A team of engineers, physicists, and data scientists from Princeton University and the Princeton Plasma Physics Laboratory (PPPL) have used artificial intelligence (AI) to predict—and then avoid—the formation of a specific type of plasma instability in magnetic confinement fusion tokamaks. The researchers built and trained a model using past experimental data from operations at the DIII-D National Fusion Facility in San Diego, Calif., before proving through real-time experiments that their model could forecast so-called tearing mode instabilities up to 300 milliseconds in advance—enough time for an AI controller to adjust operating parameters and avoid a tear in the plasma that could potentially end the fusion reaction.

Love

The thriving gray wolf population in the Chernobyl exclusion zone (CEZ) has been the subject of recent media interest. While some sensationalist reports have referred to “mutant wolves” with “superpowers,” other news outlets have offered more sober discussions of the science behind the story.

Cara N. Love, a biologist and postdoctoral fellow in the Department of Ecology and Evolutionary Biology at Princeton University, has been following the wolf population. Her research in the Chernobyl exclusion zone (CEZ) in Ukraine and Polesie State Radioecological Reserve in Belarus is helping biologists understand how nature adapts to chronic radiation exposure.

America’s electric utility workers and nuclear engineers are ready to work together to help rapidly decarbonize and electrify the economy. We welcome provisions in the bipartisan infrastructure bill that aim to prevent premature closures of our nuclear power plants. Through measures such as production tax credits, President Biden can safeguard America’s largest carbon-free energy source by recognizing the clean-air contributions of nuclear energy.