A multi-institutional team of researchers led by the University of Cincinnati's Yu Shi has developed a technique for modeling the thermodynamic properties of molten salts via deep learning artificial intelligence.
The researchers trained a neural network on data produced by quantum simulations, which they used to estimate the free energy of molten sodium chloride, Shi says. The research offers a reliable way of studying the conversion of dissolved gas to vapor in molten salts, helping to understand how impurities and solutes affect corrosion, he says.
Shi says the method also could help scientists analyze the emission of potentially toxic gas into the atmosphere, which will be useful for fourth-generation molten salt nuclear reactors.
From University of Cincinnati
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