We modeled a range of sodium thiophosphate glasses with composition x Na2S – (1-x) P2S5 (x = 0, 0.33, 0.5, 0.6, 0.67, 0.75). The glasses were formed using melt-quench technique and the calculated density of the glasses from simulations matched well (within 5%) with the experimentally measured value. We characterized the local structure of these glasses by calculating the radial pair distribution functions (RDF’s) from ab initio MD and compared it to those obtained through X-ray scattering experiments to validate the model. The FTIR and NMR characterization of these glasses help in identifying the different structural units dominating the local structure at a composition. We calculated the relative fractions of each of these structural units present in the different glasses and correlated the results to change in composition. The dominant structural units influence the ion transport in these glassy electrolytes. These atomistic simulations thereby allow us to predict the trend in ionic conductivity with composition. Our calculations indicate that an optimal room temperature ionic conductivity of ~ 10-6 S/cm is obtained at 75 Na2S – 25 P2S5 composition. A relatively high ionic conductivity (~ 10-5 S/cm) can be achieved at slightly elevated temperatures of around 60 °C, making these sodium thiophosphate glasses promising electrolytes for solid-state sodium ion batteries. Our calculations provide crucial insights into ion transport that can help develop solid electrolytes with high ionic conductivity.
We developed a kinetic Monte Carlo (kMC) model to scale up our calculations. Crucial inputs such as Na+ ions distribution and migration energies obtained from ab initio MD are the key inputs to this kMC model. This kMC model is able to predict the ionic conductivity of these glasses in agreement with experimental values. A separate Monte Carlo based model was developed to determine the charge-discharge plots for the entire battery employing these solid-state electrolytes. This novel multiscale approach of coupling atomistic simulations with Monte Carlo model provides an economical route for developing novel electrolytes for sodium ion batteries.