A team of fusion researchers from Princeton and the U.S. Department of Energy’s Princeton Plasma Physics Laboratory (PPPL) have used machine learning to control harmful energy bursts in plasma, a key challenge in achieving sustained fusion reactions. The team, led by Egemen Kolemen, demonstrated the highest fusion performance without these energy bursts at two different facilities. The machine learning approach significantly reduces computation time, allowing for real-time adjustments to the plasma's conditions. The team's findings, published in Nature Communications, highlight the potential of artificial intelligence in overcoming challenges in developing fusion power as a clean energy resource.
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