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In the region near an interface, the microscopic properties of a glass forming liquid may be perturbed from their equilibrium bulk values. In this work, we probe how the interfacial effects of additive particles dispersed in a matrix can influence the local mobility of the material and its glass transition temperature, T g . Experimental measurements and simulation results indicate that additives, such as nanoparticles, gas molecules, and oligomers, can shift the mobility and T g of a surrounding polymer matrix (even for relatively small concentrations of additive; e.g. , 5–10% by volume) relative to the pure bulk matrix, thus leading to T g enhancement or suppression. Additives thus provide a potential route for modifying the properties of a polymer material without significantly changing its chemical composition. Here we apply the Limited Mobility (LM) model to simulate a matrix containing additive species. We show that both additive concentration, as well as the strength of its very local influence on the surrounding matrix material, will determine whether the T g of the system is raised or lowered, relative to the pure matrix. We demonstrate that incorporation of additives into the simple LM simulation method, which has successfully described the behavior of bulk and thin film glassy solids, leads to direct connections with available experimental and simulation results for a broad range of polymer/additive systems. 

Data continue to accrue indicating that experimental techniques may differ in their sensitivity to mobility and glassiness. In this work the Limited Mobility (LM) kinetic model is used to show that two metrics for tracking sample mobility yield quantitatively different results for the glass transition and mobile layer thickness in systems where free surfaces are present. Both LM metrics track the fraction of material that embodies mobile free volume; in one it is relative to that portion of the sample containing any kind (mobile and dormant) of free volume, and in the other it is relative to the overall sample. Without any kind of optimization, use of the latter metric leads to semi-quantitative agreement with experimental film results, both for the mobile layer thickness and the dependence of sample glass transition temperature on film thickness. Connecting the LM predictions with experiment also produces a semi-quantitative mapping between LM model length and temperature scales, and those of real systems.