
Structure and dynamics of molten calcium chloride: ab initio simulations
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Li Y, Xu X, Wang X, Li P et al., Survey and evaluation of equations for thermophysical properties of binary/ternary eutectic salts from NaCl, KCl, MgCl2, CaCl2, ZnCl2 for heat transfer and thermal storage fluids in CSP, Solar Energy, 152 (2017) 57–79. https://doi.org/10.1016/j.solener.2017.03.019
Tian H, Wang W, Ding J, Wei X, Thermal performance and economic evaluation of NaCl–CaCl2 eutectic salt for high-temperature thermal energy storage, Energy, 227 (2021) 120412. https://doi.org/10.1016/j.energy.2021.120412
Du L, Ding J, Tian H, Wang W, et al., Thermal properties and thermal stability of the ternary eutectic salt NaCl-CaCl2-MgCl2 used in high-temperature thermal energy storage process, Applied Energy, 204 (2017) 1225–1230. https://doi.org/10.1016/j.apenergy.2017.03.096
Jacob R, Sergeev D, Yazhenskikh E, Müller M, Evaluation of the calcium chloride-calcium fluoride system for high temperature thermal energy storage, Journal of Energy Storage, 72 (2023) 108521. https://doi.org/10.1016/j.est.2023.108521
Jones RO, Density functional theory: Its origins, rise to prominence, and future, Reviews of Modern Physics, 87 (2015) 897–923. https://doi.org/10.1103/revmodphys.87.897
Geerlings P, De Proft F, Langenaeker W, Conceptual Density Functional Theory, Chemical Reviews, 103 (2003) 1793–1874. https://doi.org/10.1021/cr990029p
Deringer VL, Caro MA, Csányi G, Machine Learning Interatomic Potentials as emerging Tools for Materials Science, Advanced Materials, 31 (2019) 1902765. https://doi.org/10.1002/adma.201902765
Behler J, Perspective: Machine learning potentials for atomistic simulations, The Journal of Chemical Physics, 145 (2016) 170901. https://doi.org/10.1063/1.4966192
Xie Y, Bu M, Zhang Y, Lu G, Effect of composition and temperature on microstructure and thermophysical properties of LiCl-CaCl2 molten salt based on machine learning potentials, Journal of Molecular Liquids, 383 (2023) 122112. https://doi.org/10.1016/j.molliq.2023.122112
Rong Z, Pan G, Lu J, Liu S, et al., Ab-initio molecular dynamics study on thermal property of NaCl–CaCl2 molten salt for high-temperature heat transfer and storage, Renewable Energy, 163 (2020) 579–588. https://doi.org/10.1016/j.renene.2020.08.152
Gegentana N, Cui L, Zhou L, Du X, Deep Potential Molecular Dynamics Systematic Study of Microstructure and Thermophysical Properties of NaCl-CaCl2 Molten Salt System across Phase Transition Temperature, Journal of Thermal Science, 33 (2024) 2245–2258. https://doi.org/10.1007/s11630-024-2054-5
Gegentana N, Cui L, Zhou L, Du X, A deep potential molecular dynamics study on the ionic structure and transport properties of NaCl-CaCl2 molten salt, Ionics, 30 (2023) 285–295. https://doi.org/10.1007/s11581-023-05265-8
Bu M, Liang W, Lu G, Yu J, Local structure elucidation and properties prediction on KCl–CaCl2 molten salt: A deep potential molecular dynamics study, Solar Energy Materials and Solar Cells 232 (2021) 111346. https://doi.org/10.1016/j.solmat.2021.111346
Xie Y, Bu M, Lu G, Local structure and thermophysical property prediction for CaCl2-KCl molten salt with machine learning potentials, Materials Today Communications, 41 (2024) 110243. https://doi.org/10.1016/j.mtcomm.2024.110243
Luo X, Ling C, Xu T, Liu W et al., Thermophysical property and micro-structure of the molten NaCl-KCl-CaCl2 salt at high temperature by FPMD simulation, Solar Energy Materials and Solar Cells, 288 (2025) 113630. https://doi.org/10.1016/j.solmat.2025.113630
Xie Y, Bu M, Lu G, Insights into CaCl2-NaCl-KCl molten salt: A machine learning approach to unraveling structure and properties, Journal of Energy Storage, 102 (2024) 114156. https://doi.org/10.1016/j.est.2024.114156
