Authors: Maggie Wu, Ashley Littlefield, Bryant Jones
Mentors: Bryant Jones
Insitution: Snow College
A novel method of predictive thermodynamic property mining using AIMD simulations of molten salts for use in molten salt nuclear reactors
Solving the worlds energy crisis has been a heavily debated and researched topic for many years. One proposed solution to this problem is the micro molten salt nuclear reactor (MMSR). The MMSR is a small portable nuclear powerplant that can provide an affordable source of energy that is completely safe, readily available, and passively controlled. The waste products from this reactor are also heavily sought medically important isotopes. One final hurdle for MMSR development is the mining of the thermodynamic properties for previously unstudied eutectic mixtures of molten salts.
Due to the hygroscopic nature of molten salt eutectics, experimental techniques for measuring thermodynamic properties are time and cost prohibitive. Modern supercomputing techniques provide a solution for property mining. However, computational methods have been historically limited to previously experimentally studied salts. There has always been a need for experimentally measured values to be determined first to provide tuning for the computational techniques. This group has developed a novel technique for tuning the values for previously unstudied salts. This greatly enhances the predictive capabilities of computation methods. This technique was then employed to successfully measure the density, Heat capacity, and coefficient of thermal expansion for two promising uranium salt eutectics. These studies provided the data to also study the molecular structure of these salts. This study showed interesting new aggregation of the uranium atoms that will be presented.