counterparts with smaller internal angles. Furthermore, we delve into the role of angular interaction rigidity, uncovering a pronounced deceleration in dynamics and an increase in dynamic heterogeneity as rigidity escalates. This model not only provides insights into azobenzene-type systems but also sets the stage for subsequent research into the microscopic nuances of related systems, with potential extensions to composite systems.

Neural Networks Reveal the Impact of the Vibrational Dynamics in the Prediction of the Long-Time Mobility of Molecular Glassformers

Two neural networks (NN) are designed to predict the particle mobility of a molecular glassformer in a wide time window ranging from vibrational dynamics to structural relaxation. Both NNs are trained by information concerning the local structure of the environment surrounding a given particle. The only difference in the learning procedure is the inclusion (NN A) or not (NN B) of the information provided by the fast, vibrational dynamics and quantified by the local Debye–Waller factor. It is found that, for a given temperature, the prediction provided by the NN A is more accurate, a finding which is tentatively ascribed to better account of the bond reorientation. Both NNs are found to exhibit impressive and rather comparable performance to predict the four-point susceptibility χ4(t) at τα, a measure of the dynamic heterogeneity of the system.

A structural study and its relation to dynamic heterogeneity in a polymer glass former

The relationship between structure and dynamical behavior (super-Arrhenius temperature dependence of relaxation time accompanied by heterogeneous dynamics) in glassy materials remains an open issue in the physics of condensed matter. The question of whether this dynamic phenomena have a thermodynamic origin or not still remains unanswered. In this work we analyze several dynamic and structural parameters in a polymer glass-former by means of molecular dynamics simulations. The results obtained in this work indicate that the structure does affect dynamic behavior, whereas structural conditioning becomes noticeable below the temperature at which the non-Arrhenius behavior manifests and increases as the system approaches the glass transition temperature. Moreover, we observed that the short-range order parameters are related to local dynamics at the single-particle level. These results reinforce the idea of a connection between the structure and dynamics and that could indicate the thermodynamic nature of glass transition.

An alternative approach to evidence the structural conditioning in the dynamic slowdown in a polymer glass-former

Dynamic slowdown of liquids, leading to a breakdown of Arrhenius behavior of relaxation and Stokes-Einstein relationship (SER), as the glass transition is approached, is still not fully understood despite decades of study. They are usually associated to the emergence of dynamic heterogeneity, that is, regions or clusters of particles that have high or low mobilities. But the physical origin of these dynamic heterogeneity, and in particular, the question whether they have a structural origin or they are a purely dynamical phenomenon, is still under debate. In this work we study through molecular dynamics simulations in a polymer model the dynamic slowdown and the breakdown of SER, in connection with dynamic susceptibility calculated for an isoconfigurational ensemble, such that the effects of structure on dynamics can be discriminated. The onset of structure effects on dynamical behavior is found to be coincident with the onset of slow dynamics and SER breakdown.

Static and dynamic correlation lengths in supercooled polymers

A key point to understand the glass transition is the relationship between structural and dynamic behavior experienced by a glass former when it approaches T_g. In this work, the relaxation in a simple bead-spring polymer system in the supercooled regime near its glass transition temperature was investigated with molecular dynamic simulations. We develop a new manner to look at the dynamic length scales in a supercooled polymeric system, focusing on correlated motion of particles in an isoconfigurational ensemble (that is, associated with the structure), as measured by Pearson's correlation coefficient. We found that while the usual dynamic four-point correlation length deviates from the structural (mosaic or point-to-set) length scale at low temperatures, Pearson's length behaves similarly to the static length in the whole temperature range. The results lead to a consensus of similar scaling of structural and dynamical length scales, reinforcing the idea of the theories of Adam-Gibbs and random first order transition.