Work led by Postdoc Chen Shen and Siamak Attarian, together with Profs. Dane Morgan and Izabela Szlufarska, has resulted in the development of a machine learning–based tool called SuperSalt. This powerful framework enables accurate simulation and prediction of the properties of molten salt systems. By providing reliable insights into structure–property relationships, SuperSalt will help researchers design and tailor molten salts for emerging energy storage applications and the harsh operating conditions of next-generation nuclear reactors.
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