Filter News
Area of Research
News Topics
- (-) Artificial Intelligence (3)
- (-) Clean Water (1)
- (-) Nanotechnology (2)
- (-) Summit (4)
- 3-D Printing/Advanced Manufacturing (1)
- Big Data (1)
- Bioenergy (3)
- Biology (3)
- Biomedical (2)
- Buildings (4)
- Chemical Sciences (1)
- Climate Change (7)
- Computer Science (5)
- Coronavirus (2)
- Cybersecurity (1)
- Decarbonization (8)
- Energy Storage (2)
- Environment (8)
- Exascale Computing (1)
- Frontier (3)
- High-Performance Computing (4)
- Isotopes (1)
- Machine Learning (2)
- Materials (7)
- Materials Science (3)
- Microscopy (3)
- National Security (1)
- Net Zero (1)
- Neutron Science (2)
- Partnerships (1)
- Physics (1)
- Quantum Computing (5)
- Quantum Science (3)
- Simulation (3)
- Sustainable Energy (6)
- 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.
Researchers at ORNL are tackling a global water challenge with a unique material designed to target not one, but two toxic, heavy metal pollutants for simultaneous removal.
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 team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
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.