The 2025 Kaul Foundation Award for Excellence in Plasma Physics Research and Technology Development was 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 received the award for their work on “optimizing 3D magnetic fields within tokamaks to minimize disruption and control edge instability while improving confinement.” Such research is essential to developing fusion systems that can reliably produce energy for the power grid. As part of the honor, each winner will receive $7,500.
“Sung-moo Yang, Sang-kyung Kim, and Ricardo Schuchat have used artificial intelligence and traditional approaches to make fundamental contributions to one of the most difficult problems in fusion energy,” said Institute Director Steve Cowley. “Their research has deepened our understanding of how to manipulate them more reliably and efficiently and is already impacting experiments around the world. We are delighted that their dedication and creativity has been recognized with this well-deserved honor.”
Inside a fusion vessel, known as a tokamak, a magnetic field is used to confine plasma into a donut shape. Keeping the plasma edge stable remains a major challenge for future fusion energy, as the plasma boundary region can become unstable and cause damage to the tokamak's interior. Researchers are investigating several approaches to controlling the plasma edge. All tokamaks use magnetic fields to confine plasma, but these are often only two-dimensional. Recent research suggests that the use of 3D magnetic fields controlled by artificial intelligence (AI) systems may be a particularly powerful method.
“To date, we have explored promising avenues for 3D optimization by combining physics, AI, and real-time control. Yet, the optimization process still involves human decisions,” said Kim, a staff research physicist at PPPL.
The next step is to create a fully automated 3D field optimization system that works in harmony with all other systems that control the plasma. “This is too complex for traditional approaches, so a type of AI known as machine learning could be a breakthrough,” Kim said.
Their study is also notable in that it is designed to be widely adopted.
“Most experiments are proofs of principle to demonstrate physics,” said Shusha, a postdoctoral fellow in PPPL's Strategic Science Initiative. “Making things generic, modular and flexible with the future in mind, as we have done here, gives us long-term viability. But it requires a lot of additional technical behind-the-scenes work that is sometimes underestimated. Seeing our work recognized motivates the whole team.”
Kim pointed to the importance of collaboration between research institutions that truly made this research possible, including experiments conducted at the KSTAR tokamak in South Korea and the DIII-D tokamak in San Diego.
“It is truly an honor to receive this award,” said Yang, a staff research physicist at PPPL. “For me, it recognizes the teamwork across theory, experiment, and control engineering. I am grateful for the strong institutional support of my colleagues and PPPL. It also motivates us to continue moving toward solutions that make fusion more practical.”
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