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The development of reliable, yet computationally efficient interatomic forcefields is key to facilitate the modeling of glasses. However, the parameterization of novel forcefields is challenging as the high number of parameters renders traditional optimization methods inefficient or subject to bias. Here, we present a new parameterization method based on machine learning, which combines ab initio molecular dynamics simulations and Bayesian optimization. By taking the example of glassy silica, we show that our method yields a new interatomic forcefield that offers an unprecedented agreement with ab initio simulations. This method offers a new route to efficiently parameterize new interatomic forcefields for disordered solids in a non-biased fashion.
Topological constraint theory is a convenient theoretical framework to predict structure–property relationships in glasses and identify optimal compositions featuring targeted macroscopic properties. Although introduced for chalcogenide glasses, molecular rigidity concepts have since been applied with great success to new families of materials, such as silicate glasses, phase-change materials, and proteins. Here, we review recent developments in the extension of rigidity theory to concrete, which is by far the most heavily manufactured material in the world. By capturing the important atomic topology while filtering out less relevant structural details of calcium–silicate–hydrate, the binding phase of concrete, topological constraint theory was used to nanoengineer concrete from the atomic scale by predicting the compositional dependence of hardness, toughness, and creep. As such, rigidity concepts represent a promising tool to accelerate the discovery of new materials with tailored properties.
Understanding, predicting and eventually improving the resistance to fracture of silicate materials is of primary importance to design new glasses that would be tougher, while retaining their transparency. However, the atomic mechanism of the fracture in amorphous silicate materials is still a topic of debate. In particular, there is some controversy about the existence of ductility at the nano-scale during the crack propagation. Here, we present simulations of the fracture of three archetypical silicate glasses using molecular dynamics. We show that the methodology that is used provide realistic values of fracture energy and toughness. In addition, the simulations clearly suggest that silicate glasses can show different degrees of ductility, depending on their composition.
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