Machine-learning-driven simulations on microstructure, thermodynamic properties, and transport properties of LiCl-KCl-LiF molten salt

The thermodynamic and transport properties of high-temperature chloride molten salt systems are of great significance for spent fuel reprocessing in the field of nuclear energy engineering. Here, by using machine learning based deep potential (DP) method, we train a high-precision force field model...

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Bibliographic Details

Published in:	Artificial Intelligence Chemistry
Main Authors:	Si-Min Qi, Tao Bo, Lei Zhang, Zhi-Fang Chai, Wei-Qun Shi
Format:	Article
Language:	English
Published:	Elsevier 2024-06-01
Subjects:	LiCl-KCl Molten salt Machine learning Deep potential Transport properties Molecular dynamics
Online Access:	http://www.sciencedirect.com/science/article/pii/S2949747723000271