Silica-based glasses: Realizing process-structure-property connections through computational modeling

Silica-based glasses are increasingly becoming vital components in our current technology, from optical data transmission lines, to electronics, to optical lenses, to smartphone screens. These materials are inherently brittle and subject to failure under shock, non-equilibrium stress states, or corrosive environments.  Identifying new compositions and processing conditions that result in improved fracture resistance (i.e. a higher fracture toughness) is achievable through materials design approaches. However, discovery primarily remains an empirically determined procedure.  Atomistic molecular dynamics can be a powerful tool in this application, providing a capability to probe how glass breaks and what compositions or microstructural features result in better material performance.  In this talk, a novel numerical method to determine the fracture toughness from atomistic material representations will be demonstrated on vitreous silica-based glass compositions. Process-structure-property connections will then be explored using this measure to highlight the relationships between processing conditions, chemical composition, microstructural content, and material performance.  Finally, an overview of the collaboration between the 2019-20 CGU Math Clinic team and Sandia National Laboratories will be discussed, where project goals are focused on using machine learning to predict fracture nucleation in silica glass.

Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.