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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.

A zoomed in view of downtown Chattanooga’s sensors, which allowed the researchers to create building occupancy schedules that could enable improved energy efficiency and faster emergency responses. Credit: Andy Berres/ORNL, U.S. Dept. of Energy

Every day, hundreds of thousands of commuters across the country travel from houses, apartments and other residential spaces to commercial buildings — from offices and schools to gyms and grocery stores.

A new computational approach by ORNL can more quickly scan large-scale satellite images, such as these of Puerto Rico, for more accurate mapping of complex infrastructure like buildings. Credit: Maxar Technologies and Dalton Lunga/Oak Ridge National Laboratory, U.S. Dept. of Energy

A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.