LiF–NaF–ZrF4 multicomponent molten salts are promising candidate coolants for advanced
clean energy systems owing to their desirable thermophysical and transport properties …

Machine learning interatomic potentials have emerged as a powerful tool for bypassing the
spatiotemporal limitations of ab initio simulations, but major challenges remain in their …

Advances in nuclear power reactors include the use of mixed oxide fuel, containing uranium
and plutonium oxides. The high-temperature behaviour and structure of PuO2–x above …

In vitro and in silico studies should supplement each other in order to obtain reliable and
comprehensive data on physicochemical properties of molten salts. To attain the aim, the …

The emergence of artificial intelligence has provided efficient methodologies to pursue
innovative findings in material science. Over the past two decades, machine‐learning …

In this work, we developed a compositionally transferable machine learning interatomic
potential using atomic cluster expansion potential and PBE-D3 method for (NaCl) 1-x (MgCl …

Molten salts are promising candidates in numerous clean energy applications, where
knowledge of thermophysical properties and vapor pressure across their operating …

During the operation of fast-spectrum liquid-fueled molten salt reactors (MSRs), the salt
composition of the fuel salt changes due to the generation of transmutation products (TPs) …

Workflows applications are becoming increasingly important to support scientific discovery.
That is leading to a proliferation of workflow management systems and, thus, to a …

Molten salts could play an important role in energy storage, in the form of liquid batteries,
and heat storage for solar and nuclear power. However, their widespread application is …