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The DEMAND single crystal diffractometer at the High Flux Isotope Reactor, or HFIR, is the latest neutron instrument at the Department of Energy’s Oak Ridge National Laboratory to be equipped with machine learning-assisted software, called ReTIA. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy

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.

ZEISS Head of Additive Manufacturing Technology Claus Hermannstaedter, left, and ORNL Interim Associate Laboratory Director for Energy Science and Technology Rick Raines sign a licensing agreement that allows ORNL’s machine-learning algorithm, Simurgh, to be used for rapid evaluations of 3D-printed components with industrial X-ray computed tomography, or CT. Using machine learning in CT scanning is expected to reduce the time and cost of inspections of 3D-printed parts by more than ten times.

A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine

Image of outerspace

Few things carry the same aura of mystery as dark matter. The name itself radiates secrecy, suggesting something hidden in the shadows of the Universe.

ORNL’s RapidCure improves lithium-ion electrode production by producing electrodes faster, reducing the energy necessary for manufacturing and eliminating the need for a solvent recycling unit. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.

Oak Ridge National Laboratory’s Leah Broussard shows a neutron-absorbing "wall" that stops all neutrons but in theory would allow hypothetical mirror neutrons to pass through. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

To solve a long-standing puzzle about how long a neutron can “live” outside an atomic nucleus, physicists entertained a wild but testable theory positing the existence of a right-handed version of our left-handed universe.

SCGSR Awardee Jacob Zettlemoyer, Indiana University Bloomington, led data analysis and worked with ORNL’s Mike Febbraro on coatings, shown under blue light, to shift argon light to visible wavelengths to boost detection. Credit: Rex Tayloe/Indiana University

The COHERENT particle physics experiment at the Department of Energy’s Oak Ridge National Laboratory has firmly established the existence of a new kind of neutrino interaction.

Distinguished Inventors

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

Oak Ridge National Laboratory entrance sign

Geoffrey L. Greene, a professor at the University of Tennessee, Knoxville, who holds a joint appointment with ORNL, will be awarded the 2021 Tom Bonner Prize for Nuclear Physics from the American Physical Society.

The n-helium-3 precision experiment, conducted at ORNL, measured the weak force between protons and neutrons by detecting the tiny electrical signal produced when a neutron and a helium-3 nucleus combine and then decay as they move through the helium gas target cell. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

Through a one-of-a-kind experiment at ORNL, nuclear physicists have precisely measured the weak interaction between protons and neutrons. The result quantifies the weak force theory as predicted by the Standard Model of Particle Physics.

Researcher Chase Joslin uses Peregrine software to monitor and analyze a component being 3D printed at the Manufacturing Demonstration Facility at ORNL. Credit: Luke Scime/ORNL, U.S. Dept. of Energy.

Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.