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Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.
When it’s up and running, the ITER fusion reactor will be very big and very hot, with more than 800 cubic meters of hydrogen plasma reaching 170 million degrees centigrade. The systems that fuel and control it, on the other hand, will be small and very cold. Pellets of frozen gas will be shot int...