Filter News
Area of Research
News Topics
- (-) Nanotechnology (3)
- (-) Summit (4)
- 3-D Printing/Advanced Manufacturing (2)
- Artificial Intelligence (4)
- Big Data (4)
- Bioenergy (13)
- Biology (16)
- Biomedical (3)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (4)
- Clean Water (2)
- Climate Change (21)
- Composites (1)
- Computer Science (9)
- Coronavirus (3)
- Cybersecurity (3)
- Decarbonization (14)
- Energy Storage (2)
- Environment (25)
- Exascale Computing (3)
- Frontier (4)
- Fusion (4)
- Grid (2)
- High-Performance Computing (7)
- Hydropower (3)
- Isotopes (1)
- ITER (1)
- Machine Learning (4)
- Materials (8)
- Materials Science (4)
- Mercury (1)
- Microscopy (7)
- National Security (7)
- Net Zero (2)
- Neutron Science (3)
- Nuclear Energy (3)
- Partnerships (1)
- Physics (2)
- Polymers (1)
- Quantum Computing (5)
- Quantum Science (3)
- Security (2)
- Simulation (3)
- Sustainable Energy (13)
- Transportation (3)
Media Contacts
A new paper published in Nature Communications adds further evidence to the bradykinin storm theory of COVID-19’s viral pathogenesis — a theory that was posited two years ago by a team of researchers at the Department of Energy’s Oak Ridge National Laboratory.
Scientists at ORNL have created a miniaturized environment to study the ecosystem around poplar tree roots for insights into plant health and soil carbon sequestration.
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.