Partial Radial Distribution Functions Research Articles

Temperature-dependent local structure and lattice dynamics of 1T-TiSe[formula omitted] and 1T-VSe[formula omitted] probed by X-ray absorption spectroscopy

The local atomic structure and lattice dynamics of two isostructural layered transition metal dichalcogenides (TMDs), 1T-TiSe2 and 1T-VSe2, were studied using temperature-dependent X-ray absorption spectroscopy at the Ti, V, and Se K-edges. Analysis of the extended X-ray absorption fine structure (EXAFS) spectra, employing reverse Monte Carlo (RMC) simulations, enabled tracking of the temperature evolution of the local environment in the range of 10–300 K. The atomic coordinates derived from the final atomic configurations obtained using the RMC method were used to calculate the partial radial distribution functions (RDFs) and the mean-square relative displacement (MSRD) factors for the first ten coordination shells around the absorbing atoms. Characteristic Einstein frequencies and effective force constants were determined for TiSe, TiTi, VSe, VV, and SeSe atom pairs from the temperature dependencies of MSRDs. The obtained results reveal differences in the temperature evolution of lattice dynamics and the strengths of intralayer and interlayer interactions in TiSe2 and VSe2.

Evidence of local structural distortions and subtle thermal disorder in transparent photochromic yttrium oxyhydride

The structural properties of photochromic yttrium oxyhydride powder in its transparent state were examined using x-ray diffraction and temperature-dependent extended x-ray absorption fine structure spectroscopy (EXAFS) combined with reverse Monte Carlo (RMC) simulations. The refinement of the x-ray powder diffraction pattern, employing the Rietveld method, indicates that yttrium oxyhydride crystallizes in the nanocrystalline phase with the cubic space group Fm-3m (225), at room temperature. The lattice parameter was determined as a = 5.404(3) Å, and the nanocrystallite size was estimated at d = 16(2) nm. The partial radial distribution functions (RDFs) g(r) for Y–O, O–O, and Y–Y atom pairs were obtained from the results of the RMC simulations of the Y K-edge EXAFS spectra measured at three temperatures (10, 150, and 300 K). The analysis of the RDFs reveals a subtle impact of the thermal disorder and splitting of the second coordination shell of yttrium atoms (the Y–Y RDF), remaining at all temperatures. This observation, also supported by our density functional theory calculations, suggests the presence of local structural distortions associated with yttrium sites, which do not affect the long-range crystal order.

Alkali hydroxide (LiOH, NaOH, KOH) in water: Structural and vibrational properties, including neutron scattering results.

Structural and vibrational properties of aqueous solutions of alkali hydroxides (LiOH, NaOH, and KOH) are computed using quantum molecular dynamics simulations for solute concentrations ranging between 1 and 10M. Element-resolved partial radial distribution functions, neutron and x-ray structure factors, and angular distribution functions are computed for the three hydroxide solutions as a function of concentration. The vibrational spectra and frequency-dependent conductivity are computed from the Fourier transforms of velocity autocorrelation and current autocorrelation functions. Our results for the structure are validated with the available neutron data for 17M concentration of NaOH in water [Semrouni et al., Phys. Chem. Chem. Phys. 21, 6828 (2019)]. We found that the larger ionic radius [rLi+<rNa+<rK+] and higher concentration disturb the hydrogen-bond network of water, resulting in more disordered cationic hydration shell. Our abinitio simulation data for solute concentrations ranging between 1 and 10M can be used to guide future elastic and inelastic neutron-scattering experiments.

Artificial neural network for deciphering the structural transformation of condensed ZnO by extended x-ray absorption fine structure spectroscopy

Pressure-induced structural phase transitions play a pivotal role in unlocking novel material functionalities and facilitating innovations in materials science. Nonetheless, unveiling the mechanisms of densification, which relies heavily on precise and comprehensive structural analysis, remains a challenge. Herein, we investigated the archetypal B4 → B1 phase transition pathway in ZnO by combining x-ray absorption fine structure (XAFS) spectroscopy with machine learning. Specifically, we developed an artificial neural network (NN) to decipher the extended-XAFS spectra by reconstructing the partial radial distribution functions of Zn–O/Zn pairs. This provided us with access to the evolution of the structural statistics for all the coordination shells in condensed ZnO, enabling us to accurately track the changes in the internal structural parameter u and the anharmonic effect. We observed a clear decrease in u and an increased anharmonicity near the onset of the B4 → B1 phase transition, indicating a preference for the iT phase as the intermediate state to initiate the phase transition that can arise from the softening of shear phonon modes. This study suggests that NN-based approach can facilitate a more comprehensive and efficient interpretation of XAFS under complex in-situ conditions, which paves the way for highly automated data processing pipelines for high-throughput and real-time characterizations in next-generation synchrotron photon sources.

