Abstract: We demonstrate that the melting points and other thermodynamic quantities of the alkali metals can be calculated based on static crystalline properties. To do this we derive analytic interatomic potentials for the alkali metals fitted precisely to cohesive and vacancy energies, elastic moduli, the lattice parameter, and crystal stability. These potentials are then used to calculate melting points by simulating the equilibration of solid and liquid samples in thermal contact at ambient pressure. With the exception of lithium, remarkably good agreement is found with experimental values. The instability of the bcc structure in Li and Na at low temperatures is also reproduced and, unusually, is not due to a soft T1N phonon mode. No forces or finite-temperature properties are included in the fit, so this demonstrates a surprisingly high level of intrinsic transferability in the simple potentials. Currently, there are few potentials available for the alkali metals, so in addition to demonstrating trends in behavior, we expect that the potentials will be of broad general use.

Abstract: The solid-liquid interface (SLI) free energy was determined from molecular dynamics (MD) simulation for several body centered cubic (bcc) metals and B2 metallic compounds (space group: Pm-3m; prototype: CsCl). In order to include a bcc metal with a low melting temperature in our study, a semi-empirical potential was developed for Na. Two additional synthetic "Na" potentials were also developed to explore the effect of liquid structure and latent heat on the SLI free energy. The obtained MD data were compared with the empirical Turnbull, Laird, and Ewing relations. All three relations are found to predict the general trend observed in the MD data for bcc metals obtained within the present study. However, only the Laird and Ewing relations are able to predict the trend obtained within the sequence of "Na" potentials. The Laird relation provides the best prediction for our MD data and other MD data for bcc metals taken from the literature. Overall, the Laird relation also agrees well with our B2 data but requires a proportionality constant that is substantially different from the bcc case. It also fails to explain a considerable difference between the SLI free energies of some B2 phases which have nearly the same melting temperature. In contrast, this difference is satisfactorily described by the Ewing relation. Moreover, the Ewing relation obtained from the bcc dataset also provides a reasonable description of the B2 data.

Abstract: The Morse parameters were calculated using experimental values for the energy of vaporization, the lattice constant, and the compressibility. The equation of state and the elastic constants which were computed using the Morse parameters, agreed with experiment for both face-centered and body-centered cubic metals. All stability conditions were also satisfied for both the face-centered and the body-centered metals. This shows that the Morse function can be applied validly to problems involving any type of deformation of the cubic metals.

Abstract: Ionic compounds exhibit a variety of crystal structures that can critically affect their applications. Traditionally, relative sizes of cations and anions have been used to explain coordination of ions within the crystals. Such approaches assume atoms to be hard spheres and they cannot explain the observed structures of some crystals. Here we develop an atomistic method and use it to explore the structure-determining factors beyond the limitations of the hard sphere approach. Our approach is based upon a calibrated interatomic potential database that uses independent intrinsic bond lengths to measure atomic sizes. By carrying out extensive atomistic simulations, striking relationships among intrinsic bond lengths are discovered to determine the B1 (NaCl), B2 (CsCl), and B3 (zinc-blende) structure of binary ionic compounds.

Abstract: In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)_1-x(MgCl₂)_x molten salt and we showed that it is possible to fit a robust potential for this pseudo-binary system by only including data from x={0, 1/3, 2/3, 1}. We also assessed the performance of several DFT methods including PBE-D3, PBE-D4, R2SCAN-D4, and R2SCANrVV10 on unary NaCl and MgCl₂ salts. Our results show that the R2SCAN-D4 method calculates the thermophysical properties of NaCl and MgCl₂ with an overall modestly better accuracy compared to the other three methods.

Abstract: In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)_1-x(MgCl₂)_x molten salt and we showed that it is possible to fit a robust potential for this pseudo-binary system by only including data from x={0, 1/3, 2/3, 1}. We also assessed the performance of several DFT methods including PBE-D3, PBE-D4, R2SCAN-D4, and R2SCANrVV10 on unary NaCl and MgCl₂ salts. Our results show that the R2SCAN-D4 method calculates the thermophysical properties of NaCl and MgCl₂ with an overall modestly better accuracy compared to the other three methods.

Abstract: In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)_1-x(MgCl₂)_x molten salt and we showed that it is possible to fit a robust potential for this pseudo-binary system by only including data from x={0, 1/3, 2/3, 1}. We also assessed the performance of several DFT methods including PBE-D3, PBE-D4, R2SCAN-D4, and R2SCANrVV10 on unary NaCl and MgCl₂ salts. Our results show that the R2SCAN-D4 method calculates the thermophysical properties of NaCl and MgCl₂ with an overall modestly better accuracy compared to the other three methods.

Abstract: In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)_1-x(MgCl₂)_x molten salt and we showed that it is possible to fit a robust potential for this pseudo-binary system by only including data from x={0, 1/3, 2/3, 1}. We also assessed the performance of several DFT methods including PBE-D3, PBE-D4, R2SCAN-D4, and R2SCANrVV10 on unary NaCl and MgCl₂ salts. Our results show that the R2SCAN-D4 method calculates the thermophysical properties of NaCl and MgCl₂ with an overall modestly better accuracy compared to the other three methods.

