Updated software improves slicing for large-format 3D printing
In the wet, muddy places where America’s rivers and lands meet the sea, scientists from the Department of Energy’s Oak Ridge National Laboratory are unearthing clues to better understand how these vital landscapes are evolving under climate change.
Oak Ridge National Laboratory scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.
ORNL's Guang Yang and Andrew Westover have been selected to join the first cohort of DOE’s Advanced Research Projects Agency-Energy Inspiring Generations of New Innovators to Impact Technologies in Energy 2024 program. The program supports early career scientists and engineers in their work to convert disruptive ideas into impactful energy technologies.
ORNL researchers completed successful testing of a gallium nitride transistor for use in more accurate sensors operating near the core of a nuclear reactor. This is an important technical advance particularly for monitoring new, compact.
Researchers used quantum simulations to obtain new insights into the nature of neutrinos — the mysterious subatomic particles that abound throughout the universe — and their role in the deaths of massive stars.
In May, the Department of Energy’s Oak Ridge and Brookhaven national laboratories co-hosted the 15th annual International Particle Accelerator Conference, or IPAC, at the Music City Center in Nashville, Tennessee.
Researchers at ORNL and the University of Maine have designed and 3D-printed a single-piece, recyclable natural-material floor panel tested to be strong enough to replace construction materials like steel.
Erin Webb, lead for the Bioresources Science and Engineering group at Oak Ridge National Laboratory, has been elected a Fellow of the American Society of Agricultural and Biological Engineers — the society’s highest honor.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
ORNL scientists develop a sample holder that tumbles powdered photochemical materials within a neutron beamline — exposing more of the material to light for increased photo-activation and better photochemistry data capture.