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ORNL’s Erin Webb is co-leading a new Circular Bioeconomy Systems Convergent Research Initiative focused on advancing production and use of renewable carbon from Tennessee to meet societal needs. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

ORNL’s Erin Webb is co-leading a new Circular Bioeconomy Systems Convergent Research Initiative focused on advancing production and use of renewable carbon from Tennessee to meet societal needs. 

An international team using neutrons set the first benchmark (one nanosecond) for a polymer-electrolyte and lithium-salt mixture. Findings could produce safer, more powerful lithium batteries. Credit: Phoenix Pleasant/ORNL

An international team using neutrons set the first benchmark (one nanosecond) for a polymer-electrolyte and lithium-salt mixture. Findings could produce safer, more powerful lithium batteries.

Neutron Scattering Society

The Neutron Scattering Society of America, or NSSA, recognized Oak Ridge National Laboratory’s Ke An and Ken Herwig as fellows for their outstanding contributions to neutron scattering. 

ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user. 
 

Jens Dilling has been named associate laboratory director for the Neutron Sciences Directorate at the Department of Energy’s Oak Ridge National Laboratory, effective April 1.

Jens Dilling has been named associate laboratory director for the Neutron Sciences Directorate at the Department of Energy’s Oak Ridge National Laboratory, effective April 1.

3D printed “Frankenstein design” collimator show the “scars” where the individual parts are joined

Scientists at ORNL have developed 3D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments

Images showing distortion caused by residual stress in the horizontal and vertical axes of material. ORNL researchers found that simply adding material in critical regions mitigates the accumulation of stress. Credit: ORNL, U.S. Dept. of Energy

ORNL scientists have determined how to avoid costly and potentially irreparable damage to large metallic parts fabricated through additive manufacturing, also known as 3D printing, that is caused by residual stress in the material. 

ORNL engineer Canan Karakaya uses computational modeling to design and improve chemical reactors and how they are operated to convert methane, carbon dioxide, ammonia or ethanol into higher-value chemicals or energy-dense fuels. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Canan Karakaya, a R&D Staff member in the Chemical Process Scale-Up group at ORNL, was inspired to become a chemical engineer after she experienced a magical transformation that turned ammonia gas into ammonium nitrate, turning a liquid into white flakes gently floating through the air. 

Astrophysicists at the State University of New York, Stony Brook, and University of California, Berkeley created 3D simulations of X-ray bursts on the surfaces of neutron stars. Two views of these X-ray bursts are shown: the left column is viewed from above while the right column shows it from a shallow angle above the surface.

Astrophysicists at the State University of New York, Stony Brook and University of California, Berkeley, used the Oak Ridge Leadership Computing Facility’s Summit supercomputer to compare models of X-ray bursts in 2D and 3D. 

ORNL researchers developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with more accurate information on cancer reporting.

In partnership with the National Cancer Institute, researchers from ORNL and Louisiana State University developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with exponentially more accurate information on cancer reporting.