Abstract: In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)_1-x(MgCl₂)_x molten salt and we showed that it is possible to fit a robust potential for this pseudo-binary system by only including data from x={0, 1/3, 2/3, 1}. We also assessed the performance of several DFT methods including PBE-D3, PBE-D4, R2SCAN-D4, and R2SCANrVV10 on unary NaCl and MgCl₂ salts. Our results show that the R2SCAN-D4 method calculates the thermophysical properties of NaCl and MgCl₂ with an overall modestly better accuracy compared to the other three methods.

Abstract: In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)_1-x(MgCl₂)_x molten salt and we showed that it is possible to fit a robust potential for this pseudo-binary system by only including data from x={0, 1/3, 2/3, 1}. We also assessed the performance of several DFT methods including PBE-D3, PBE-D4, R2SCAN-D4, and R2SCANrVV10 on unary NaCl and MgCl₂ salts. Our results show that the R2SCAN-D4 method calculates the thermophysical properties of NaCl and MgCl₂ with an overall modestly better accuracy compared to the other three methods.

Abstract: In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)_1-x(MgCl₂)_x molten salt and we showed that it is possible to fit a robust potential for this pseudo-binary system by only including data from x={0, 1/3, 2/3, 1}. We also assessed the performance of several DFT methods including PBE-D3, PBE-D4, R2SCAN-D4, and R2SCANrVV10 on unary NaCl and MgCl₂ salts. Our results show that the R2SCAN-D4 method calculates the thermophysical properties of NaCl and MgCl₂ with an overall modestly better accuracy compared to the other three methods.

Abstract: In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)_1-x(MgCl₂)_x molten salt and we showed that it is possible to fit a robust potential for this pseudo-binary system by only including data from x={0, 1/3, 2/3, 1}. We also assessed the performance of several DFT methods including PBE-D3, PBE-D4, R2SCAN-D4, and R2SCANrVV10 on unary NaCl and MgCl₂ salts. Our results show that the R2SCAN-D4 method calculates the thermophysical properties of NaCl and MgCl₂ with an overall modestly better accuracy compared to the other three methods.

Abstract: Achieving atomic-level understanding of crystallization of molten salts is of importance to a wide range of technological applications. Recent work [Fan et al., Proc. Natl. Acad. Sci. USA 122, e2425702122 (2025)] revealed that crystal nucleation in molten LiF salt is a multistage process according to the molecular-dynamics (MD) simulations based on an atomic cluster expansion (ACE) machine-learning interatomic potential (MLIP). In order to understand the influence of increasing cation size on nucleation pathways and nucleation rates of molten fluoride salts, here we develop two new ACE MLIPs for NaF and KF. The two ACE MLIPs feature DFT-SCAN-level accuracy for liquid and multiple solid polymorphs over a wide temperature (0–2000 K) and pressure (0-100 GPa) range, and also reproduce well a number of experimental data for solid and liquid equilibrium properties. The efficiency of the two ACE MLIPs enable million-atom-scale or microsecond-scale MD simulations. The two general-purpose ACE MLIPs are expected to be useful for atomistic simulations for different purposes, in addition to studying crystallization of molten NaF and KF salts.

Abstract: The solid-liquid interface (SLI) free energy was determined from molecular dynamics (MD) simulation for several body centered cubic (bcc) metals and B2 metallic compounds (space group: Pm-3m; prototype: CsCl). In order to include a bcc metal with a low melting temperature in our study, a semi-empirical potential was developed for Na. Two additional synthetic "Na" potentials were also developed to explore the effect of liquid structure and latent heat on the SLI free energy. The obtained MD data were compared with the empirical Turnbull, Laird, and Ewing relations. All three relations are found to predict the general trend observed in the MD data for bcc metals obtained within the present study. However, only the Laird and Ewing relations are able to predict the trend obtained within the sequence of "Na" potentials. The Laird relation provides the best prediction for our MD data and other MD data for bcc metals taken from the literature. Overall, the Laird relation also agrees well with our B2 data but requires a proportionality constant that is substantially different from the bcc case. It also fails to explain a considerable difference between the SLI free energies of some B2 phases which have nearly the same melting temperature. In contrast, this difference is satisfactorily described by the Ewing relation. Moreover, the Ewing relation obtained from the bcc dataset also provides a reasonable description of the B2 data.

Abstract: The solid-liquid interface (SLI) free energy was determined from molecular dynamics (MD) simulation for several body centered cubic (bcc) metals and B2 metallic compounds (space group: Pm-3m; prototype: CsCl). In order to include a bcc metal with a low melting temperature in our study, a semi-empirical potential was developed for Na. Two additional synthetic "Na" potentials were also developed to explore the effect of liquid structure and latent heat on the SLI free energy. The obtained MD data were compared with the empirical Turnbull, Laird, and Ewing relations. All three relations are found to predict the general trend observed in the MD data for bcc metals obtained within the present study. However, only the Laird and Ewing relations are able to predict the trend obtained within the sequence of "Na" potentials. The Laird relation provides the best prediction for our MD data and other MD data for bcc metals taken from the literature. Overall, the Laird relation also agrees well with our B2 data but requires a proportionality constant that is substantially different from the bcc case. It also fails to explain a considerable difference between the SLI free energies of some B2 phases which have nearly the same melting temperature. In contrast, this difference is satisfactorily described by the Ewing relation. Moreover, the Ewing relation obtained from the bcc dataset also provides a reasonable description of the B2 data.