AI Enhances Thorium Nuclear Reactor Models

Researchers in China have developed an artificial intelligence framework to improve nuclear reactor modeling. Scientists from Henan Normal University and the China Institute of Atomic Energy led the project ^[1]. They applied a Bayesian neural network to predict yields from thorium-232 fission ^[1]. This approach addresses long-standing gaps in global nuclear databases ^[1]. The new model helps engineers understand how thorium behaves during energy production ^[1]. Thorium-based molten salt reactors are considered a key part of future green energy systems ^[1]. These reactors offer potential safety and efficiency gains over traditional uranium-fueled plants ^[1]. By using AI, the team achieved more accurate performance metrics for next-gen designs ^[1]. This breakthrough could accelerate the deployment of advanced nuclear technologies ^[1]. Accurate modeling is vital for managing radioactive waste and ensuring reactor stability ^[1].