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Media Contacts
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
For years, Duane Starr led workshops at ORNL to help others from across the U.S. government understand uranium processing technologies. After his retirement, Starr donated a 5-foot-tall working model, built in his garage, that demonstrates vibration harmonics, consistent with operation of a super critical gas centrifuge rotor, a valuable resource to ongoing ORNL-led workshops.
How do you get water to float in midair? With a WAND2, of course. But it’s hardly magic. In fact, it’s a scientific device used by scientists to study matter.
Currently, the biggest hurdle for electric vehicles, or EVs, is the development of advanced battery technology to extend driving range, safety and reliability.
Using neutrons to see the additive manufacturing process at the atomic level, scientists have shown that they can measure strain in a material as it evolves and track how atoms move in response to stress.
ORNL’s Fulvia Pilat and Karren More recently participated in the inaugural 2023 Nanotechnology Infrastructure Leaders Summit and Workshop at the White House.
In 2023, the National School on X-ray and Neutron Scattering, or NXS, marked its 25th year during its annual program, held August 6–18 at the Department of Energy’s Oak Ridge and Argonne National Laboratories.
The Spallation Neutron Source — already the world’s most powerful accelerator-based neutron source — will be on a planned hiatus through June 2024 as crews work to upgrade the facility. Much of the work — part of the facility’s Proton Power Upgrade project — will involve building a connector between the accelerator and the planned Second Target Station.
The Department of Energy’s Office of Science has selected three ORNL research teams to receive funding through DOE’s new Biopreparedness Research Virtual Environment initiative.
Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.