Predicting Q-Speciation in Binary Phosphate Glasses Using Statistical Mechanics

Modeling Oxygen Tricluster Formation in Calcium Aluminosilicate Supercooled Liquids and Glasses

Calcium aluminosilicate glasses have technological importance for a variety of industrial applications. However, the short-range structure of this glass system remains widely debated regarding the formation of oxygen triclusters. It is argued that triclusters are observed in high percentages within molecular dynamics simulations because of the high melting temperatures and correspondingly high fictive temperatures. This work explores the formation of such structural units by first simulating various compositions at different liquid temperatures to understand thermodynamic factors affecting the formation of such species. Structural results are then implemented into a statistical mechanical model which can predict the formation of triclusters at a given fictive temperature. Results show temperature and composition dependence of these structures, with aluminum charge modification favored in the peraluminous regime. It is concluded that oxygen triclusters are the preferred method of charge compensation even when extrapolating to laboratory fictive temperatures, indicating that triclusters are not a byproduct of simulation timescales.

Beyond the Average: Spatial and Temporal Fluctuations in Oxide Glass-Forming Systems

Atomic structure dictates the performance of all materials systems; the characteristic of disordered materials is the significance of spatial and temporal fluctuations on composition-structure-property-performance relationships. Glass has a disordered atomic arrangement, which induces localized distributions in physical properties that are conventionally defined by average values. Quantifying these statistical distributions (including variances, fluctuations, and heterogeneities) is necessary to describe the complexity of glass-forming systems. Only recently have rigorous theories been developed to predict heterogeneities to manipulate and optimize glass properties. This article provides a comprehensive review of experimental, computational, and theoretical approaches to characterize and demonstrate the effects of short-, medium-, and long-range statistical fluctuations on physical properties (e.g., thermodynamic, kinetic, mechanical, and optical) and processes (e.g., relaxation, crystallization, and phase separation), focusing primarily on commercially relevant oxide glasses. Rigorous investigations of fluctuations enable researchers to improve the fundamental understanding of the chemistry and physics governing glass-forming systems and optimize structure-property-performance relationships for next-generation technological applications of glass, including damage-resistant electronic displays, safer pharmaceutical vials to store and transport vaccines, and lower-attenuation fiber optics. We invite the reader to join us in exploring what can be discovered by going beyond the average.

Role of Ag+ Ions in Determining Ce3+ Optical Properties in Fluorophosphate and Sulfophosphate Glasses

Understanding the interactions among dopant species and the role of the host lattice is of fundamental importance for the chemical formulation of optically active glasses. Here, we consider the archetypal dopant pair of Ag-Ce in complex fluorophosphate (PF) and sulfophosphate (PS) matrices, in which variable bonding environments and ligand selectivity exert distinct effects on dopant properties. The addition of Ag⁺ to PF glasses blue-shifts the ultraviolet (UV) cutoff wavelength of Ce³⁺ and enhances its photoluminescence (PL) intensity. In PS matrices, the exact opposite effect is observed: red-shifting the UV cutoff and lowering the PL intensity. No Ag-Ag pairs or cluster species were found in either matrix material; however, in PS, such clustering could be triggered by secondary broad-band UV-visible irradiation. The optical properties of Ag-Ce-codoped glasses are a result of the ionocovalent character of the Ag⁺-O-Ce³⁺ bond, the cross-relaxation process between Ag⁺ and Ce³⁺, and the redox ratio of Ce³⁺/Ce⁴⁺. In the PF glasses, the enhancement of the Ce³⁺ PL intensity is due to energy transfer from Ag⁺ to Ce³⁺ and a redox shift from Ce⁴⁺ to Ce³⁺. The more covalent Ag⁺-O-Ce³⁺ interactions in the PS series decrease the Ce³⁺/Ce⁴⁺ ratio. Moreover, photoinduced Ag clustering is facilitated in the more covalent environment, which indicates that glasses commonly used for Ag nanoparticle formation, such as silicate glasses, also possess more covalent Ag⁺-O bonding.

Mixed Alkali Effect in Silicate Glass Structure: Viewpoint of 29Si Nuclear Magnetic Resonance and Statistical Mechanics

The mixed alkali effect in glasses is the deviation from linear property changes when alkali cations are mixed. The extent of this effect and its structural origin remain topics of interest. In this work, we use a statistical mechanics approach to predict the composition-structure relationship in mixed modifier Na₂O-K₂O-SiO₂ glasses. This is achieved by accounting for the enthalpy between each pairwise alkali ion and silicate unit interaction. The initial enthalpy parameters are obtained based on experimental structural data for binary Na₂O-SiO₂ and K₂O-SiO₂ glasses, which can be transferred to predict the short-range order structure of mixed modifier glasses without additional free parameters. To this end, we have performed ²⁹Si magic angle spinning NMR spectroscopy measurements on y(xNa₂O-(1 - x)K₂O)-(100 - y)SiO₂ glasses with x = 0, 0.25, 0.5, 0.75, and 1 and y = 34, 42, and 50. Good agreement between experimental data and model predictions are observed. Finally, we use this information to discuss the relative entropic and enthalpic contributions to the mixed modifier effect in silicate glass structure.

Statistical Mechanical Model of Topological Fluctuations and the Intermediate Phase in Binary Phosphate Glasses

Glasses are topologically disordered materials with varying degrees of fluctuations in structure and topology. This study links statistical mechanics and topological constraint theory to quantify the degree of topological fluctuations in binary phosphate glasses. Because fluctuations are a potential mechanism enabling self-organization, we investigated the ability of phosphate glasses to adapt their topology to mitigate localized stresses, e.g., in the formation of a stress-free intermediate phase. Results revealed the dependency of both glass composition and temperature in governing the ability of a glass network to relax localized stresses and achieve an ideal, isostatic state; also, the possibility of a second intermediate phase at higher modifier content was found.

Statistical Mechanical Modeling of Borate Glass Structure and Topology: Prediction of Superstructural Units and Glass Transition Temperature

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.