University of Texas-Led Team Solves a Big Problem for Fusion Energy

Summary

AUSTIN, Texas — Abundant, low-cost, clean energy — the envisioned result if scientists and engineers can successfully produce a reliable method of generating and sustaining fusion energy — took one step closer to reality, as a team of researchers from The University of Texas at Austin, Los Alamos National Laboratory and Type One Energy Group solved a longstanding problem in the field. One of the big challenges holding fusion energy back has been the ability to contain high-energy particles inside fusion reactors. When high-energy alpha particles leak from a reactor, that prevents the plasma from getting hot and dense enough to sustain the fusion reaction. To prevent them from leaking, engineers design elaborate magnetic confinement systems, but there are often holes in the magnetic field, and a tremendous amount of computational time is required to predict their locations and eliminate them. In their paper published in Physical Review Letters, the research team describes having discovered a shortcut that can help engineers design leak-proof magnetic confinement systems 10 times as fast as the gold standard method, without sacrificing accuracy. While several other big challenges remain for all magnetic fusion designs, this advance addresses the biggest challenge that’s specific to a type of fusion reactor first proposed in the 1950s, called a stellarator. “What’s most exciting is that we’re solving something that’s been an open problem for almost 70 years,” said Josh Burby, assistant professor of physics at UT and first author of the paper. “It’s a paradigm shift in how we design these reactors.” A stellarator uses external coils carrying electric currents that generate magnetic fields to confine a plasma and high-energy particles. This confinement system is often described as a “magnetic bottle.” There is a way to identify where the holes are in the magnetic bottle using Newton’s laws of motion, which is very precise but takes an enormous amount of computational tim...