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MgCl 2 –NaCl–KCl (MgNaK) eutectic salt has emerged as a highly promising candidate for concentrated solar power (CSP), with extensive research conducted in recent years. However, the thermal property data for the MgNaK eutectic salt are still very limited. Here, we present a novel and accurate many-body potential trained by machine learning (ML) for MgNaK eutectic salt (with mole fractions of 45.4 %, 33 %, and 21.6 % respectively), developed using energies and forces extracted from first-principles molecular dynamics calculations (FPMD). The performance of the potential is well tested. We conduct a detailed investigation on the temperature-dependent structural and corresponding thermal properties, analyzing them from both the atomic and electronic perspectives. The introduction of Na+ or K+ ions disrupts the net structure formed by corner-joint and edge-joint MgCl x units, thereby affecting the transport properties. The calculated density (ρ) and constant pressure specific heat capacity (C P) exhibit agreement with experimental data within a margin of 2 %. We observe and discuss the typical λ of negative linear temperature correlation, which is similar to other molten alkali chloride salts. Finally, based on the simulated and experimental values, we provide reliable recommendations for the λ and viscosities (η) of MgNaK eutectic salt across its entire operating temperature range. [Display omitted] • An accurate machine learning-based many-body potential for MgNaK eutectic salt is developed. • The structural and thermophysical evolutions with temperature are discussed in detail from the atom and electronic levels. • Adding Na + or K+ ions loosens the network formed by MgCl x units, affecting transport properties. • The relationship between structure and thermo-physical properties is elucidated. • Reliable thermal conductivities and viscosities of MgNaK eutectic salt are recommended. [ABSTRACT FROM AUTHOR]

NaCl–CaCl 2 molten salt is considered as a promising high-temperature heat transfer and storage fluid for advanced nuclear power plants and concentrating solar power plants in the field of renewable energy utilization. However, the comprehensive physical properties and their microscopic mechanisms for the molten NaCl–CaCl 2 are failed to be measured accurately due to the extremely measuring condition. In this work, the ab-initio molecular dynamics simulation is used to investigate its microstructures and thermophysical properties for entire operating temperatures. It reveals that ion clusters are formed in terms of three for face-sharing, two for edge-sharing, and one for corner-sharing Cl− ions between the coordination shells of two neighboring cations. The coordination numbers of Na+-Cl- and Ca2+-Cl- ion pairs decrease from 5.88 to 6.46 at 783 K to 5.33 and 6.02 at 1173 K respectively. Meanwhile, the reliable and meaningful values of densities, ion self-diffusion coefficients, viscosities, and thermal conductivities were evaluated from 783 to 1173 K. It suggests that the distances and interactions between ions pairs determine thermodynamic properties directly. The ab-initio molecular dynamics simulation is proved to be an effective way to obtain the essential data for the designs of heat transfer and thermal energy storage systems in practical applications. • Ab-initio molecular dynamics simulations are applied for NaCl–CaCl 2. • Approach-to-equilibrium molecular dynamics method is used for thermal conductivity. • The correlation between microstructures and thermophysical properties are studied. • The distances and interactions between ion pairs determine its properties. [ABSTRACT FROM AUTHOR]

• A machine learning potential for ZnCl 2 -NaCl-KCl is developed for the first time. • The machine learning potential yields accurate microstructures near AIMD. • Adding Na+ and K+ deteriorate ZnCl 4 network and affect transport properties. • A weak negative temperature dependent thermal conductivity is noted and discussed. • Reliable experimental data of viscosity in the VTF form are recommended. ZnCl 2 -NaCl-KCl ternary salts are promising thermal storage and heat transfer fluid materials with a freezing point below 250 °C, thermal stability up to 800 °C, and other favorable properties that fit the use in the next generation concentrated solar thermal power. This work for the first time developed a machine learning-based interatomic potential for ZnCl 2 -NaCl-KCl ternary salt (0.6:0.2:0.2 in mole fraction) on the basis of energies and forces estimated by ab initio molecular dynamics calculations. The proposed machine learning potential was validated with the obtained partial radial distribution functions and the coordination numbers with the AIMD. The structural and thermophysical evolutions with temperature over the entire operating temperature range were documented. Adding Na+ and K+ ions deteriorated the network by corner-sharing and edge-sharing ZnCl 4 tetrahedra, and apparently affected self-diffusion coefficient, thermal conductivity, and viscosity of the melt. The calculated thermophysical properties agreed with experimental data. A negative temperature dependence of thermal conductivity was noted and discussed. Based on the experimental data, viscosity data by Li et al. and those of this work, yielded reliable experimental values in the Vogel-Tamman-Fulcher form. [ABSTRACT FROM AUTHOR]

