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Ionic transport is a critical property for the glass industry, since emerging applications such as sensors, batteries, and electric melting are based on the phenomenon. Short-range interactions (anion-charge carrier) have not been able to explain the total activation barrier observed experimentally, and, as such, it is critical to understand the larger role of all ions in a glass, not just the carrier and the ‘site’ ions. This research focuses on the role of network formers and their impact on diffusion in glasses, something that current models lack an explicit explanation of. Atomistic simulations with randomly generated parameters for the cation potentials and classical simulations were used to determine the diffusion coefficients and activation energies for synthetic network formers. Using this database, explainable machine learning algorithms were employed to explore network former interactions and determine which parameters are the most influential for ion diffusion. Results suggest that the bond length of the cations changes the geometry of the structure contributing the greatest to cation-modifier interactions. 

Haven and Verkerk studied the diffusion of ions in ionic conductive glasses with and without an external electric field to better understand the mechanisms behind ionic conductivity. In their work, they introduced the concept now known as Haven’s ratio (H R ), which is defined as the ratio of the tracer diffusion coefficient (D self ) of ions to the diffusion coefficient from steady-state ionic conductivity (D σ ), calculated by the Nernst–Einstein equation. D σ can be challenging to obtain experimentally because the number of charge carriers has to be implied, a subject still under discussion in the literature. Molecular dynamics (MD) allows for direct measurement of the mean squared displacement ( r 2 ) of diffusing cations, which can be used to calculate D, avoiding the definition of a charge carrier. Using MD, the authors have calculated the r 2 of three alkali ions (Li, Na, and K) at different temperatures and concentrations in silicate glass, with and without the influence of an electric field. Results found for H R generally fell close to 0.6 at lower concentrations (x = 0.1) and close to 0.3 at higher concentrations (x = 0.2 and 0.3), comparable to the literature, implying that the electric field introduces new mechanisms for the diffusion of ions and that MD can be a powerful tool to study ionic diffusion in glasses under external electric fields.