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

DeFever, Ryan S.; Maginn, Edward J.

doi:10.1021/acs.jpca.1c06107

Cited by 5 publications

(14 citation statements)

References 81 publications

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“…Combined with the work here, comprehensive phase diagrams of RDX and HMX could then be generated for these molecular models. Moreover, while this work focused on single‐component phase coexistence, it is possible to determine multi‐component phase coexistence behavior, such as the RDX‐HMX liquidus, using alchemical transformation techniques [57].…”

Section: Discussionmentioning

confidence: 99%

Predicting Melt Curves of Energetic Materials Using Molecular Models

Tow

Larentzos

Sellers

et al. 2022

Propellants Explo Pyrotec

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In this work, the solid–liquid coexistence curves of classical fully flexible atomistic models of α‐RDX and β‐HMX were calculated using thermodynamically rigorous methodologies that identify where the free energy difference between the phases is zero. The free energy difference between each phase at a given state point was computed using the pseudosupercritical path (PSCP) method, and Gibbs–Helmholtz integration was used to evaluate the solid–liquid free energy difference as a function of temperature. This procedure was repeated for several pressures to determine points along the coexistence curve, which were then fit to the Simon–Glatzel functional form. While effective, this method is computationally expensive. An alternative approach is to compute the melting point at a single pressure via the PSCP method, and then use the Gibbs–Duhem integration technique to trace out the coexistence curve in a more computationally economical manner. Both approaches were used to determine the coexistence curve of α‐RDX. The Gibbs–Duhem integration method was shown to generate a melt curve that is in good agreement with the PSCP‐derived melt curve, while only costing ∼10 % of the computational resources used for the PSCP method. For α‐RDX, the predicted melting temperature increases significantly more for a given increase in pressure when compared to available experimental data.

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Section: Discussionmentioning

confidence: 99%

Predicting Melt Curves of Energetic Materials Using Molecular Models

Tow

Larentzos

Sellers

et al. 2022

Propellants Explo Pyrotec

View full text Add to dashboard Cite

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“…In order to construct the phase diagram using DPMD simulations, we employ the use of the direct coexistence method. 81 In the case of the binary LiCl−KCl mixture, the experimental phase diagram is illustrated in Figure S1a. As seen in Figure S1a, the area below the horizontal line at the bottom represents the region where the molten salt is present in the solid state at all compositions.…”

Section: Solid−liquid Coexistence Calculationsmentioning

confidence: 99%

“…Such an approximation is valid, as the crystalline phases of LiCl and KCl are immiscible. 81 Hence, the liquid phase composition determines the equilibrium point on the liquidus line at any temperature. After the initial system is constructed, the liquid composition changes as the DPMD simulations proceed at the desired temperature.…”

Section: Solid−liquid Coexistence Calculationsmentioning

confidence: 99%

“…Similar results have also been reported in previous studies for the solid−liquid coexistence simulations of LiCl−KCl. 81 The remaining simulation protocols were the same as those described in Section 2.3.…”

Section: Solid−liquid Coexistence Calculationsmentioning

confidence: 99%

“…To calculate the points on the liquidus curve, we employ the direct coexistence approach. 81 The direct coexistence approach employs constructing MD simulation boxes consisting of a solid LiCl or KCl crystal in contact with a molten LiCl/KCl mixture (see Figure 9). The simulation protocols are described in Section 2.5.…”

Section: Temperature and Compositional Dependencementioning

confidence: 99%

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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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