Estimation of Activity and Molar Excess Gibbs Energy of Binary Liquid Alloys Pb-Sn, Al-Sn and In-Zn from the Partial Radial Distribution Function Simulated by Ab Initio Molecular Dynamics

For the present, it is difficult to obtain thermodynamic data for binary liquid alloys by experimental measurements. In this study, the molecular dynamics processes of the binary liquid alloys Pb50-Sn50, Al50-Sn50, and In50-Zn50 were simulated by using the ab initio molecular dynamics (AIMD) principle, and their partial radial distribution functions (PRDF) were obtained at different simulation steps. Combined with the relevant binary parameters of the Molecular Interaction Volume Model (MIVM), Regular Solution Model (RSM), Wilson Model, and Non-Random Two-Liquid (NRTL) models. The integral terms containing the PRDF were computed using the graphical integration method to obtain the parameters of these models, thus estimating their activity and molar excess Gibbs energy. The total average relative deviations (ARD) of the activity and molar excess Gibbs energy estimates of the four models for the binary liquid alloys Pb50-Sn50, Al50-Sn50, and In50-Zn50 at full concentration when the PRDF is obtained by the symmetry method are MIVM: 21.59% and 59.35%; RSM: 21.63% and 60.27%; Wilson: 24.27% and 86.7%; NRTL: 23.9% and 83.24%. When the PRDF is obtained by the asymmetric method: MIVM: 22.86% and 68.08%; RSM: 32.84% and 68.66%; Wilson: 25.14% and 82.75%; NRTL: 24.49% and 85.74%. This indicates that the estimation performance of the MIVM model is superior to the other three models, and the symmetric method performs better than the asymmetric method. The present study also derives and verifies the feasibility of Sommer’s equation for estimating the molar excess Gibbs energy and activity of binary liquid alloy systems in the Miedema model by using different equations of enthalpy of mixing versus excess entropy given by Tanaka, Ding, and Sommer. The total ARD of Tanaka, Ding, and Sommer’s relational equations in the Miedema model for estimating the activities and molar excess Gibbs energies of the binary liquid alloys Pb-Sn, Al-Sn, and In-Zn are 3.07% and 8.92%, 6.09% and 17.1%, and 4.1% and 14.77%. The results indicate that the estimation performance of the Miedema model is superior to the other four models.

Conformational and static properties of tagged chains in solvents: effect of chain connectivity in solvent molecules.

Polymer chains immersed in different solvent molecules exhibit diverse properties due to multiple spatiotemporal scales and complex interactions. Using molecular dynamics simulations, we study the conformational and static properties of tagged chains in different solvent molecules. Two types of solvent molecules were examined: one type consisted of chain molecules connected by bonds, while the other type consisted of individual bead molecules without any bonds. The only difference between the two solvent molecules lies in the chain connectivity. Our results show a compression of the tagged chains with the addition of bead or chain molecules. Chain molecule confinement induces a stronger compression compared to bead molecule confinement. In chain solvent molecules, the tagged chain's radius of gyration reached a minimum at a monomer volume fraction of ∼0.3. Notably, the probability distributions of chain size remain unchanged at different solvent densities, irrespective of whether the solvent consists of beads or polymers. Furthermore, as solvent density increases, a crossover from a unimodal to a bimodal distribution of bond angles is observed, indicating the presence of both compressed and expanded regions within the chain. The effective monomer-solvent interaction is obtained by calculating the partial radial distribution function and the potential of the mean force. In chain solvents, the correlation hole effect results in a reduced number of nearest neighbors around tagged monomers compared to bead solvents. The calculation of pore size distribution reveals that the solvent nonhomogeneity induced by chain connectivity leads to a broader distribution of pore sizes and larger pore dimensions at low volume fractions. These findings provide a deeper understanding of the conformational behavior of polymer chains in different solvent environments.

