Three researchers at ORNL have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
While studying how bio-inspired materials might inform the design of next-generation computers, scientists at ORNL achieved a first-of-its-kind result that could have big implications for both edge computing and human health.
ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.
Several significant science and energy projects led by the ORNL will receive a total of $497 million in funding from the Inflation Reduction Act.
Over the past seven years, researchers in ORNL’s Geospatial Science and Human Security Division have mapped and characterized all structures within the United States and its territories to aid FEMA in its response to disasters. This dataset provides a consistent, nationwide accounting of the buildings where people reside and work.
Researchers in the geothermal energy industry are joining forces with fusion experts at ORNL to repurpose gyrotron technology, a tool used in fusion. Gyrotrons produce high-powered microwaves to heat up fusion plasmas.
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 researchers are developing a first-of-its-kind artificial intelligence device for neutron scattering called Hyperspectral Computed Tomography, or HyperCT.
Practical fusion energy is not just a dream at ORNL. Experts in fusion and material science are working together to develop solutions that will make a fusion pilot plant — and ultimately carbon-free, abundant fusion electricity — possible.
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.