Abstract

Introduction The main purpose of this study is to simulate the ionic transport in the electrolytes of high-temperature molten-salt batteries using first-principles molecular dynamics techniques. Figures 1 and 2 show the configuration of a thermal battery in which what we concentrate on is the electrolyte. Figure 3 displays its overall chemical reaction to generate electricity. Our fundamental technique is based on the Hellmann-Feynman theorem which integrates the molecular dynamics (MD) simulation with the Density Functional Theory. Then we compare simulation results with experiments from leteratures to verify the pros and cons of different methods. First principles MD simulation technique is a powerful tool for evaluating ionic conductivity and to understand the interactions between each ion. Results and Discussion Figure 4 shows the molecular simulation model of the LiCl-KCl electrolyte. Its radial distribution function (RDF) is shown in Figure 5, which implies a stable molten structure and the phenomenon of ionic distributions. Figure 6 shows the mean square displacement (MSD) in different runs of the same case. It indicates that run-1 did not reach convergence. With continuous run-2 and run-3, a good converged mean square displacement is displayed. The ionic conductivity is related to the diffusion coefficient and is calculated by the Nernst-Einstein relation. The simulation results compared with experimental data are shown in Figure 7. Furthermore, Figure 8 shows the melting point prediction by cooling down the molten-salt electrolytes; the temperature at the discontinuous of the potential energy jump is recognized to be the melting point of electrolyte. Conclusion First-principles molecular dynamics simulation technique is an ab initio technique to simulate the ionic interaction from the very beginning without inputting a semi-empirical potential model. It is expected to build up a more complete software tool for designing the molten salt electrolytes to replace the costive trial-and-error experiments and to optimize the battery design in a more efficient way. Figure 1

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