Scientists conducted a groundbreaking study on the genetic data of over half a million U.S. veterans, using tools from the Oak Ridge National Laboratory to analyze 2,068 traits from the Million Veteran Program.
ORNL researchers created and tested two methods for transforming coal into the scarce mineral graphite, which is used in batteries for electric vehicles.
Scientists at ORNL have developed a first-ever urban heat wave simulation that takes into account the compounding effects from building infrastructure. The method provides a more accurate picture of the impacts from excessive heat on at-risk
Researchers at Oak Ridge National Laboratory used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts.
Researchers from ORNL have taken a major step forward in using quantum mechanics to enhance sensing devices, a new advancement that could be used in a wide range of areas, including materials characterization, improved imaging and biological and medical
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.
U2opia Technology has licensed Situ and Heartbeat, a package of technologies from the Department of Energy’s Oak Ridge National Laboratory that offer a new method for advanced cybersecurity monitoring in real time.
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.
To speed the arrival of the next-generation solid-state batteries that will power electric vehicles and other technologies, scientists led by ORNL advanced the development of flexible, durable sheets of electrolytes.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of th