Modeling and simulation play an important role in glass research, from understanding glass structure, to composition – property relations, to new composition and process design. This session will focus on atomistic simulation schemes and their applications to understand complex glass structures, and structural origin of properties. Other simulation methods, such as machine learning, big data and their applications in predictive modeling of glass properties will be covered. The topics will include, but are not limited to: Development of empirical potentials to simulate multicomponent glasses, e.g. glasses contain boron oxide and phosphorus oxide; study of glass/water reaction and interactions; simulation of mechanical behaviors of glasses; simulation of phase separation and crystal nucleation in glasses and melts; interfacial structure and behaviors of glass and other materials; and ab initio molecular dynamics simulations of glasses.
Session Organizers
- Jincheng Du, University of North Texas, USA, jincheng.du@unt.edu
- Walter Kob, University of Montpellier, France, walter.kob@umontpellier.fr
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