Modeling Metallic Halide Local Structures in Salt Melts Using a Genetic Algorithm

Knowing the local structure of metal ions in molten salt melts is essential for understanding the chemistry related to corrosion and solvation processes for various applications such as molten salt reactors, solar thermal power systems, and molten saltenabled materials processing. However, modeling the dynamic local structure of metals in salt melts is difficult because classical mechanics does not reproduce the correct local atomic networking. The computational cost of carrying out multiple first-principles dynamics calculations to ensure that the compositional space is well sampled can be prohibitively large. In order to address this issue, the current study explores the use of the evolutionary algorithm Universal Structure Predictor: Evolutionary Xtallography (USPEX) to predict coordination numbers of strontium and zirconium in binary and ternary chloride and fluoride melts. Temperaturedependent coordination number distributions for the metal atoms were computed using a Boltzmann distribution. The calculated average coordination numbers were found to be consistent with observations from extended X-ray absorption fine structure (EXAFS) experiments and the expected temperature trends. Furthermore, the most stable predicted crystal structures compare well with EXAFS values, validating our approach for predicting local structures in salt melts.

Automated summary

Understanding the local structure of metal ions in molten salt melts is crucial for various applications, but modeling this dynamic structure is challenging due to the limitations of classical mechanics. In this study, the researchers used the USPEX evolutionary algorithm to predict the coordination numbers of strontium and zirconium in chloride and fluoride melts. The results were consistent with experimental observations, validating the approach for predicting local structures in salt melts.