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 ...

Efficient processing of nuclear cross-sections data is critical for advanced reactor physics and safety assessments. Existing workflows of using nuclear data in Hierarchical Data Format, version 5 ...

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 ...

A new machine learning approach models adjusting power output of the Holos-Quad microreactor design by HolosGen LLC. The multi-agent reinforcement learning approach trains more efficiently than ...

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 ...

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 ...

The IAEA hosts a webinar focused on the strategic integration of Artificial Intelligence (AI) in Waste Management and Nuclear Decommissioning. This session highlights how AI technologies such as ...

This study introduces a methodology for applying artificial intelligence techniques to build an internal dosimetry prediction toolkit for nuclear medical pediatric applications. Based on distinct ...