Illuminating businesses and homes with the star-sustaining power of fusion will be one of the greatest engineering challenges in human history. In order to recreate the energy-generating physics at the center of our Sun—which uses a lot of gravity to squeeze atoms together—reactors on Earth have to compensate for this lack of mass with an immense increase in heat.
At around 100 million degrees Celsius, light nuclei in the form of an electron soup known as plasma can overcome strong electric repulsion and fuse via quantum tunneling. While that’s all well and good, there’s just one pretty big problem—containing that ultra-hot plasma in the first place. That’s because plasma has a tendency to escape the magnetic fields containing it within reactors, which immediately spells the end of the fusion reaction. But scientists from Princeton, as well as the Princeton Plasma Physics Laboratory (PPPL), are employing AI to avoid these plasma mishaps and hopefully keep future fusion reactions from this particular form of self-sabotage.
Using the U.S.’s DIII-D experimental fusion reactor in San Diego, researchers demonstrated that their AI model trained on experimental data could detect what are known as “tearing mode” instabilities—a type of plasma disruption when plasma-containing magnetic field lines break—some 300 milliseconds in advance. Although that’s not enough time for humans to react to an instability, AI can readily change parameters to avoid the tear, and thus keep the reaction stable. The results of the work were published last week in the journal Nature.
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