Calculation of liquidus curve in phase diagram LiCl-KCl by molecular dynamics simulation

Kobelev, M. A.; Tatarinov, A. S.; Zakiryanov, Dmitry; Tkachev, N. K.

doi:10.1080/01411594.2020.1758318

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…Solid–liquid equilibrium calculations in systems with two or more components have largely focused on computing the solubilities of higher-melting components in a solvent − rather than computing liquidus/solidus curves in mixtures where the pure components have similar melting temperatures. − Both the direct coexistence and thermodynamic free-energy-based methods are more challenging for multicomponent systems. For direct coexistence, multicomponent systems appear to exacerbate the problems presented by system size effects and slow equilibration.…”

Section: Introductionmentioning

confidence: 99%

Computing the Liquidus of Binary Monatomic Salt Mixtures with Direct Simulation and Alchemical Free Energy Methods

DeFever

Maginn

2021

J. Phys. Chem. A

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We describe and validate a free-energy-based method for computing the liquidus for binary solid–liquid phase diagrams in molecular simulations of monatomic salts. The method is demonstrated by calculating the liquidus for LiCl–KCl and MgCl2–KCl salt mixtures with the polarizable ion model (PIM). The free-energy-based method is cross-validated with direct coexistence simulations. Both techniques show excellent agreement with one another. Though the predictions of the PIM disagree with experiments, we use our free-energy-based approach to decouple the contributions of liquid mixture nonidealities and pure component solid–liquid equilibrium to the phase diagram. In both mixtures, the PIM accurately reproduces the liquid phase nonidealities but fails to predict the liquidus because it does not accurately predict the pure component melting temperature of LiCl or MgCl2.

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Section: Introductionmentioning

confidence: 99%

Computing the Liquidus of Binary Monatomic Salt Mixtures with Direct Simulation and Alchemical Free Energy Methods

DeFever

Maginn

2021

J. Phys. Chem. A

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“…In contrast, classical force fields can exhibit large errors between the experimental and the calculated values. For instance, the calculated liquidus for LiCl–KCl by Kobelev et al using CMD simulations was observed to exhibit a maximum deviation of approximately 130 K, almost twice that shown in Figure . Similarly, even though the CMD force fields used by DeFever et al explicitly include atomic polarizability, the calculated liquidus was observed to have a maximum deviation of ∼160 K from experimental values.…”

Section: Resultsmentioning

confidence: 86%

“…The curved lines represent the solid–liquid equilibrium state, namely, the liquidus temperature. This has also been termed as the “ liquidus ” in previous studies, and it refers to the range of temperatures and compositions where the system can coexist as both a liquid and a solid. − In other words, it illustrates the conditions under which the first solid crystals begin to form during the cooling of a molten mixture and vice versa. For LiCl–KCl, the liquidus on the left represents the case in which solid KCl is in contact with a liquid mixture at a certain LiCl–KCl composition.…”

Section: Methodsmentioning

confidence: 99%

Development of a Neural Network Potential for Modeling Molten LiCl/KCl Salts: Bridging Efficiency and Accuracy

Bin Faheem,

Lee

2024

J. Phys. Chem. C

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Optimizing molten salts for molten salt reactors and concentrated solar power can be challenging due to limited experimental data. To tackle this, we utilize neural network potentials (NNPs) for the atomistic modeling of molten salts and use the widely popular LiCl/KCl salts as prototype systems. Based on the results reported herein, the NNP exhibits remarkable accuracy and is similar to density functional theory calculations. The reliability of the NNP was due to a rigorous approach to acquiring training data, which covered atomic configurations at different temperatures and pressures for pure LiCl, pure KCl, and LiCl−KCl (58.8% mol LiCl) systems. It was observed that the NNP reasonably reproduced experimental physical properties of molten LiCl/KCl salts across various compositions and temperatures and microstructures that are similar to highly accurate first-principles molecular dynamics. Furthermore, the NNP was employed to calculate diffusion coefficients of molten LiCl−KCl salts, for which no current experimental data are available. From this, we verify the NNP by reporting the well-known Chemla effect in molten LiCl−KCl systems. We further employ the use of the NNP to predict the phase diagram of the LiCl−KCl system by using solid−liquid coexistence simulations. The robustness and versatility of the NNP reported in this study demonstrate the promising potential of the developed NNP in overcoming the longstanding trade-offs between computational efficiency and accuracy in the MD simulations of molten salts.

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“…(3) The liquidus temperature of the electrolyte can be decreased by increasing the amount of KCl, based on LiCl-KCl binary phase diagram. 34 Accordingly, at 670 °C, the pure LiCl, and melts containing 10 and 30 wt% KCl experience a superheat value of around 60, 82, and 156 °C, respectively, causing lower values of viscosity in the presence of greater amount of KCl. Therefore, the introduced KCl can promote the physicochemical properties of the LiCl electrolyte, consequently accelerating the reduction kinetics.…”

Section: Influence Of the Electrolyte Composition On The Reduction Of...mentioning

confidence: 99%

Steam-assisted electro-reduction of NiO: a sustainable alternative to conventional hydrogen reduction

Xie,

Kamali

2024

Green Chem.

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Calculation of liquidus curve in phase diagram LiCl-KCl by molecular dynamics simulation

Cited by 7 publications

References 12 publications

Computing the Liquidus of Binary Monatomic Salt Mixtures with Direct Simulation and Alchemical Free Energy Methods

Computing the Liquidus of Binary Monatomic Salt Mixtures with Direct Simulation and Alchemical Free Energy Methods

Development of a Neural Network Potential for Modeling Molten LiCl/KCl Salts: Bridging Efficiency and Accuracy

Steam-assisted electro-reduction of NiO: a sustainable alternative to conventional hydrogen reduction

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