Filter News
Area of Research
- (-) National Security (12)
- (-) Nuclear Science and Technology (4)
- (-) Supercomputing (71)
- Advanced Manufacturing (3)
- Biology and Environment (35)
- Clean Energy (44)
- Computational Biology (1)
- Computer Science (2)
- Fusion and Fission (6)
- Fusion Energy (1)
- Isotopes (1)
- Materials (28)
- Materials for Computing (6)
- Neutron Science (15)
- Quantum information Science (2)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (5)
- (-) Computer Science (49)
- (-) Frontier (14)
- (-) Materials Science (11)
- (-) Mathematics (1)
- (-) Summit (21)
- (-) Sustainable Energy (3)
- Advanced Reactors (4)
- Artificial Intelligence (25)
- Big Data (15)
- Bioenergy (4)
- Biology (8)
- Biomedical (7)
- Biotechnology (2)
- Buildings (2)
- Chemical Sciences (1)
- Climate Change (15)
- Coronavirus (8)
- Cybersecurity (8)
- Decarbonization (4)
- Energy Storage (1)
- Environment (16)
- Exascale Computing (13)
- Fusion (6)
- Grid (4)
- High-Performance Computing (23)
- Isotopes (3)
- Machine Learning (13)
- Materials (5)
- Microscopy (2)
- Molten Salt (1)
- Nanotechnology (5)
- National Security (24)
- Net Zero (1)
- Neutron Science (7)
- Nuclear Energy (19)
- Partnerships (1)
- Physics (5)
- Quantum Computing (10)
- Quantum Science (11)
- Security (6)
- Simulation (11)
- Software (1)
- Space Exploration (2)
- Transformational Challenge Reactor (2)
- Transportation (3)
Media Contacts
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
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.
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.
Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant
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.
A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.