Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet
To minimize potential damage from underground oil and gas leaks, Oak Ridge National Laboratory is co-developing a quantum sensing system to detect pipeline leaks more quickly.
A new Department of Energy report produced by Oak Ridge National Laboratory details national and international trends in hydropower, including the role waterpower plays in enhancing the flexibility and resilience of the power grid.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.
Ada Sedova’s journey to Oak Ridge National Laboratory has taken her on the path from pre-med studies in college to an accelerated graduate career in mathematics and biophysics and now to the intersection of computational science and biology
Scientists at the Department of Energy’s Oak Ridge National Laboratory have developed a new method to peer deep into the nanostructure of biomaterials without damaging the sample. This novel technique can confirm structural features in starch, a carbohydrate important in biofuel production.
ORNL computer scientist Catherine Schuman returned to her alma mater, Harriman High School, to lead Hour of Code activities and talk to students about her job as a researcher.
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.
Oak Ridge National Laboratory is training next-generation cameras called dynamic vision sensors, or DVS, to interpret live information—a capability that has applications in robotics and could improve autonomous vehicle sensing.