Molecular Dynamics Study on the Formation of Ordered Arrangement of Ba-Ba Atomic Pairs in the SiO2-Al2O3-CaO-BaO Glass-Ceramic

In this study, the barium–calcium aluminosilicate (BaO-CaO-Al2O3-SiO2) glass-ceramic system (BCAS) was modelled by using classical molecular dynamics (MD) simulation method based on Born–Mayer–Huggins (BMH) potential for interatomic interactions. The model system was heated to 5000 K and cooled to 300 K for obtaining a glassy structure. Then the temperature of the system was increased to 400 K, 500 K and 600 K temperatures for observing more ordered structure. For understanding of order formation, the structural development was analyzed by partial radial distribution function (PRDF). The results demonstrated that the PRDF peaks of Ba-Ba became sharper than other bond pairs with the increasing of annealing temperature. These sharp peaks at distant atomic distances represent the occurrence of ordered arrangement in Ba-Ba interactions.

Estimation of Activity and Molar Excess Gibbs Energy of Binary Liquid Alloys Al-Cu, Al-Ni, and Al-Fe from the Partial Radial Distribution Function Simulated by Ab Initio Molecular Dynamics

To accurately and conveniently obtain the thermodynamic data of binary liquid alloys, a new method is proposed in this study. It combines ab initio molecular dynamics (AIMD) simulation with a thermodynamic model to estimate the activity and molar excess Gibbs energy of binary liquid alloys. Additionally, two methods of grouping the partial radial distribution function (PRDF) of 5000 steps obtained by simulation are proposed for the first time. The PRDF of Al50Cu50, Al50Ni50, and Al50Fe50 is obtained by AIMD simulation. These PRDF are combined with four thermodynamic models to estimate the activity and molar excess Gibbs energy. Furthermore, the estimation results of the four models are compared with those of the Miedema model. The results show that when the first peak of the PRDF is obtained by the symmetric method, the average relative deviation (ARD) of the activity and molar excess Gibbs energy of the four models are, respectively: 28% and 32% for Molecular Interaction Volume Model (MIVM); 162% and 38% for Regular Solution Model (RSM); 508% and 65% for Wilson model; 562% and 67% for Non-Random Two-Liquid (NRTL). When the first peak of PRDF is obtained by non-symmetric method, the average ARD of the activity and molar excess Gibbs energy of the four models are, respectively: 64% and 20% for MIVM; 115% and 26% for RSM; 661% and 70% for Wilson; 727% and 72% for NRTL. In addition, the average ARD of the activity and molar excess Gibbs energy of the Miedema model are 113% and 33%. These data indicate that the estimation performance of the MIVM model is superior to the other four models, and the symmetric method performs better than the non-symmetric method. The grouping treatment of PRDF data effectively improves estimation performance.

Static and Dynamic Properties of SPC/E Water Model

In this work, we have studied static and dynamic properties of bulk water using SPC/E water model. We have considered 1500 water molecules confined to a three dimensional box. LAMMPS software has been used to perform molecular dynamic simulation under canonical ensemble. The partial radial distribution functions, diffusion coefficients, velocity autocorrelation functions, and mean square displacements have been calculated at 300K for different densities ranging from 900 kg/m3 to 1000 kg/m3. The principle peak heights of the partial radial distribution functions are found to decrease with increase in high density regime showing abnormal behaviour in this density regime.

Estimation of Two Component Activities of Binary Liquid Alloys by the Pair Potential Energy Containing a Polynomial of the Partial Radial Distribution Function

An investigation of partial radial distribution functions and atomic pair potentials within a system has established that the existing potential functions are rooted in the assumption of a static arrangement of atoms, overlooking their distribution and vibration. In this study, Hill’s proposed radial distribution function polynomials are applied for the pure gaseous state to a binary liquid alloy to derive the pair potential energy. The partial radial distribution functions of 36 binary liquid alloy from literatures were used to obtain the binary model parameters of four thermodynamic models for validation. Results show that the regular solution model (RSM) and molecular interaction volume model (MIVM) outperform other models when the asymmetric method calculates the partial radial distribution function. RSM demonstrates an average SD of 0.078 and an ARD of 32.2%. Similarly, MIVM exhibits an average SD of 0.095 and an average ARD of 32.2%. Wilson model yields an average SD of 0.124 and an average ARD of 226%. Nonrandom two-liquid (NRTL) model exhibits an average SD of 0.225 and an average ARD of 911%. On applying the partial radial distribution function symmetry method, MIVM and RSM outperform the other models, with an average SD of 0.143 and an average ARD of 165.9% for MIVM. RSM yields an average SD of 0.117 and an average ARD of 208.3%. Wilson model exhibits average values of 0.133 and 305.6% for SD and ARD, respectively. NRTL model shows an average SD of 0.200 and an average ARD of 771.8%. Based on this result, the influence of the symmetry degree on the thermodynamic model is explored by examining the symmetry degree as defined by the experimental activity curves of the two components.

