The 2025 Kaul Foundation Prize for Excellence in Plasma Physics Research and Technology Development has been awarded to Seong-Moo Yang, SangKyeun Kim and Ricardo Shousha of the U.S. Department of Energy's Princeton Plasma Physics Laboratory (PPPL). The trio earned the prize for their work "optimizing 3D magnetic fields in tokamaks to control edge instabilities while minimizing disruptions and improving confinement." Such research is critical to developing fusion systems that can reliably generate energy for the power grid. As a part of the honor, each winner will receive $7,500.
"Seong-Moo Yang, SangKyeun Kim and Ricardo Shousha have made fundamental contributions to one of the most challenging problems in fusion energy, using artificial intelligence and traditional approaches," said Lab Director Steve Cowley. "Their work has advanced our understanding of how to operate them more reliably and efficiently, and it is already influencing experiments around the world. I am delighted to see their dedication and creativity recognized with this well-deserved honor."
Inside fusion vessels known as tokamaks, magnetic fields are used to confine plasma into the shape of a doughnut. Keeping the edge of a plasma stable remains a significant challenge for future fusion energy, as this boundary region can become unstable and damage the inside of the tokamak. Researchers are exploring several approaches to controlling a plasma's edge. All tokamaks use magnetic fields to confine plasma, but these are often only two-dimensional. Recent research suggests that using 3D magnetic fields controlled with an artificial intelligence (AI) system could be a particularly robust method.
"Up to now, we have explored the promising path for 3D optimization by combining physics, AI and real-time control. Still, the human decision is included in the optimization process," said Kim, a staff research physicist at PPPL.
The next step will be making a fully automated 3D field optimization system that works in harmony with all the other systems that control a plasma. "This is too complicated for conventional approaches, so a form of AI known as machine learning will be a key method to make a breakthrough," Kim said.
Their research is also notable because it was designed to be broadly adopted.
"Most experiments are proof of principle to show the physics," said Shousha, a Strategic Science Initiative postdoc at PPPL. "When you make things generic, modular and flexible with the future in mind, as we did here, it gives it long-term viability. But that requires a lot of additional technical, behind-the-scenes work that can sometimes be underappreciated. Seeing that our work was recognized motivates the whole team."
Kim noted the importance of collaboration across research institutions that truly made this work possible, including experiments conducted at the KSTAR tokamak in South Korea and the DIII-D tokamak in San Diego.
"Winning this award is a real honor," said Yang, a staff research physicist at PPPL. "To me, it recognizes teamwork across theory, experiments and control engineering. I'm grateful to my colleagues and for the strong institutional support at PPPL. It also motivates me to keep pushing toward solutions that make fusion more practical."
