Quantitative Design of Glassy Materials Using Temperature-Dependent Constraint Theory

TLDR

Computational design of new materials is a long‑standing goal, yet accurate first‑principles prediction of glass properties is often infeasible because of computational limits, especially for borate glasses where boron coordination changes with network modifiers. The authors propose an analytical, topology‑based approach that uses a temperature‑dependent constraint model to predict dynamic properties of soda‑lime‑borate glasses. They develop a temperature‑dependent constraint model that maps the glass network topology to dynamic behavior, applied to the ternary soda‑lime‑borate system. The model’s predicted compositional trends match experimental data, enabling exploration of new glass compositions and uncovering the topological origins of properties such as liquid fragility.

Abstract

The computational design of new materials has long been a "holy grail" within the materials chemistry community. However, accurate prediction of glass properties from first principles is often impossible, because of computational restrictions. Here, we present an alternative analytical modeling approach that focuses on the topology of the glass network. Specifically, we demonstrate the use of a temperature-dependent constraint model to enable accurate prediction of dynamic properties, taking the ternary soda−lime−borate glassy system as an example. Borate glasses have posed a particular challenge for traditional molecular dynamics simulations, because of the change in boron coordination that occurs in the presence of network modifiers. Focusing on topological constraints instead of interatomic force fields, the calculated compositional trends with our model are in quantitative agreement with experimental measurements. Our modeling approach enables the exploration of new composition spaces of glassy materials and is proving to be a valuable tool for revealing the topological source of properties such as liquid fragility, which has been a longstanding problem in condensed matter science.