Filter News
Area of Research
- (-) National Security (8)
- (-) Supercomputing (21)
- Biology and Environment (40)
- Biology and Soft Matter (1)
- Clean Energy (24)
- Computational Biology (1)
- Computer Science (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (2)
- Fusion and Fission (3)
- Isotopes (2)
- Materials (21)
- Materials for Computing (2)
- Neutron Science (5)
News Topics
- (-) Bioenergy (3)
- (-) Biomedical (4)
- (-) Energy Storage (3)
- (-) Environment (4)
- (-) Machine Learning (8)
- (-) Quantum Science (4)
- (-) Summit (7)
- 3-D Printing/Advanced Manufacturing (1)
- Artificial Intelligence (9)
- Big Data (4)
- Biology (7)
- Biotechnology (1)
- Buildings (3)
- Chemical Sciences (2)
- Climate Change (7)
- Computer Science (14)
- Coronavirus (4)
- Critical Materials (1)
- Cybersecurity (5)
- Decarbonization (2)
- Exascale Computing (6)
- Frontier (7)
- Grid (5)
- High-Performance Computing (9)
- Materials (8)
- Materials Science (5)
- Microscopy (2)
- Nanotechnology (3)
- National Security (13)
- Neutron Science (2)
- Partnerships (1)
- Physics (2)
- Quantum Computing (7)
- Security (4)
- Simulation (5)
- Space Exploration (1)
- Sustainable Energy (2)
Media Contacts
A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.
A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.
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.
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.