AI diagnostic achieves major advances in fusion energy

Fusion energy systems depend on a wide variety of diagnostics to measure properties like temperature and electron density. These tools can play a crucial role in detecting instant plasma instabilities and sudden oscillations that can disrupt a reactor.

This advancement is particularly significant for Thomson scattering - a diagnostic technique that is used to study the outer edge of plasma, which is the most crucial area to measure.

Researchers can better understand the phenomenon of Diag2Diag, to better stabilize the plasma and enhance the efficiency.

Theories behind plasma stability

Diag2Diag has a crucial role in providing evidence regarding a leading theory on how resonant magnetic perturbations (RMPs) help suppress edge-localized modes (ELMs), which are sudden and cataclysmic outbursts of energy inside reactors.

AI has confirmed that RMP can create magnetic islands by reconstructing detailed temperature and density data, consequently helping stabilize the plasma and improve stability.

A principal research scientist at PPPL said, “Diag2Diag provided much more detail on how this happens and how it evolves."

The AI breakthrough in fusion energy is one step closer to achieving the holy grail of clean energy: a reliable, economical and affordable power source for the future.