Evolution of Structure and Dynamic of Simulated CdTe Model According to the Melting Process

CdTe model containing 9955 atoms was built and simulated by the method of molecular dynamics (MD) with the Stillinger–Weber (SW) potential. The model was obtained by heating from 300K to 3000K at a rate of 1013 K/s. The structural properties of the model are investigated through the total energy per atom, the partial radial distribution functions (PRDFs), the coordination number distributions and the bond-angle distributions. Calculation results have shown that the model has a melting point of about 1370K and changes from tetrahedral to octahedral structure when the temperature of CdTe model is above the melting point. These results are consistent with the reported experimental and simulation results. In addition, the mobility of Cd and Te atoms is also researched through the mean squared displacement (MSD) and the diffusion coefficients of Cd and Te atoms.

Bulk metallic glass Al2Ca from a biomedical application viewpoint: A molecular dynamics study

Molecular dynamics simulations were performed to investigate the glass transition temperature (Tg) and mechanical properties of Al–Ca-based bulk metallic glass (BMG), Al2Ca. The second-neighbour modified embedded atom method potential was used to simulate the system. We estimate the Tg between 600 to 660 K. To ensure the glassy state of the studied material, the total radial distribution function (RDF) has been calculated from 300 to 1500 K. Partial RDF for Al, Ca, and Al–Ca subsystems are also calculated. Elastic properties including bulk modulus, compressibility, Young’s modulus, shear modulus, tensile yield strength and Poisson ratio are calculated. From the obtained data of elastic constants, it is concluded that Al2Ca BMG can be the potential material to be used in the biomedical field.

Automated potential development workflow: Application to BaZrO3

We present a Python workflow, Automated Potential Development (APD), for automating the development of interatomic potentials, including calculation of density functional theory (DFT) fitting data, optimization of potentials, and potential-driven molecular dynamics (MD) simulations. The workflow currently supports CASTEP and VASP DFT codes and the MEAMfit potential optimization code for optimization of reference-free modified embedded atom method (RF-MEAM) potentials. The LAMMPS software is supported for calculating the relaxed geometry, elastic constants, phonon dispersion, thermal expansion and radial distribution functions using the optimized potentials. These same properties are also computed at the DFT level and APD automatically generates plots and tables of these data. Query-by-committee active learning is supported, using multiple fitted potentials to evaluate the energies of atomic configurations generated from LAMMPS MD runs. The workflow is demonstrated on BaZrO3, an oxide-based perovskite material, with RF-MEAM results found in good agreement with DFT. Program summaryProgram title: Automated potential development (APD) workflowCPC Library link to program files:https://doi.org/10.17632/pd9gbxyy8d.1Developer's repository link:https://gitlab.com/AndyDuff123/meamfitLicensing provisions: BSD 3-clauseProgramming language: Python, BashNature of problem: Development of new interatomic potentials is a time-consuming process and requires expertise in density functional theory (DFT), potential optimization, and molecular dynamics (and statics) simulations using the optimized potential. Furthermore repeated cycles are usually required to fix numerical issues and improve the potential, requiring further DFT calculations and potential reoptimization. There are also many tedious steps including setting up inputs, submitting jobs (including continuation jobs where jobs terminated prematurely), analyzing outputs, and validating predictions of the interatomic potential. The latter requires multiple calculations of properties computed at both the DFT and potential level.Solution method: The APD workflow provides a black-box solution to fully automate the generation of interatomic potentials. The workflow takes as input a Materials Project id and temperature range of interest. All DFT, potential optimization, and potential molecular dynamics simulations are automatically set-up, submitted and analyzed. Active-learning is incorporated, and properties are computed both at the DFT and potential-level for validation purposes, with tables and graphs for relaxed geometry, elastic constants, phonon dispersion, partial radial distribution functions, and thermal expansion automatically generated.Additional comments including restrictions and unusual features: A full guide to installation, including setting up an environment with all relevant packages and libraries, are included in the distribution. The APD workflow is currently restricted to RF-MEAM potentials and the properties listed above. Some materials which are particularly challenging at the DFT level, e.g. complex magnetic structures, may require intervention in tuning DFT input parameters.

