Structural determination of a molten (Li-K)Cl mixture of the eutectic composition by x-ray diffraction and molecular dynamics simulation

First-principles molecular dynamics study on the behaviors of Cs in a mixed system of liquid metal and LiCl-KCl molten salt

The structure and dynamic properties of Cs in the mixed system of LiCl-KCl molten salt and a liquid metal (Bi and Pb) electrode are investigated through first-principles molecular dynamics simulation. It is found that the dynamic properties of different ions in molten salt could be significantly affected when the liquid metal electrode is coupled and this influence varies with the type of liquid metal applied. The microstructures of the mixed systems of molten salt and liquid metal electrode: MS-Cs-Bi, MS-CsCl-Bi, MS-Cs-Pb, and MS-CsCl-Pb, are also investigated by the bond angle distribution function, Voronoi tessellation analysis, five-fold symmetry parameter, and bond-orientational order parameter. The comparison study of the microstructures of the mixed systems when different liquid metal electrodes are applied provides information on the liquid metal electrode selection when conducting electrolysis. The present study represents the first demonstration of the study of a mixed system of salt and liquid electrode for practical applications and would be greatly beneficial to the development of pyroprocessing of spent nuclear fuel.

Compositional transferability of deep learning potentials: a case study for LiCl-KCl melt

CONTEXT

One of the crucial issues related to machine learning potentials is the formation of representative dataset. For multicomponent systems, it is a general methodology to scan the composition range with a certain step. However, there is a lack of information on the compositional transferability of machine learning potentials. In this paper, we extend the knowledge in this area by studying the transferability of deep learning potential over the range of compositions of LiCl-KCl molten mixtures. The training dataset was formed using only the near-eutectic composition of 60% LiCl-40% KCl. Then, we tested the ability of the model to predict physicochemical properties of the melts far from the reference composition. It was found that for the composition range from 0 to 100% of LiCl, the calculated properties concur closely with those of other studies and ab initio calculations. Therefore, the model shows prominent non-intuitive compositional transferability. Moreover, the solid states and solid-liquid coexistence were reproduced. The calculated melting temperatures of LiCl and KCl show the errors of 6.6% and 0.4%, respectively. We argue that such good transferability stems from the local structure configurations that are typical both for pure LiCl and for pure KCl which are implicitly presented in the training dataset because of local fluctuations in composition.

METHODS

To collect the data for the initial dataset, density functional theory was employed. Then, the DeePMD package was used to train a neural network potential. To calculate the properties of the melts, standard equilibrium and non-equilibrium molecular dynamic approaches were utilized.

Coordination and Thermophysical Properties of Transition Metal Chlorocomplexes in LiCl-KCl Eutectic

Eutectic LiCl-KCl molten salt is often used in molten salt reactors as the primary coolant due to its high thermal capacity and high solubility of fission products. Thermophysical properties, such as density, heat capacity, and viscosity, are important parameters for engineering applications of molten salts but may be significantly influenced by metal solutes from corrosion of metallic structural materials. The behavior of the LiCl-KCl eutectic composition is well researched, yet the effects on these properties due to chlorocomplex formation from metals dissolved in the salt are less well known. These properties are often difficult to accurately measure from experimental methods due to the issues arising from the dissolved species, such as volatility. Here, we applied a combination of quantum mechanics molecular dynamics (QM-MD) and deep machine learning force field (DP-FF) molecular dynamics simulations to investigate the structural and thermophysical properties of LiCl-KCl eutectic as well as the influence of dissolved transition metal chlorocomplexes NiCl₂ and CrCl₃ at low concentrations. We find that the dissolution of Ni and Cr in the LiCl-KCl system forms the local tetrahedral (NiCl₄)^2- and octahedral (CrCl₆)^3- chlorocomplexes, respectively, which do not have a significant impact on the overall liquid salt structures. In addition, the thermodynamic properties including diffusion constant and specific heat capacity are not significantly affected by these chlorocomplexes. However, the viscosity significantly increases in the temperature range of 673-773 K. This study thus provides essential information for evaluating the effects of dissolved metals on the thermophysical and transport properties of molten salts.

Molten alkali halides – temperature dependence of structure, dynamics and thermodynamics

Temperature-induced structural, dynamical and thermodynamic changes reveal novel insights into the mechanism and dynamics of ion transport in molten salts.