A machine learning-powered simulation is giving researchers a new window into the processes that create some of the universe’s heaviest elements.

Senescence is a protective cellular response aimed at limiting the proliferation of old, cancerous or damaged cells. In response to various stressors, senescent cells enter stable cell cycle arrest, ...

Machine learning models energy release during heavy-element formation, enabling faster simulations of neutron star mergers ...

Using a novel simulation model based on machine learning, an international research team at GSI/FAIR has succeeded in gaining a deeper understanding of element formation in stellar events such as ...

Please see the full solicitation for complete information about the funding opportunity. Below is a summary assembled by the Research & Innovation Office (RIO). The DOE SC program in Nuclear Physics ...

Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development ...