Theoretical prediction on the local structure and transport properties of molten alkali chlorides by deep potentials

doi:10.1016/j.jmst.2020.09.040

Abstract

Abstract:

In this work, the local structure and transport properties of three typical alkali chlorides (LiCl, NaCl, and KCl) were investigated by our newly trained deep potentials (DPs). We extracted datasets from ab initio molecular dynamics (AIMD) calculations and used these to train and validate the DPs. Large-scale and long-time molecular dynamics simulations were performed over a wider range of temperatures than AIMD to confirm the reliability and generality of the DPs. We demonstrated that the generated DPs can serve as a powerful tool for simulating alkali chlorides; the DPs also provide results with accuracy that is comparable to that of AIMD and efficiency that is similar to that of empirical potentials. The partial radial distribution functions and angle distribution functions predicted using the DPs are in close agreement with those derived from AIMD. The estimated densities, self-diffusion coefficients, shear viscosities, and electrical conductivities also matched well with the AIMD and experimental data. This work provides confidence that DPs can be used to explore other systems, including mixtures of chlorides or entirely different salts.

Key words: Deep potentials, Molecular dynamics simulations, Alkali chlorides, Local structure, Transport properties

Wenshuo Liang, Guimin Lu, Jianguo Yu. Theoretical prediction on the local structure and transport properties of molten alkali chlorides by deep potentials[J]. J. Mater. Sci. Technol., 2021, 75: 78-85.

Figures/Tables 6

Fig. 1. Comparison of energies and forces predicted using DPs with DFT for LiCl (a)-(b), NaCl (c)-(d), and KCl (e)-(f) at multiple temperatures.

Fig. 2. Comparison of RDFs (a)-(c) and ADFs (d)-(f) predicted using DPMD and AIMD at 1200 K. DPMD simulations with 1024 atoms (dots), DPMD simulations with 512 atoms (dashes), and AIMD simulations with 108 atoms (solid lines).

Fig. 3. Densities of molten LiCl (a), NaCl (b), and KCl (c) calculated via DPMD simulations within the NPT ensemble as a function of temperature. Experimental and AIMD data are from Wang et al. [20] and Bengtson et al. [28], respectively.

Fig. 4. Self-diffusion coefficients of molten LiCl (a), NaCl (b), and KCl (c) derived from DPMD simulations within the NVT ensemble at various temperatures. Experimental data are from Janz et al. [36]. AIMD data are from Bengtson et al. [28].

Fig. 5. Shear viscosities of molten LiCl (a), NaCl (b), and KCl (c) derived from DPMD simulations within the NVT ensemble at various temperatures. MD data are from Galamba et al. and Wang et al. [20,31]. Experimental data are from Janz et al. [36,39].

Fig. 6. Electrical conductivities of molten LiCl (a), NaCl (b), and KCl (c) derived from DPMD simulations within the NVT ensemble at various temperatures. Experimental data are from Janz et al. [36,39]. MD data are from Wang et al. [20].

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