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Balendra Sutharshan

In the mid-1980s, Balendra Sutharshan moved to Canada from the island nation of Sri Lanka. That move set Sutharshan on a path that had him heading continent-spanning collaborations and holding leadership posts at multiple Department of Energy

ORNL and NASA’s Jet Propulsion Laboratory scientists studied the formation of amorphous ice like the exotic ice found in interstellar space and on Jupiter’s moon, Europa. Credit: NASA/JPL-Caltech

Researchers from NASA’s Jet Propulsion Laboratory and Oak Ridge National Laboratory successfully created amorphous ice, similar to ice in interstellar space and on icy worlds in our solar system. They documented that its disordered atomic behavior is unlike any ice on Earth.

By using computer-aided design and additive manufacturing, developers can improve the performance characteristics of geothermal tools, such as this optimized rotor design, and reduce production cost. Credit: ORNL/U.S. Dept. of Energy

Additive manufacturing can make the design and production of specialized tools for geothermal energy cheaper and more efficient, according to a study by Oak Ridge National Laboratory.

Gina Accawi, ORNL’s group leader for digital manufacturing and analyses framework, is making sure advanced manufacturing software and systems keep pace in a secure cyberspace and 5G world. Credit: ORNL/U.S. Dept. of Energy

As a computer engineer at Oak Ridge National Laboratory, Gina Accawi has long been the quiet and steady force behind some of the Department of Energy’s most widely used online tools and applications.

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

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

Sergei Kalinin

Sergei Kalinin, a scientist and inventor at the Department of Energy’s Oak Ridge National Laboratory, has been elected a fellow of the Microscopy Society of America professional society.

Brenda Smith, shown here working with a gas viscometer in her research lab, is one of several people concurrently researching the thermophysical properties of feedstock gas. Their research will support computational researchers who are designing processes to separate isotopes. Credit: Carlos Jones/ORNL, US Dept. of Energy

For years Brenda Smith found fulfillment working with nuclear batteries, a topic she’s been researching as a chemist at Oak Ridge National Laboratory.

ORNL, in collaboration with Cincinnati, Inc., used the Big Area Additive Manufacturing machine to 3D print a mold made of recycled thermoplastic composite and syntactic foam, demonstrating the potential for multimaterials in large-scale applications. Credit: ORNL/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers, in collaboration with Cincinnati Inc., demonstrated the potential for using multimaterials and recycled composites in large-scale applications by 3D printing a mold that replicated a single facet of a

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.