Abstract
The use of molten salts as coolants, fuels, and tritium breeding blankets in the next generation of fission and fusion nuclear reactors benefits from furthering the characterization of the molecular structure of molten halide salts, paving the way to predictive capability of the chemical and thermophysical properties of molten salts. Due to its neutronic, chemical, and thermochemical properties, 2- is a candidate molten salt for several fusion- and fission-reactor designs. We performed neutron and x-ray total-scattering measurements to determine the atomic structure of liquid 2-. We also performed ab initio and neural-network molecular-dynamics simulations to predict the structure obtained by neutron- and x-ray-diffraction experiments. The use of machine learning provides improvements to the efficiency in predicting the structure at a longer length scales than is achievable with ab initio simulations at significantly lower computational expense while retaining near ab initio accuracy. We found that the NNMD simulations accurately predicted the oligomer formations seen in the experimental first-structure-factor peak. Our combination of high-resolution measurements with large-scale molecular dynamics provided an avenue to explore and experimentally verify the intermediate-range ordering beyond the first-nearest neighbor that has posed too many experimental and computational challenges in previous works. With a deeper understanding of the salt structure and ion ordering, the evolution of salt chemistry over the lifetime of a reactor can be better predicted, which is crucial to the licensing and operation of advanced fission and fusion reactors that employ molten salts. To this end, this work will serve as a reference for future studies of salt structure and macroscopic properties with and without the addition of solutes.
- Received 15 August 2023
- Revised 10 November 2023
- Accepted 29 November 2023
DOI:https://doi.org/10.1103/PRXEnergy.3.013001
Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.
Published by the American Physical Society
Physics Subject Headings (PhySH)
Popular Summary
The use of molten salts in energy applications has seen revitalized interest due to their favorable use in the next generation nuclear reactors aimed at decarbonizing the energy sector. Molten salt reactors were initially developed and tested as part of the Molten Salt Reactor Experiment (MSRE) at Oak Ridge National Laboratory in the 1960s. Using molten salts as coolant fluid and as the carrier of the fissile material enables passive safety systems and improves the thermal performance. These salts, however, interact with the construction materials and fission products causing corrosion and material degradation. Molecular dynamics simulations predict the thermal and chemical properties of the salts and their interaction with materials. The accuracy of their predictions depends on an accurate structural prediction. In this work, the authors experimentally measure the liquid structure of 2LiF-BeF2 using both neutrons and X-rays and perform large scale molecular dynamics simulations that incorporate the use of machine learning. The authors found good agreement between experiments and simulations and experimentally verified the intermediate-range structure that had previously been out of reach. These results will serve as a foundation for further development of molecular dynamics predictions required to employ salts in energy applications.
