RESUMO
Many emerging materials, such as ultrastable glasses1,2 of interest for phone displays and OLED television screens, owe their properties to a gradient of enhanced mobility at the surface of glass-forming liquids. The discovery of this surface mobility enhancement3-5 has reshaped our understanding of the behaviour of glass formers and of how to fashion them into improved materials. In polymeric glasses, these interfacial modifications are complicated by the existence of a second length scale-the size of the polymer chain-as well as the length scale of the interfacial mobility gradient6-9. Here we present simulations, theory and time-resolved surface nano-creep experiments to reveal that this two-scale nature of glassy polymer surfaces drives the emergence of a transient rubbery, entangled-like surface behaviour even in polymers comprised of short, subentangled chains. We find that this effect emerges from superposed gradients in segmental dynamics and chain conformational statistics. The lifetime of this rubbery behaviour, which will have broad implications in constraining surface relaxations central to applications including tribology, adhesion, and surface healing of polymeric glasses, extends as the material is cooled. The surface layers suffer a general breakdown in time-temperature superposition (TTS), a fundamental tenet of polymer physics and rheology. This finding may require a reevaluation of strategies for the prediction of long-time properties in polymeric glasses with high interfacial areas. We expect that this interfacial transient elastomer effect and TTS breakdown should normally occur in macromolecular systems ranging from nanocomposites to thin films, where interfaces dominate material properties5,10.
RESUMO
Ultrasonic testing is widely used for defect detection in polymer composites owing to advantages such as fast processing speed, simple operation, high reliability, and real-time monitoring. However, defect information in ultrasound images is not easily detectable because of the influence of ultrasound echoes and noise. In this study, a stable three-dimensional deep convolutional autoencoder (3D-DCA) was developed to identify defects in polymer composites. Through 3D convolutional operations, it can synchronously learn the spatiotemporal properties of the data volume. Subsequently, the depth receptive field (RF) of the hidden layer in the autoencoder maps the defect information to the original depth location, thereby mitigating the effects of the defect surface and bottom echoes. In addition, a dual-layer encoder was designed to improve the hidden layer visualization results. Consequently, the size, shape, and depth of the defects can be accurately determined. The feasibility of the method was demonstrated through its application to defect detection in carbon-fiber-reinforced polymers.
RESUMO
The film thickness and substrate interface are the two most common parameters to tune the dynamics of supported thin films. Here, we investigated the glass transition temperature (Tg) and thermal expansion of thin poly(methyl methacrylate) (PMMA) films with various thicknesses and different interfacial effects. We showed that, although the Tg of the thin films can be modulated equivalently by the two factors, their ability to change the expansivity (ß) is quite different; that is, ß increases notably with a reduction in the thickness, while it is insensitive to perturbations at the interface. We attribute the deviation in modulating ß by the thickness and the interfacial effect to the disparate abilities to change the free volume content in the film by a free surface and substrate interface. This leads to a situation where thin films with dissimilar thicknesses and interfacial properties can have the same Tg but very different ß values, suggesting that Tg alone cannot unequivocally quantify thin film dynamics.