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ORNL seismic researcher Chengping Chai placed seismic sensors on the ground at various distances from an ORNL nuclear reactor to learn whether they could detect its operating state. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.

Rigoberto Advincula

Rigoberto Advincula, a renowned scientist at ORNL and professor of Chemical and Biomolecular Engineering at the University of Tennessee, has won the Netzsch North American Thermal Analysis Society Fellows Award for 2023.

Robert Wagner

SAE International has awarded ORNL Buildings and Transportation Science Division Director Robert Wagner with the SAE Medal of Honor for his dedication and support of the organization’s mission of advancing mobility solutions.

Merlin Theodore

Merlin Theodore is one of eight new board members announced by President Biden; she will join the 25-member board for a six-year term.

Seven scientists at the Department of Energy’s Oak Ridge National Laboratory have been named Battelle Distinguished Inventors, in recognition of their obtaining 14 or more patents during their careers at the lab. Credit: ORNL, U.S. Dept. of Energy

Seven scientists at the Department of Energy’s Oak Ridge National Laboratory have been named Battelle Distinguished Inventors, in recognition of their obtaining 14 or more patents during their careers at the lab.

A team led by Raymond Borges Hink has developed a method using blockchain to protect communications between electronic devices in the electric grid, preventing cyberattacks and cascading blackouts. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Although blockchain is best known for securing digital currency payments, researchers at the Department of Energy’s Oak Ridge National Laboratory are using it to track a different kind of exchange: It’s the first time blockchain has ever been used to validate communication among devices on the electric grid.

Researchers from ORNL and Argonne National Laboratory will work with Wabtec, a leading manufacturer of freight locomotives, to develop the hardware and control strategies for a single cylinder, dual-fuel engine to demonstrate the viability of using alternative fuels for locomotives. The team’s goal is to reduce carbon emissions from the roughly 25,000 locomotives already in use in North America. Credit: ORNL, U.S. Dept. of Energy

As the United States shifts away from fossil-fuel-burning cars and trucks, scientists at the Department of Energy’s Oak Ridge and Argonne national laboratories are exploring options for another form of transportation: trains. The research focuses on zero-carbon hydrogen and other low-carbon fuels as viable alternatives to diesel for the rail industry.

Michelle Kidder received the lab’s Director’s Award for Outstanding Individual Accomplishment in Science and Technology for her decades-long work mentoring students, teachers and early-career staff. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.

Susan Hubbard, ORNL’s deputy for science and technology, and Ricardo Marc-Antoni Duncanson, founder of Marc-Antoni Racing, celebrated the company's licensing of ORNL-developed technologies during an event on Oct. 17. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Marc-Antoni Racing has licensed a collection of patented energy storage technologies developed at ORNL. The technologies focus on components that enable fast-charging, energy-dense batteries for electric and hybrid vehicles and grid storage.

Paul Brackman loads 3D-printed metal samples into a tower for examination using an X-ray CT scan in DOE’s Manufacturing Demonstration Facility at ORNL. Credit: Brittany Cramer/ORNL, U.S. Dept. of Energy

A new deep-learning framework developed at ORNL is speeding up the process of inspecting additively manufactured metal parts using X-ray computed tomography, or CT, while increasing the accuracy of the results. The reduced costs for time, labor, maintenance and energy are expected to accelerate expansion of additive manufacturing, or 3D printing.