Effect of composition and temperature on microstructure and thermophysical properties of LiCl-CaCl2 molten salt based on machine learning potentials

LiCl-CaCl2 molten salt is a promising candidate for storing and converting energy and capturing CO2. The machine learning potential molecular dynamics simulations have high efficiency and accuracy and can overcome the disadvantages of classical molecular dynamics simulations and first-principles molecular dynamics simulations. Therefore, this study applied machine learning potential molecular dynamics simulations to investigate the microstructure change and thermophysical properties of LiCl-CaCl2 molten salt in response to temperature and composition. Partial radial distribution function, coordination number distribution, and angular distribution function were used for microstructural analysis. It is found that the local structure of LiCl-CaCl2 molten salt hardly changed with temperature rise. However, it suffered from serious octahedral distortion with the increased CaCl2 content from 20% to 80%. Thermophysical properties of LiCl-CaCl2 molten salt were systematically analyzed, including density, self-diffusion coefficient, shear viscosity, electrical conductivity, thermal expansion coefficient, and specific heat capacity. The relationships between properties and temperature or CaCl2 mole fraction were fitted. In conclusion, this study can provide a novel and efficient approach to investigating molten salt in-depth and enrich the data of fundamental properties of LiCl-CaCl2 molten salt.

Amorphous Zirconia-doped Tantala modeling and simulations using explicit multi-element spectral neighbor analysis machine learning potentials (EME-SNAP)

We model amorphous Zirconia-doped Tantala with machine learning interactomc potentials based on explicit multielement spectral neighbor analysis (EME-SNAP). These atomic structure models can reproduce partial radial distribution functions obtained from first-principles calculations and elastic moduli found from experimental measurements. The two-body pair forces calculated from EME-SNAP further affirm that the potentials capture the atomic interactions well. Molecular dynamics simulations of simulated annealing with EME-SNAP show that the final density of the amorphous models depends on the thermal history even when the annealing rate is kept constant, which captures experimental observations of history-dependent densities. Mechanical spectroscopy is also simulated using both Morse-Beest-Kramer-Santen pair potentials and EME-SNAP. The success in applying the EME-SNAP to amorphous Zirconia-doped Tantala pushes the boundaries of simulation accuracy and system size and enables better and more realistic atomistic modeling for amorphous systems. There are still some limitations in applying the potentials generated in this paper. They are only optimized for trained amorphous phases; high-temperature stability and transferability need to be further investigated.

Effect of silver nanoparticle volume fraction on thermal conductivity, specific heat and viscosity of ethylene glycol base silver nanofluid: A molecular dynamics investigation

Using molecular dynamics (MD) simulation, the effect of temperature and Ag nanoparticles volume fraction in Ethylene Glycol (EG) base fluid is investigated in the context of some thermophysical properties like thermal conductivity (TC), viscosity, and specific heat. The 12–6 Lennard-Jones (LJ) potential is considered to model the Van der Walls interaction between the atoms of the nanofluid. The ability of nanoparticles to change the characteristics of a fluid is determined by its diffusive qualities relative to the fluid. TC of the base fluid increases with temperature. The enhancement of the relative TC to the base fluid TC (knf/kbf) is due to the reduction of the condensation of the fluid surrounding the nanoparticle. We also show that viscosity increases with volume fraction but reduces with temperature. Moreover, a nonlinear increment of TC and Viscosity with volume fraction is seen, which is consistent with the results of different models. Mean square displacement (MSD) calculation is performed to understand the mechanism of thermal conductivity enhancement. It is observed that viscosity decreases nonlinearly with increasing particle diameter from 1.1 nm to 1.5 nm. To gain a better understanding of the local structure and organization of the studied system total and partial radial distribution functions (RDFs) are investigated. The results provide important information regarding the properties of the nanofluid (EG + Ag) with respect to concentration, temperature etc. As EG is a more complex structure and lower freezing point than water, so we try to simulate this base fluid with a high TC nanoparticle (Ag), because, till now, maximum simulations are performed on Argon or water-based nanofluid.

