Researchers at Oak Ridge National Laboratory have identified a key need for future hydropower innovations – full-scale testing – to better inform developers and operators before making major investments.
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.
As the United States shifts away from fossil-fuel-burning cars and trucks, scientists at the Department of Energy’s Oak Ridge and Argonne national laboratories are exploring options for another form of transportation: trains. The research focuses on zero-carbon hydrogen and other low-carbon fuels as viable alternatives to diesel for the rail industry.
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 at ORNL recently demonstrated a new technology to better control how power flows to and from commercial buildings equipped with solar, wind or other renewable energy generation.
To further the potential benefits of the nation’s hydropower resources, researchers at Oak Ridge National Laboratory have developed and maintain a comprehensive water energy digital platform called HydroSource.
Oak Ridge National Laboratory researchers are developing a first-of-its-kind artificial intelligence device for neutron scattering called Hyperspectral Computed Tomography, or HyperCT.
Oak Ridge National Laboratory’s Innovation Crossroads program welcomes six new science and technology innovators from across the United States to the sixth cohort.
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.