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The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines

ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.

Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.

From left, Amit Naskar, Ngoc Nguyen and Christopher Bowland in ORNL’s Carbon and Composites Group bring a new capability—structural health monitoring—to strong, lightweight materials promising for transportation applications.

Carbon fiber composites—lightweight and strong—are great structural materials for automobiles, aircraft and other transportation vehicles. They consist of a polymer matrix, such as epoxy, into which reinforcing carbon fibers have been embedded. Because of differences in the mecha...

ORNL researchers Todd Toops, Charles Finney, and Melanie DeBusk (left to right) hold an example of a particulate filter used to collect harmful emissions in vehicles.

Researchers are looking to neutrons for new ways to save fuel during the operation of filters that clean the soot, or carbon and ash-based particulate matter, emitted by vehicles. A team of researchers from the Energy and Transportation Science Division at the Department of En...