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DOE national laboratory scientists led by Oak Ridge National Laboratory have developed the first tree dataset of its kind, bridging molecular information about the poplar tree microbiome to ecosystem-level processes. Credit: Andy Sproles, ORNL/U.S. Dept. of Energy

A first-ever dataset bridging molecular information about the poplar tree microbiome to ecosystem-level processes has been released by a team of DOE scientists led by ORNL. The project aims to inform research regarding how natural systems function, their vulnerability to a changing climate and ultimately how plants might be engineered for better performance as sources of bioenergy and natural carbon storage.

ORNL researchers are developing algorithms and multilayered communication and control systems that make electric vehicle chargers operate more reliably, even if there is a voltage drop or disturbance in the electric grid. Credit: Andy Sproles/ORNL, US Dept. of Energy

ORNL researchers are working to make EV charging more resilient by developing algorithms to deal with both internal and external triggers of charger failure. This will help charging stations remain available to traveling EV drivers, reducing range anxiety.

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

Scientists at ORNL have developed 3-D-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. 

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 achieved the highest wireless power transfer level for a light-duty passenger vehicle when the team demonstrated a 100-kW wireless power transfer to an EV using ORNL’s patented polyphase electromagnetic coupling coil. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

A team of researchers at ORNL demonstrated that a light-duty passenger electric vehicle can be wirelessly charged at 100-kW with 96% efficiency using polyphase electromagnetic coupling coils with rotating magnetic fields.

AI-driven attention mechanisms aid in streamlining cancer pathology reporting.

In partnership with the National Cancer Institute, researchers from the Department of Energy’s Oak Ridge National Laboratory’s Modeling Outcomes for Surveillance using Scalable Artificial Intelligence are building on their groundbreaking work to

Sean Oesch

While government regulations are slowly coming, a group of cybersecurity professionals are sharing best practices to protect large language models powering these tools. Sean Oesch, a leader in emerging cyber technologies, recently contributed to the OWASP AI Security and Privacy Guide to inform global AI security standards and regulations.

Anuj Kapadia

Anuj J. Kapadia, who heads the Advanced Computing Methods for Health Sciences Section at ORNL, has been elected as president of the Southeastern Chapter of the American Association of Physicists in Medicine. 

New system combines human, artificial intelligence to improve experimentation

To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.