Predicting the compositional evolution of the atomic-scale structure of oxide glasses is important for developing quantitative composition-property models. In binary phosphate glasses, the addition of network modifiers generally leads to depolymerization of the networks as described by the Q-speciation, where Q denotes PO tetrahedra with n number (between 0 and 3) of bridging P-O-P linkages per tetrahedron. Upon the initial creation of nonbridging oxygens and thus partly depolymerized Q species, a variety of network former-modifier interactions exist. Here, on the basis of P magic angle spinning nuclear magnetic resonance spectroscopy data from the literature, we present a statistical description of the compositional evolution of Q-speciation in these glasses by accounting for the relative enthalpic and entropic contributions to the bonding preferences. We show that the entire glass structure evolution can be predicted based on experimental structural information for only a few glass compositions in each series. The model also captures the differences in bonding preferences in glasses with different field strengths (charge-to-size ratio) of the modifier cations.

Due to an increasing demand for oxide glasses with a better mechanical performance, there is a need to improve our understanding of the composition-structuremechanical property relations in these brittle materials. At present, some properties such as Young's modulus can to a large extent be predicted based on the chemical composition, while others-in particular fracture-related properties-are typically optimized based on a trial-and-error approach. In this work, we study the mechanical properties of a series of 20 glasses in the quartenary Na 2 O-Al 2 O 3 -B 2 O 3 -SiO 2 system with fixed soda content, thus accessing different structural domains. Ultrasonic echography is used to determine the elastic moduli and Poisson's ratio, while Vickers indentation is used to determine hardness. Furthermore, the single-edge precracked beam method is used to estimate the fracture toughness (K Ic ) for some compositions of interest. The compositional evolutions of Vickers hardness and Young's modulus are in good agreement with those predicted from models based on bond constraint density and strength. Although there is a larger deviation, the overall compositional trend in K Ic can also be predicted by a model based on the strength of the bonds assumed to be involved in the fracture process. K E Y W O R D Scrack path, elastic moduli, fracture toughness, glass properties, Vickers hardness

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Predicting the compositional evolution of the atomic-scale structure and properties of oxide glasses is important for designing new materials for advanced applications. A statistical mechanics-based approach has recently been applied to predict the composition–structure evolution in binary phosphate glasses, while topological constraint theory (TCT) has been applied in the last decade to predict the structure–property evolution in various oxide and nonoxide glass systems. In this work, we couple these two approaches to enable quantitative predictions of the compositional dependence of glass transition temperature and the population of superstructural units. The object of the study is the lithium borate glass system because they feature interesting structural characteristics (e.g., boron anomaly), and ample structure and property data are available. In these glasses, the average coordination number of boron first increases when lithium modifiers are added and then later decreases accompanied by network depolymerization. First, on the basis of 10B nuclear magnetic resonance spectroscopy data from literature, we present a statistical description of the structural evolution in lithium borate glasses by accounting for the relative enthalpic and entropic contributions to the bonding preferences. We show that the entire glass structure evolution (both short- and intermediate-range) can be predicted based on experimental structural information for only a few glass compositions. We then show that the developed structural model can be combined with a previously established TCT model to predict the compositional evolution of the glass transition temperature. This work thus opens a new avenue for the computational design of glasses with tailored properties.

Predicting the atomic-scale structure of multicomponent glasses from their composition and thermal history would greatly accelerate the discovery of new engineering and functional glasses. A statistical mechanics-based approach has recently been applied to predict the composition-structure evolution in binary oxide glasses by determining the relative entropic and enthalpic contributions to the bonding preferences. In this work, we first establish the network modifier-former interaction parameters in sodium silicate and sodium borate glasses to predict the structural evolution in sodium borosilicate glasses. Due to the significant variations in the experimentally determined structural speciation in borosilicate glasses, we perform classical molecular dynamics (MD) simulations to establish and validate our structural model. We also show that the statistical mechanical model naturally accounts for the difference in structural speciation from MD simulations and NMR experiments, which in turn arises from the difference in cooling rate and thus thermal history of the glasses. Finally, we demonstrate the predictive capability of the model by accurately accounting for the structural evolution in potassium borosilicate glasses without using any adjustable model parameters. This is possible, because all the interaction parameters are already established in the potassium silicate, potassium borate, and sodium borosilicate glasses, respectively.