Artificial intelligence reframes nuclear material studies
The future of nuclear energy, which can produce electricity without harmful emissions, depends on discovery of new materials. A scientist at Argonne is using computer vision to separate the best candidates from a crowded field.
A student in Carnegie Mellon University's School of Computer Science (SCS) has used reinforcement learning to help control nuclear fusion reactions, a significant step toward harnessing the immense power produced in nuclear fusion as a source of clean, abundant energy.
Just as a clogged kitchen sink can bring household routines to a halt, a blockage in a nuclear reactor's heat exchanger can slow operations and require urgent attention. Researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory are now using artificial intelligence to spot these hidden clogs early.…