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Generative model explores tungsten microstructure under fusion conditions
A comparison of real SEM tungsten microstructures (left column) with machine learning–generated synthetic microstructures (right) for different values of the model setting parameters. Adjusting the model setting controls how diverse or sharp the synthetic microstructures appear. (Image: ORNL, DOE)
Researchers have developed a model to generate images that serve as synthetic data close-ups of tungsten surfaces under fusion reactor conditions.
Tungsten is a top-choice material for plasma-facing components (PFCs) in fusion machines, so understanding tungsten’s performance is critical to the safety and longevity of component designs.
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