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Media Contacts
A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.
ORNL's Spallation Neutron Source, the nation’s leading source of pulsed neutron beams for research, was recently restarted after nine months of upgrade work.
Summer interns at the Department of Energy’s Oak Ridge National Laboratory recently dove into various smart devices to better understand cybersecurity vulnerabilities posed by technology meant to simplify a user’s life.
Distinguished materials scientist Takeshi Egami has spent his career revealing the complex atomic structure of metallic glass and other liquids — sometimes sharing theories with initially resistant minds in the scientific community.
In a game-changing study, ORNL scientists developed a deep learning model — a type of artificial intelligence that mimics human brain function — to analyze high-speed videos of plasma plumes during a process called pulsed laser deposition.
For the first time, ORNL will run equipment developed at its research facilities on a commercially available quantum network at EPB Quantum Network powered by Qubitekk to help validate the technology's commercial viability.
On Feb. 15, 2024, the one billionth item, also known as an “occupancy,” was scanned at the Port of Aqaba, Jordan, one of the early sites where radiation detection equipment was installed. This milestone shows the extent of countries committed to preventing the spread of radioactive material through the amount of data volunteered to ORNL for continuous improvement. As adversaries push the limits of smuggling dangerous material, this collaboration pushes back through science-backed analysis.
Researchers at the Department of Energy’s Oak Ridge National Laboratory have found a chemical “chameleon” that could improve the process used to purify rare-earth metals used in clean energy, medical and national security applications.
A team led by scientists at ORNL identified and demonstrated a method to process a plant-based material called nanocellulose that reduced energy needs by a whopping 21%, using simulations on the lab’s supercomputers and follow-on analysis.
As a mechanical engineer in building envelope materials research at ORNL, Bryan Maldonado sees opportunities to apply his scientific expertise virtually everywhere he goes, from coast to coast. As an expert in understanding how complex systems operate, he’s using machine learning methods to control the process and ultimately optimize performance.