A developing method to gauge the occurrence of a nuclear reactor anomaly has the potential to save millions of dollars.
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.
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.
An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.
Combining expertise in physics, applied math and computing, Oak Ridge National Laboratory scientists are expanding the possibilities for simulating electromagnetic fields that underpin phenomena in materials design and telecommunications.
After its long journey to Mars beginning this summer, NASA’s Perseverance rover will be powered across the planet’s surface in part by plutonium produced at the Department of Energy’s Oak Ridge National Laboratory.
A team led by Dan Jacobson of Oak Ridge National Laboratory used the Summit supercomputer at ORNL to analyze genes from cells in the lung fluid of nine COVID-19 patients compared with 40 control patients.
Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
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