An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
Deborah Frincke, one of the nation’s preeminent computer scientists and cybersecurity experts, serves as associate laboratory director of ORNL’s National Security Science Directorate. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
Through a consortium of Department of Energy national laboratories, ORNL scientists are applying their expertise to provide solutions that enable the commercialization of emission-free hydrogen fuel cell technology for heavy-duty
The Accelerating Therapeutics for Opportunities in Medicine , or ATOM, consortium today announced the U.S. Department of Energy’s Oak Ridge, Argonne and Brookhaven national laboratories are joining the consortium to further develop ATOM’s artificial intelligence, or AI-driven, drug discovery platform.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and the University of Tennessee are automating the search for new materials to advance solar energy technologies.
On Feb. 18, the world will be watching as NASA’s Perseverance rover makes its final descent into Jezero Crater on the surface of Mars. Mars 2020 is the first NASA mission that uses plutonium-238 produced at the Department of Energy’s Oak Ridge National Laboratory.
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.
Artificial intelligence (AI) techniques have the potential to support medical decision-making, from diagnosing diseases to prescribing treatments. But to prioritize patient safety, researchers and practitioners must first ensure such methods are accurate.