Filter News
Area of Research
- (-) Advanced Manufacturing (3)
- (-) Supercomputing (32)
- Biological Systems (1)
- Biology and Environment (58)
- Biology and Soft Matter (1)
- Clean Energy (41)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Fusion and Fission (19)
- Fusion Energy (4)
- Isotopes (5)
- Materials (22)
- Materials for Computing (2)
- National Security (12)
- Neutron Science (10)
- Nuclear Science and Technology (17)
- Quantum information Science (2)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (5)
- (-) Big Data (13)
- (-) Bioenergy (3)
- (-) Biomedical (7)
- (-) Climate Change (12)
- (-) Microscopy (2)
- (-) Nuclear Energy (2)
- Artificial Intelligence (21)
- Biology (6)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (1)
- Computer Science (45)
- Coronavirus (7)
- Cybersecurity (2)
- Decarbonization (3)
- Energy Storage (1)
- Environment (13)
- Exascale Computing (12)
- Frontier (13)
- Grid (1)
- High-Performance Computing (20)
- Machine Learning (7)
- Materials (6)
- Materials Science (9)
- Mathematics (1)
- Nanotechnology (5)
- National Security (3)
- Net Zero (1)
- Neutron Science (8)
- Physics (3)
- Quantum Computing (10)
- Quantum Science (10)
- Security (1)
- Simulation (10)
- Software (1)
- Space Exploration (1)
- Summit (21)
- Sustainable Energy (3)
- Transportation (3)
Media Contacts
ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
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.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
The world is full of “huge, gnarly problems,” as ORNL research scientist and musician Melissa Allen-Dumas puts it — no matter what line of work you’re in. That was certainly the case when she would wrestle with a tough piece of music.
An international problem like climate change needs solutions that cross boundaries, both on maps and among disciplines. Oak Ridge National Laboratory computational scientist Deeksha Rastogi embodies that approach.
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.