(103f) Exploring Low-Energy Regions of Glassy Potential Energy Landscapes

Glassy materials are ubiquitous in human life, with applications ranging from composites in computing chips to dense emulsions in the everyday hand soap. The complex physics and dynamics of glassy materials has puzzled scientists for long. The inability of glasses to equilibrate and find their lowest energy configurations is often attributed to their potential energy landscapes: rugged, barrier-filled surfaces in high-dimensional space that seem incredibly difficult to navigate. Further, the characteristic properties of system configurations deep in the energy landscape are fundamental to understanding questions surrounding the glass transition. In this study, we employ a modified metadynamics based algorithm, and report the surprising observation of canyon-like structures in high-dimensional glassy energy landscapes. Our algorithm successfully uses these canyons as navigational aids to access low energy states deep within the potential energy landscape. The earlier-noted rugged surfaces line the canyon floors with smooth canyon walls. The algorithm successfully overcomes local ruggedness and explores low-energy regions of the landscape. Further, we observe such canyons in three vastly different glassy systems, successfully sampling low energy configurations in each - while revealing fractal signatures in the landscape structure. Finally, we contrast our results with ones obtained using conventionally studied techniques like molecular dynamics and Monte Carlo based schemes, discussing the pros and cons of each.

Funding source acknowledgement: NSF DMR-1609525