2021
DOI: 10.1016/j.jmst.2020.09.040
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Theoretical prediction on the local structure and transport properties of molten alkali chlorides by deep potentials

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Cited by 43 publications
(28 citation statements)
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“…Other DPs were developed to calculate transport properties of silicate in the mantle [144][145][146]. DPs were also employed in large-scale calculations of thermodynamic, transport, and structural properties in different molten salts [149][150][151][152][153][154][155][156][157].…”
Section: Multi-element Bulk Systemsmentioning
confidence: 99%
“…Other DPs were developed to calculate transport properties of silicate in the mantle [144][145][146]. DPs were also employed in large-scale calculations of thermodynamic, transport, and structural properties in different molten salts [149][150][151][152][153][154][155][156][157].…”
Section: Multi-element Bulk Systemsmentioning
confidence: 99%
“…Recently, a faster Drude-type model that includes some of the same ingredients as in these other more expensive models has also been successfully developed and applied to the case of MgCl 2 and its mixtures with KCl . A variety of articles based on machine-learning simulation schemes for molten salts have also recently appeared in the literature. Advances in computational models have come hand-in-hand with new experimental studies, ,,, ,− and in some cases, the combination of these challenges strongly entrenched assumptions, for example the octahedral coordination of U 3+ , the tetrahedrality in coordination for Mg 2+ , , and other properties that collectively have influenced the literature for 30 years or more. , The works cited thus far are meant to provide some context and are not exhaustive or cover many of the most studied salts and their mixtures of which the eutectics are of special relevance.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, the Behler–Parrinello NN (BP-NN) model uses hand-crafted local symmetry functions as descriptors, requiring human intervention. The recent studies using the ML force field (ML-FF) on molten salt systems showed that the predicted local structure, thermophysical properties, and transport properties of some alkaline agree well with the AIMD and experimental results, suggesting that these properties can be accurately predicted using the ML-FF-based MD simulations.…”
Section: Introductionmentioning
confidence: 63%