Filter News
Area of Research
News Topics
- (-) Artificial Intelligence (4)
- (-) Nuclear Energy (3)
- (-) Security (2)
- 3-D Printing/Advanced Manufacturing (2)
- 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)
- Nanotechnology (3)
- National Security (7)
- Net Zero (2)
- Neutron Science (3)
- Partnerships (1)
- Physics (2)
- Polymers (1)
- Quantum Computing (5)
- Quantum Science (3)
- Simulation (3)
- Summit (4)
- Sustainable Energy (13)
- Transportation (3)
Media Contacts
Oak Ridge National Laboratory physicist Elizabeth “Libby” Johnson (1921-1996), one of the world’s first nuclear reactor operators, standardized the field of criticality safety with peers from ORNL and Los Alamos National Laboratory.
When the COVID-19 pandemic stunned the world in 2020, researchers at ORNL wondered how they could extend their support and help
Friederike (Rike) Bostelmann, who began her career in Germany, chose to come to ORNL to become part of the Lab’s efforts to shape the future of nuclear energy.
To achieve practical energy from fusion, extreme heat from the fusion system “blanket” component must be extracted safely and efficiently. ORNL fusion experts are exploring how tiny 3D-printed obstacles placed inside the narrow pipes of a custom-made cooling system could be a solution for removing heat from the blanket.
It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.
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 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.