First‐Principles Molecular Dynamics Study on Ionic Structure and Transport Properties of NaCl‐MgCl2‐CaCl2 Ternary Molten Salt System

AbstractThe carbochlorination in molten salt is an effective method for titanium extraction form low‐grade titanium slag with a high calcium and magnesium content. However, in industrial practice, the fluidity of molten salt will gradually decrease with the increase of CaCl2 content. It is important to elucidate the influencing mechanism of CaCl2 content on the microstructure and diffusion properties of molten salt for the rational selection of a molten salt system and clean utilization of titanium slag. In this study, the densities of molten salt systems with different CaCl2 contents are measured according to the Archimedes principle. Then, using the first‐principles molecular dynamics (FPMD) method, the ionic structure and transport properties of NaCl‐MgCl2‐CaCl2 ternary molten salt systems under different CaCl2 contents are qualitatively and quantitatively described by determining the partial radial distribution functions (PRDF), coordination number (CN), angular distribution functions (ADF), and diffusion coefficient (DC). The results show that with the addition of CaCl2, Ca2+ ion complexed with Cl− ion to form larger ionic clusters, which reduced the proportion of free Cl− ion and restricted the diffusion of Cl− ion.

Computational Study of the Physical Properties of a High Temperature Molten Salt Mixture of FLiNaK and CeF3

In this work, we study the diffusion characteristics and structure of the molten salt FLiNaK with dissolved CeF3 in the operating temperature range of the molten-salt reactor. The temperature dependence of the self-diffusion coefficients of the ions that make up the salt mixture is represented with good accuracy as a linear dependence, except for the case of self-diffusion of Ce ions. As a rule, Li and F ions are more mobile than Na and K ions and significantly more so than slow Ce ions. The coordination numbers and their increase upon dissolution of CeF3 in FLiNaK were determined based on the calculation of partial radial distribution functions. The detailed structure of the melt is studied based on the construction of Voronoi polyhedra. The obtained topological characteristics indicate a predominantly tetrahedral type of distribution of Ce ions over the bulk of the system. Rotational symmetry of the 5th order prevails in the structure of the Li and F subsystems, and symmetries of the 3rd and 4th orders prevail in the Na and K subsystems, respectively. The simulation results can be used to search for actinide, which can be replaced by cerium in real experiments.

The short-range order in liquid water and amorphous ice

The short-range order in water and ice was determined from experimentally measured partial radial distribution functions by applying the Quasi Crystalline Model (QCM). Partial radial distribution functions were analyzed for water at several pressures and temperatures, crystalline ice, and for the three known phases of amorphous ice: Low-Density Amorphous (LDA), High-Density Amorphous (HDA), and Very-High-Density Amorphous (VHDA). It was found that at low temperatures and pressures, the short-range order of water is similar to that of the hexagonal ice (Ih) structure. At higher pressures and low temperatures, the short-range order of water becomes similar to that of tetragonal ice III structures with a c/a ratio of 0.8. At higher temperatures of 573 K, the short-range order obtained was similar to that of rhombohedral ice II (α = 113°). As for the amorphous ices, we conclude from the QCM analysis that these three forms are structurally distinct with short-range orders corresponding to ice Ih, ice III, and ice II for LDA, HDA, and VHDA ices, respectively.

Prediction on local structure and properties of LiCl-KCl-AlCl3 ternary molten salt with deep learning potential

LiCl-KCl-AlCl3 molten salt is the main electrolyte for Al-Li alloys electrolysis. It’s beneficial for the electrolyte optimization to have a deeply understand to the local structure and properties of LiCl-KCl-AlCl3 molten salt. Deep potential molecular dynamics simulations were applied in this study, which can balance efficiency and accuracy of the calculations. A deep potential model for LiCl-KCl-AlCl3 molten salt was trained to predict the local structure and properties of LiCl-KCl-AlCl3 molten salt. The structure and properties with temperature were analyzed. The structure information includes the partial radial distribution functions and coordination number distribution; the properties consist of density, self-diffusion coefficient, viscosity, ionic conductivity, thermal expansion coefficient and heat capacity. The structure analysis shows that due to the strong and stable covalent bond between Al-Cl ion pairs, the increase of temperature has no obvious effect on the coordination structure of Al3+ and Cl–. For K-Cl and Li-Cl ion pairs, as the temperature increases, the connection between the anion and cation clusters weakens, and the overall structure of the molten salt tends to be loose, so the density and shear viscosity of the LiCl-KCl-AlCl3 molten salt decrease with the increase of temperature, the self-diffusion coefficient and ionic conductivity increase with increasing temperature, and the thermal expansion coefficient increases with increasing temperature. The variation of the self-diffusion coefficient, shear viscosity and ionic conductivity with temperature follows the Arrhenius rule. Moreover, this work provides an effective and accurate way to explore other molten salts.