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Machine-Learned Interatomic Potentials for Predicting Physicochemical Properties of Molten Metal-Salt Systems for Calcium Electrolysis

M. Polovinkin, N. Rybin, D. Maksimov, F. Valiev, A. Khudorozhkova, M. Laptev, A. Rudenko, A. Shapeev

Abstract

The design of efficient electrolysis devices for pure metal production requires accurate data on the properties of the melts used in the process. This work focuses on two key systems for calcium production: the molten Ca-Cu alloy and the CaCl$_2$-KCl electrolyte. High-temperature experiments are often expensive and time-consuming; however, we demonstrate that molecular dynamics (MD) simulations driven by machine-learned Moment Tensor Potentials (MTPs), trained on highly accurate density functional theory data, offer an effective and accurate alternative. Our MTP-driven MD simulations accurately reproduce the structural, thermodynamic, and transport properties across a range of temperatures and compositions relevant to electrolysis systems. We report calculated densities, radial distribution functions, heat capacities, thermal conductivities, ionic conductivities (for the electrolyte), viscosities, and diffusion coefficients, with deviations from experimental data within 20%. The strong agreement between calculations and experiments validates the proposed approach, establishing a robust framework for the computational exploration and optimization of liquid systems in metallurgical applications.

Machine-Learned Interatomic Potentials for Predicting Physicochemical Properties of Molten Metal-Salt Systems for Calcium Electrolysis

Abstract

The design of efficient electrolysis devices for pure metal production requires accurate data on the properties of the melts used in the process. This work focuses on two key systems for calcium production: the molten Ca-Cu alloy and the CaCl-KCl electrolyte. High-temperature experiments are often expensive and time-consuming; however, we demonstrate that molecular dynamics (MD) simulations driven by machine-learned Moment Tensor Potentials (MTPs), trained on highly accurate density functional theory data, offer an effective and accurate alternative. Our MTP-driven MD simulations accurately reproduce the structural, thermodynamic, and transport properties across a range of temperatures and compositions relevant to electrolysis systems. We report calculated densities, radial distribution functions, heat capacities, thermal conductivities, ionic conductivities (for the electrolyte), viscosities, and diffusion coefficients, with deviations from experimental data within 20%. The strong agreement between calculations and experiments validates the proposed approach, establishing a robust framework for the computational exploration and optimization of liquid systems in metallurgical applications.

Paper Structure

This paper contains 11 sections, 11 equations, 15 figures, 1 table.

Table of Contents

  1. Introduction
  2. Methods
  3. MTP fitting
  4. Physicochemical properties calculation
  5. Experimental measurements
  6. Results and discussion
  7. Potential fitting
  8. Physicochemical properties of Ca-Cu liquid alloy
  9. Physicochemical properties of the CaCl$_2$-KCl molten salt
  10. Conclusion
  11. Data availability

Figures (15)

  • Figure 1: Composition dependence of Ca-Cu liquid alloy density at temperatures 900, 1000, 1200, and 1400 K. Experimental data for Ca-Cu liquid alloy are taken from calcium_Hiemstra1997CaCu_exp_Zaikovcopper_Assael2010.
  • Figure 2: RDFs for liquid alloys systems. (a) RDF in pure copper at temperature 1423 K. Experimental curve from CaRDF_Waseda1974. (b) RDF in pure calcium at temperature 1123 K. Experimental curve from waseda1980structure. (c-d) RDFs in Ca-Cu liquid alloy at molar fraction of calcium 0.5 and 0.8, temperature 1000 K.
  • Figure 3: Composition dependence of mass-specific heat capacity for Ca-Cu melt.
  • Figure 4: Composition dependence of viscosity at temperatures 1000, 1200, and 1400 K. Experimental data for Ca-Cu liquid alloy is taken from CaCu_exp_Zaikovcopper_Assael2010.
  • Figure 5: Diffusion coefficients of Ca-Cu liquid alloy at temperatures 900, 1000, 1200, and 1400 K. (a) Composition dependence of calcium diffusion coefficient. (b) Composition dependence of copper diffusion coefficient.
  • ...and 10 more figures