(354h) Ultra-Fragile “Granular Materials” Designed Via a Genetic Algorithm

Venkatesh Meenakshisundaram, Jui-Hsiang Hung, and David S. Simmons

Understanding glass formation behavior in soft matter materials such as polymers and colloids has held the interest of researchers for several decades and still remains a grand challenge. A key attribute to complexity of glass formation behavior is the local structure of these materials. While there are extensive studies using binary Lennard-Jones binary mixtures and Kremer-Grest model polymers to elucidate the role of local structures on glass formation, a conclusive answer is yet to be determined. In this work, we employ molecular dynamics simulations within the framework of a genetic algorithm to optimize shapes of coarse models, similar to granular materials, for largest fragility. Fragility is a measure of deviation from Arrhenius behavior at the glass transition temperature. We used four different systems in this study where granular materials were composed of 2, 3, 4, and 6 spherical beads. In general, the study revealed that the larger fragility can be achieved by increasing the number of beads within a granular material. The shapes determined for different systems in this study are non-intuitive and can provide further insights into role of local structures in glass formation. Shapes determined from this work can also be used as blueprint to develop macromers that can be polymerized to design new materials. This work is made possible by the generous funding of W. M. Keck foundation.