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Media Contacts
Scientists at ORNL used neutrons to end a decades-long debate about an enzyme cancer uses.
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.
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.
ORNL’s Matthew Loyd will receive a Department of Energy Office of Science Early Career Research award.
The "SNS LEGO Model Middle School Outreach Program" invites middle school students to build a LEGO model of the SNS, a major scientific accelerator. This engaging initiative aims to teach students about STEM careers and the inner workings of the SNS through hands-on construction and interactive lessons. Launching next spring, the program seeks to inspire interest in science and engineering among young learners.
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.
A group of scientists at the Department of Energy’s Oak Ridge National Laboratory have conducted neutron scattering research to reveal key information about fungus cell membranes that could aid in developing new antifungal treatments.
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.