The quest for boundless clean fusion energy, akin to the reactions at the core of the sun, has been a long-standing challenge. But now, Princeton University and its Princeton Plasma Physics Laboratory researchers have made a significant leap forward with an AI model that could solve one of the major roadblocks.
Tokamak reactors, with their unique donut shape, are currently leading the pack in fusion reactor designs. They use magnets to squeeze plasma particles together, creating a lasting fusion reaction. However, even a minor disruption to the magnetic field can cause the plasma to escape, ending the reaction and potentially damaging the reactor.
This is where the Princeton team's AI model comes in. It can predict these so-called tearing mode instabilities 300 milliseconds before they occur, providing enough time to regain control of the plasma. This breakthrough is due to the AI model being trained on real data from previous fusion experiments, rather than theoretical physics models.
The team tested the algorithm on a real reactor, the DIII-D National Fusion Facility in San Diego, and found that their AI-based system could control the power being fed into the reactor and the shape of the plasma to keep the particles in check.
While this is a significant step forward, it's still early days. The researchers acknowledge that their work is proof-of-concept at this stage and requires further fine-tuning. However, they remain hopeful that their model could be refined and eventually applied to other reactors to optimize the reaction or harvest the energy from it.
With AI set to play a large role in controlling and maintaining fusion reactions, this breakthrough brings us a step closer to the dream of boundless clean fusion energy.
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