Skip to main content
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. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

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.

Vittorio Badalassi, left, of Oak Ridge National Laboratory leads the Fusion Energy Reactor Models Integrator, or FERMI, project, and collaborates with ORNL computational physicist David Green. FERMI applies fission platforms to fusion reactor design. Credit: Commonwealth Fusion Systems and Colby Earles/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory expertise in fission and fusion has come together to form a new collaboration, the Fusion Energy Reactor Models Integrator, or FERMI

Verónica Melesse Vergara speaks with third and fourth graders at East Side Intermediate School in Brownsville. Credit: ORNL, U.S. Dept. of Energy

Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.

The researchers embedded a programmable model into a D-Wave quantum computer chip. Credit: D-Wave

Since the 1930s, scientists have been using particle accelerators to gain insights into the structure of matter and the laws of physics that govern our world.

Snapshot of total temperature distribution at supersonic speed of mach 2.4. Total temperature allows the team to visualize the extent of the exhaust plumes as the temperature of the plumes is much greater than that of the surrounding atmosphere. Credit: NASA

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. 

Tyler Gerczak, a materials scientist at Oak Ridge National Laboratory, is focused on post-irradiation examination and separate effects testing of current fuels for light water reactors and advanced fuel types that could be used in future nuclear systems. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy

Ask Tyler Gerczak to find a negative in working at the Department of Energy’s Oak Ridge National Laboratory, and his only complaint is the summer weather. It is not as forgiving as the summers in Pulaski, Wisconsin, his hometown.

Combining fundamental chemistry with high-performance computing resources at ORNL, researchers demonstrate a more efficient method for recovering uranium from seawater, unveiling a prototype material that outperforms best-in-class uranium adsorbents. Credit: Alexander Ivanov/Oak Ridge National Laboratory, U.S. Dept. of Energy.

Scientists have demonstrated a new bio-inspired material for an eco-friendly and cost-effective approach to recovering uranium from seawater.

ORNL staff members (from left) Ashley Shields, Michael Galloway, Ketan Maheshwari and Andrew Miskowiec are collaborating on a project focused on predicting and analyzing crystal structures of new uranium oxide phases. Credit: Jason Richards/ORNL

Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.

Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.

Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.