A new AI tool named Diag2Diag, developed by Princeton University, generates detailed plasma data where physical sensors cannot reach, a major step toward viable fusion energy.
Oct 1, 2025
Source:
Princeton Engineering - Princeton University
AI Generates Missing Fusion Data
Researchers from Princeton University and the Princeton Plasma Physics Laboratory (PPPL) have developed a groundbreaking AI tool that creates highly detailed data from inside a fusion reactor, even in areas where physical sensors cannot see.
The tool, named Diag2Diag, uses existing sensor readings to generate synthetic data, effectively filling in the gaps left by missing or limited diagnostics. The team published its findings in the journal Nature Communications.
How It Works
Diag2Diag functions by collecting information from various sensors and predicting what other, more specialized diagnostics would report. The process is akin to recovering the audio for a silent film by analyzing the visual cues in each frame.
This AI can produce synthetic data at a higher resolution than physical hardware can achieve, offering an unprecedented view of plasma behavior.
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Source:
http://Phys.org
Boosting Reactor Efficiency and Design
The AI's ability to see the unseen is particularly crucial for monitoring the plasma's edge, or "pedestal." This region is vital for maintaining stability in a fusion reactor but is notoriously difficult to measure with conventional tools.
By generating this critical data virtually, Diag2Diag has significant implications for future fusion power plants.
Key Advantages for Fusion
Compact and Affordable Reactors: With fewer physical sensors required, reactors can be designed to be smaller, cheaper, and simpler to build and maintain.
Enhanced Control: High-resolution data allows for more precise, real-time control over the plasma, a key requirement for commercializing fusion energy.
Improved Reliability: The AI can compensate for failing or degraded sensors, a vital feature for plants designed to operate 24/7.
The model was trained using real-world experimental data from the DIII-D National Fusion Facility, ensuring its predictions are grounded in actual plasma physics.
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Source:
Princeton Plasma Physics Laboratory
