Glass Transition

The glass transition describes the non-equilibrium transformation of a liquid into a glassy solid upon cooling, a phenomenon lacking a complete theoretical understanding. Current research focuses on improving the prediction of glass transition temperatures and identifying characteristic structural features associated with this transition using techniques like machine learning (e.g., neural networks and random forests) and data-driven analysis of molecular dynamics simulations. These efforts aim to enhance the design and optimization of glassy materials across diverse applications, from polymers to nanomagnetic systems, by providing more accurate predictive models and a deeper understanding of the underlying physical mechanisms.