• A machine learning potential for molten ZnCl 2 is developed for the first time. • The machine learning potential yields precise microstructures of molten ZnCl 2. • The IRO affects the bond angle and FSDP of partial structure factors. • Simulated thermophysical properties are in good agreement with experimental values. • A positive temperature dependent thermal conductivity is observed and discussed. Molten eutectic salts consisting of ZnCl 2 and other alkali chlorides are promising thermal storage and heat transfer fluid materials in the next generation concentrated solar thermal power. To go deep into the thermal and transport properties for a high order mixture, the microstructure information, as well as thermodynamics properties of individual components, have to be identified first. This work develops interatomic potentials of molten ZnCl 2 based on neural-network machine learning approach for the first time. The machine learning potential is trained by fitting to the energies and forces of liquid structures ab initio molecular dynamics calculations. The developed machine learning potential is validated by comparing partial radial distribution functions, coordination numbers, and partial structure factors with AIMD and PIM potential. The machine learning potential yields a more precise description of the microstructures than the PIM potential which suffers from the analytical form. Furthermore, structural and thermophysical evolution with temperature are studied and the results are in good agreement with experimental values. The efficient machine learning potential with DFT accuracy from our study will provide a promising scheme for accurate molecular simulations of structures and dynamics of molten ZnCl 2 mixtures. [ABSTRACT FROM AUTHOR]

• Molecular simulation is used to compute structures-properties of Na 2 CO 3 -K 2 CO 3. • Temperature and component dependence are studied from microscopic view. • The temperature-thermophysical properties-composition correlation are obtained. Molten carbonate eutectic salts are promising thermal storage and heat transfer fluid materials in solar thermal power plant with the feature of large specific heat capacity, wide operating temperature range and little corrosive. The high-temperature properties of molten carbonates should be determined accurately over the entire operating temperature for energy system design. In this paper, molecular dynamic simulation is used to study temperature and component dependence of microstructures and thermophysical properties of the binary carbonate molten salt. Negative linear temperature dependence of densities and thermal conductivities of binary mixtures of different components is confirmed with respect to the distances of ion clusters. Besides, positive linear temperature dependence of self-diffusion coefficient is also obtained. When temperature is constant, densities and thermal conductivities of binary mixtures are linearly related with components. Self-diffusion coefficients of CO 3 2− firstly increase and then decrease with increasing mole fraction of Na 2 CO 3. The temperature-thermophysical properties-composition correlation formulas are obtained, and the database of thermophysical properties of molten carbonate salts over the entire operating temperature is complemented, which will provide the essential data for heat transfer and storage system design, operation, and optimization in CSP. [ABSTRACT FROM AUTHOR]

• A workflow to construct solid-molten salt interaction potential is designed. • Deep potential could yield accurate solid-molten salt interaction at ab initio level. • Trends in interfacial heat transfer are correctly described by deep potential model. Interfacial heat and mass transfer properties at molten salt/solid interfaces are crucial for the study of heat storage/transfer properties of molten salt nanocomposite materials as well as the microscopic mechanism of thermophysical property enhancement, but accurate force field parameters for describing molten salt-solid interactions are still lacking. This study has utilized a workflow that could meet the demand of high accuracy and efficiency in molecular dynamics (MD) simulations of molten salt/solid interface with the deep potentials (DPs) trained by deep learning (DL), using SiO 2 /LiCl-KCl interface as a model system. In terms of the short-ranged polarizability and long-ranged correlations of ions, DPs can give accurate description of potential energy surface over wide temperature range at the level of ab initio calculations. Further analysis on interfacial thermal resistance (ITR) and thermal conductivity shows that the slowing down of heat transfer is related to the disordered microstructure of molten salt ions near the SiO 2 surfaces, which also leads to larger ITR. For the mass transfer of molten salt ions on the SiO 2 surfaces, the more active ionic diffusion and permeation through the solid can be observed due to the weaker adsorption between them, which is ascribed primarily to the high temperature. The workflow, of which the feasibility has been verified for molten salt/solid interfaces in this work with rigorous modeling, will be used for building accurate interatomic interaction models and calculating thermophysical properties for various complex interfacial systems containing molten salts. The influence of interfacial microstructure on heat and mass transfer will provide theoretical support for the application of molten salts in energy industry. [ABSTRACT FROM AUTHOR]

NaCl–CaCl 2 –MgCl 2 ternary molten salt is a potential material for thermal transfer and storage applications at high temperatures. In the present work, its microstructures and thermophysical properties over a wide operating temperature range were investigated by using ab-initio molecular dynamics simulations. An approach-to-equilibrium molecular dynamics method was used to calculate the thermal conductivity of molten salts. The local coordination structures and mechanisms of their temperature dependence were investigated. It can be found that the dominant bonding interactions are between cation-chlorine ion pairs, which can be considered as bridges connecting the local structures in liquids. The interaction between ions decreases with the increase of temperature as distances of ion clusters get larger. The thermophysical properties were evaluated in detail from 703 to 1173 K, showing a good accordance with the experimental data. A detailed relationship between operating temperature, microstructure, and thermophysical properties has been studied. The results suggest that the changes in thermodynamic properties with increasing temperature are caused by the variations of microstructures, in terms of the distances and bonding characteristics of ions. • Ab-initio molecular dynamics simulations are applied for NaCl–CaCl 2 –MgCl 2. • A pproach-to-equilibrium molecular dynamics method is used for thermal conductivity. • The relationship between operating temperature and properties has been studied. • Properties of molten salt are determined by the distances and interactions of ions. [ABSTRACT FROM AUTHOR]