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Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers. Credit: ORNL, U.S. Dept. of Energy

Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.

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

ORNL’s Sergei Kalinin and Rama Vasudevan (foreground) use scanning probe microscopy to study bulk ferroelectricity and surface electrochemistry -- and generate a lot of data. Credit: Jason Richards/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.

Oak Ridge National Laboratory’s MENNDL AI software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. Credit: ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.

The students analyzed diatom images like this one to compare wild and genetically modified strains of these organisms. Credit: Alison Pawlicki/Oak Ridge National Laboratory, US Department of Energy.

Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.

Representatives from The University of Toledo and the U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL) in Tennessee are teaming up to conduct collaborative automotive materials research.” Credit: University of Toledo

ORNL and The University of Toledo have entered into a memorandum of understanding for collaborative research.

Summit supercomputer

Processes like manufacturing aircraft parts, analyzing data from doctors’ notes and identifying national security threats may seem unrelated, but at the U.S. Department of Energy’s Oak Ridge National Laboratory, artificial intelligence is improving all of these tasks.

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.

Edmon Begoli

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.