AI makes fusion energy smarter and safer with real-time plasma monitoring

Published: Thursday, September 4, 2025 at 11:07 pm

AI Advances Fusion Energy Safety and Efficiency

Researchers have developed two artificial intelligence (AI) systems designed to enhance the safety and efficiency of fusion energy reactors. The work, published in *Nuclear Fusion*, focuses on addressing critical challenges in plasma control, a key component in harnessing fusion power.

One AI model is designed to predict disruptions, sudden and potentially damaging instabilities in the plasma. This model, using a transparent decision tree approach, accurately predicted disruptions 94% of the time, providing warnings an average of 137 milliseconds before the event. This early warning allows for timely intervention by control systems, preventing potential damage to reactor components.

The second AI system, a multi-task learning neural network, focuses on real-time monitoring of plasma behavior. It identifies the operational mode of the plasma (L-mode or H-mode) and detects edge-localized modes (ELMs), bursts of instability that can harm reactor components. This system achieved a 96.7% success rate in recognizing plasma conditions, enabling smart decisions by control systems. The AI model uses specific physical parameters based on proven scaling laws, making it more stable and less susceptible to experimental errors.

These AI tools are currently being tested in a tokamak, a type of experimental fusion reactor. The advancements in AI-driven plasma monitoring offer a significant step forward in the development of fusion energy, promising both enhanced safety and improved performance.

BNN's Perspective:

The application of AI in fusion energy research is a promising development. While the technology is still in its early stages, the potential for increased safety and efficiency is undeniable. This research highlights the importance of continued investment in innovative technologies to accelerate the development of clean energy sources.

Keywords: fusion energy, artificial intelligence, AI, plasma, disruptions, tokamak, H-mode, L-mode, ELMs, machine learning, real-time monitoring, reactor safety, energy, clean energy, Hefei Institutes of Physical Science, Nuclear Fusion, Professor Sun Youwen

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