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.
Joe Hagerman, ORNL research lead for buildings integration and controls, understands the impact building technology innovations can have during times of crisis. Over a decade ago, he found himself in the middle of one of the most devastating natural disasters of the century, Hurricane Katrina.
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.
Scientists at ORNL used neutron scattering and supercomputing to better understand how an organic solvent and water work together to break down plant biomass, creating a pathway to significantly improve the production of renewable
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.
Oak Ridge National Laboratory researchers have built a novel microscope that provides a “chemical lens” for viewing biological systems including cell membranes and biofilms.
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