Cooperativity of dynamics in supercooled polymeric materials and its temperature dependence predicted from a surface controlled model

Influence of Chemical Composition and Structure on the Cooperative Fluctuation in Supercooled Glass-Forming Liquids

The kinetics of the glass transition and the characteristic size of the fluctuating spatio-temporal domains in supercooled glass-forming liquids, i.e., the Cooperatively Rearranging Regions (CRR), were measured upon cooling over a broad range of cooling rates using Differential Scanning Calorimetry (DSC) and chip-based Fast Scanning Calorimetry (FSC). The investigations were conducted on a selection of fragile glass formers (fragility indices between 80 and 140), with a large variance in the atomic or molecular structure but comparable thermal glass transition temperatures Tg, with the aim of evaluating the influence of chemical composition and structure on the CRR size and the associated temperature fluctuation. The selected materials are two polymers (poly(vinyl acetate) (PVAc), poly(lactic acid) (PLA)) as well as the simplest chalcogenide glass-former (selenium). It turned out that the CRR size plotted against the reduced temperature T/Tg follows the same trend, irrespective of the considered glass-former.

Thickness Dependence of Segmental Dynamics in Free-Standing Thin Films Predicted by a Dynamically Correlated Network Model

The anomalous dynamics and glass transition behaviors of supercooled liquids under nanoconfinement, such as ultrathin polymer films, have attracted much attention in recent decades. However, a complete elucidation of this mechanism has not yet been achieved. For the dynamics of bulk materials without confinement, we previously proposed a dynamically correlated network (DCN) model, which was found to agree well with the experimental data. The model assumes that segments with thermal fluctuations are dynamically correlated to their neighbors to form string-like clusters, which eventually grow into networks as temperature decreases. In this study, we applied the DCN model to nanoconfined free-standing films by using a simple cubic lattice sandwiched between two free surface layers consisting of virtual "uncorrelated" segments. The average size of DCNs at lower temperatures decreased with decreasing thickness because of confinement. This trend was associated with a decrease in the percolation temperature at which the size of DCN diverges. It was also revealed that the fractal dimension of the generated DCNs exhibits a peak with respect to temperature. The segmental relaxation time for free-standing polystyrene films was evaluated, and the predicted thickness dependence of the glass transition temperature qualitatively agreed with the experimental data. The results suggest that the concept of DCN is compatible with the dynamics of free-standing thin films.

Approaching Polymer Dynamics Combining Artificial Neural Networks and Elastically Collective Nonlinear Langevin Equation

The analysis of structural relaxation dynamics of polymers gives an insight into their mechanical properties, whose characterization is used to qualify a given material for its practical scope. The dynamics are usually expressed in terms of the temperature dependence of the relaxation time, which is only available through time-consuming experimental processes following polymer synthesis. However, it would be advantageous to estimate their dynamics before synthesizing them when designing new materials. In this work, we propose a combined approach of artificial neural networks and the elastically collective nonlinear Langevin equation (ECNLE) to estimate the temperature dependence of the main structural relaxation time of polymers based only on the knowledge of the chemical structure of the corresponding monomer.

A Dynamically Correlated Network Model for the Collective Dynamics in Glass-Forming Molecular Liquids and Polymers

The non-Arrhenius behavior of segmental dynamics in glass-forming liquids is one of the most profound mysteries in soft matter physics. In this article, we propose a dynamically correlated network (DCN) model to understand the growing behavior of dynamically correlated regions during cooling, which leads to the viscous slowdown of supercooled liquids. The fundamental concept of the model is that the cooperative region of collective motions has a network structure that consists of string-like parts, and networks of various sizes interpenetrate each other. Each segment undergoes dynamical coupling with its neighboring segments via a finite binding energy. Monte Carlo simulations showed that the fractal dimension of the DCNs generated at different temperatures increased and their size distribution became broader with decreasing temperature. The segmental relaxation time was evaluated based on a power law with four different exponents for the activation energy of rearrangement with respect to the DCN size. The results of the present DCN model are consistent with the experimental results for various materials of molecular and polymeric liquids.

"Nothing Can Hide Itself from Thy Heat": Understanding Polymers via Unconventional Applications of Thermal Analysis

This article surveys some exciting possibilities and results offered by less common, yet essential applications of differential scanning calorimetry and thermogravimetric analysis (TGA). The applications are concerned with the most commonly studied processes of the glass transition, crystallization, melting, polymerization, and degradation. Issues related to the glass transition include the non-Arrhenius temperature dependence and fragility, kinetic complexity of physical aging, evaluation of cooperatively rearranging regions, and rigid amorphous fraction. Discussion of crystallization covers separation of heterogeneous and homogeneous nucleation, crystallization controlled by physical aging, and the use of isoconversional methods for determining the Hoffman-Lauritzen parameters. For melting, the role of reorganization and nucleation control is emphasized. For the thermal degradation and polymerization, advanced kinetic treatments as a way of obtaining mechanistic insights are discussed, and the possibility of studying both processes during continuous cooling is stressed. The possibility of using TGA for monitoring polycondensation is also highlighted.