Bu M, Liang W, Lu G, Yu J, Static and dynamic ionic structure of molten CaCl2 via first-principles molecular dynamics simulations, Ionics, 27 (2020) 771–779. https://doi.org/10.1007/s11581-020-03852-7
Perdew JP, Burke K, Ernzerhof M, Generalized gradient approximation made simple, Physical Review Letters, 77 (1996) 3865–3868. https://doi.org/10.1103/physrevlett.77.3865
Umesaki N, Structural characterization of molten calcium chloride by molecular dynamics simulation, AIP Conference Proceedings, 256 (1992) 561–562. https://doi.org/10.1063/1.42392
Biggin S, Enderby JE, The structure of molten calcium chloride, Journal of Physics C Solid State Physics, 14 (1981) 3577–3583. https://doi.org/10.1088/0022-3719/14/25/006
Grimme S, Antony J, Ehrlich S, Krieg H, A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu, The Journal of Chemical Physics, 132 (2010) 154104. https://doi.org/10.1063/1.3382344
Grimme S, Hansen A, Brandenburg JG, Bannwarth C, Dispersion-Corrected Mean-Field electronic structure Methods, Chemical Reviews, 116 (2016) 5105–5154. https://doi.org/10.1021/acs.chemrev.5b00533
Goerigk L, A comprehensive overview of the DFT-D3 London-Dispersion correction, in: Elsevier eBooks, 2017: pp. 195–219. https://doi.org/10.1016/b978-0-12-809835-6.00007-4
Kühne TD, Iannuzzi M, Del Ben M, Rybkin VV et al., CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations, The Journal of Chemical Physics, 152 (2020) 194103. https://doi.org/10.1063/5.0007045
VandeVondele J, Hutter J, Gaussian basis sets for accurate calculations on molecular systems in gas and condensed phases, The Journal of Chemical Physics, 127 (2007) 114105. https://doi.org/10.1063/1.2770708
Goedecker S, Teter M, Hutter J, Separable dual-space Gaussian pseudopotentials, Physical Review. B, Condensed Matter, 54 (1996) 1703–1710. https://doi.org/10.1103/physrevb.54.1703
Koput J, Ab Initio Prediction of the Potential Energy Surface and Vibration-Rotation Energy Levels of CaCl2, Journal of Physical Chemistry A, 112 (2008) 2743–2746. https://doi.org/10.1021/jp711785p
Janz GJ, Thermodynamic and transport properties for molten salts: correlation equations for critically evaluated density, surface tension, electrical conductance, and viscosity data, Journal of Physical and Chemical Reference Data, 17 (1988) 309.
Porter T, Vaka MM, Steenblik P, Della Corte D, Computational methods to simulate molten salt thermophysical properties, Communications Chemistry, 5 (2022) 69. https://doi.org/10.1038/s42004-022-00684-6
Zakiryanov D, The refined determination of the ion pair lifetimes in ionic liquids, Computational and Theoretical Chemistry, 1210 (2022) 113646. https://doi.org/10.1016/j.comptc.2022.113646
Thomas M, Brehm M, Fligg R, Vöhringer P, et al., Computing vibrational spectra from ab initio molecular dynamics, Physical Chemistry Chemical Physics, 15 (2013) 6608. https://doi.org/10.1039/c3cp44302g
Brehm M, Kirchner B, TRAVIS - a free analyzer and visualizer for Monte Carlo and molecular dynamics trajectories, Journal of Chemical Information and Modeling, 51 (2011) 2007–2023. https://doi.org/10.1021/ci200217w
Yu M, Trinkle DR, Accurate and efficient algorithm for Bader charge integration, The Journal of Chemical Physics, 134 (2011) 064111. https://doi.org/10.1063/1.3553716
Bockris JO, Richards SR, Nanis L, Self-Diffusion and structure in molten group II chlorides, The Journal of Physical Chemistry, 69 (1965) 1627–1637. https://doi.org/10.1021/j100889a031
Ichikawa K, Shimoji M, Niwa K, Impurity diffusion of calcium ions in alkali chloride + calcium chloride mixed melts and Self‐Diffusion of calcium ions in molten calcium chloride, Berichte Der Bunsengesellschaft Für Physikalische Chemie, 69 (1965) 248–255. https://doi.org/10.1002/bbpc.19650690313
DOI: https://doi.org/10.15826/elmattech.2025.4.052
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