Filter News
Area of Research
- (-) Supercomputing (24)
- Advanced Manufacturing (1)
- Biology and Environment (8)
- Clean Energy (21)
- Computer Science (1)
- Fusion and Fission (4)
- Fusion Energy (4)
- Isotopes (3)
- Materials (12)
- Materials for Computing (1)
- National Security (6)
- Neutron Science (10)
- Nuclear Science and Technology (20)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (2)
News Topics
- (-) Coronavirus (8)
- (-) Cybersecurity (1)
- (-) Frontier (1)
- (-) Grid (2)
- (-) Isotopes (1)
- (-) Microscopy (2)
- (-) Nuclear Energy (1)
- (-) Summit (13)
- 3-D Printing/Advanced Manufacturing (3)
- Artificial Intelligence (5)
- Big Data (8)
- Bioenergy (3)
- Biology (1)
- Biomedical (8)
- Chemical Sciences (1)
- Climate Change (1)
- Computer Science (29)
- Decarbonization (1)
- Energy Storage (1)
- Environment (4)
- Exascale Computing (2)
- Fusion (1)
- High-Performance Computing (2)
- Machine Learning (4)
- Materials (2)
- Materials Science (7)
- Mathematics (1)
- Molten Salt (1)
- Nanotechnology (4)
- National Security (1)
- Neutron Science (8)
- Physics (2)
- Polymers (1)
- Quantum Science (8)
- Sustainable Energy (4)
- Transportation (2)
Media Contacts
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.
The prospect of simulating a fusion plasma is a step closer to reality thanks to a new computational tool developed by scientists in fusion physics, computer science and mathematics at ORNL.
An international team of researchers has discovered the hydrogen atoms in a metal hydride material are much more tightly spaced than had been predicted for decades — a feature that could possibly facilitate superconductivity at or near room temperature and pressure.
Researchers across the scientific spectrum crave data, as it is essential to understanding the natural world and, by extension, accelerating scientific progress.