Yigit Gunsur Elmacioglu, PhD student at Princeton University MAE department, won the best student talk award at the first-ever Open-Source Software for Fusion Energy (OSSFE) conference for his presentation “DESC: Stellarator Equilibrium and Optimization Code“.
Yufan Xu, a postdoctoral researcher at PPPL, won the National Lab Research SLAM award for his talk, “Can Terminator 2 Help Humanity Unlock Unlimited Fusion Energy?”
PBS Space Time features divertorlets in a new video on fusion energy.
“By learning from past experiments, rather than incorporating information from physics-based models, the AI could develop a final control policy that supported a stable, high-powered plasma regime in real time, at a real reactor,” said Princeton Plasma Physics Laboratory research leader Egemen Kolemen at the time, about a year ago.
Controlling the superheated plasma that makes up the whirling core of a fusion reactor is simple. You just have to predict the future.
Borrowing inspiration from the movie Terminator 2, Yufan Xu, an associate research physicist specializing in liquid metals in the Princeton Plasma Physics Laboratory’s Tokamak Experimental Science Department, argues that liquid metal can be an ideal material to protect the interior walls of doughnut-shaped fusion devices known as tokamaks.
As a part of a broad set of investments around artificial intelligence, Princeton University has launched AI for Accelerating Invention, an initiative to achieve faster breakthroughs across engineering disciplines, including biomedicine, robotics and nuclear fusion.
Undergraduate students contributed to our group's efforts in the development of the DESC stellarator optimizaton code through the Science Undergraduate Laboratory Internships (SULI) program at PPPL.
Francisco Saenz, a graduate student in Plasma Control Group, shares how we’re studying how liquid metal can draw away excess heat to protect the reactor.
Egemen Kolemen, a staff research physicist at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) and an associate professor of mechanical and aerospace engineering at Princeton University, was awarded the American Nuclear Society's. (ANS) 2024 Technical Accomplishment Award for his research on using machine learning for controlling fusion reactors.
Yufan Xu presented Lithium Experimental Application Platform (LEAP).
Achieving a sustained fusion reaction is a delicate balancing act, requiring a sea of moving parts to come together to maintain a high-performing plasma: one that is dense enough, hot enough, and confined for long enough for fusion to take place.