Polymer NanoComposites, Interfaces and Data

For polymer composites, nanocomposites and polymer thin film systems, the local properties of polymers can be altered by the chemical and physical interactions with substrates and embedded particles over a substantial length scale. In order to better understand and design nanocomposites, polymer coatings and electronic components, it is essential to develop better understanding and robust design strategies. Two key missing links are understanding of altered polymer properties near surfaces/particles and ability to quantitatively leverage prior data for these systems, predictively in a robust manner. Therefore there is great interest in utilizing scanning probe methods to quantify the local property changes in the polymer region near surfaces. Additionally, there is great need to harvest, record and be able to learn from the vast amount of data archived in journal articles. In this work, both experimental characterization and development of a data framework and infrastructure is presented. The ability of Atomic Force Microscopy (AFM) to characterize the local mechanical properties (elastic and viscoelastic) of the interphase region in model composites is presented and combined with numerical simulations to refine the analysis. A new platform for data, analysis tools and simulation portals for polymer nanocomposites will be presented: NanoMine. NanoMine utilizes a robust schema to hold the data in a software infrastructure with query, visualization and microstructure analysis tools. Case studies are demonstrated which connect the property-structure-property domains through a combination of machine learning and physics-based modeling, demonstrating the ability to identify the most critical features influence properties.
Together this work illustrates a new approach to tackle materials design principles for the complex, high dimensional problems inherent in the multi-phase polymer space.