Filter News
Area of Research
- (-) Biology and Environment (9)
- (-) Neutron Science (8)
- Advanced Manufacturing (14)
- Building Technologies (1)
- Clean Energy (50)
- Computational Engineering (1)
- Computer Science (5)
- Fusion and Fission (17)
- Fusion Energy (11)
- Materials (17)
- Materials for Computing (4)
- National Security (15)
- Nuclear Science and Technology (13)
- Quantum information Science (7)
- Supercomputing (23)
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (6)
- (-) Machine Learning (8)
- (-) Quantum Science (2)
- (-) Security (2)
- Artificial Intelligence (10)
- Big Data (8)
- Bioenergy (39)
- Biology (57)
- Biomedical (17)
- Biotechnology (8)
- Chemical Sciences (5)
- Clean Water (13)
- Climate Change (32)
- Composites (2)
- Computer Science (20)
- Coronavirus (8)
- Decarbonization (18)
- Energy Storage (6)
- Environment (78)
- Exascale Computing (4)
- Fossil Energy (1)
- Frontier (3)
- Grid (2)
- High-Performance Computing (16)
- Hydropower (8)
- Materials (10)
- Materials Science (12)
- Mathematics (3)
- Mercury (7)
- Microscopy (9)
- Nanotechnology (5)
- National Security (3)
- Net Zero (1)
- Neutron Science (56)
- Nuclear Energy (2)
- Physics (3)
- Polymers (2)
- Quantum Computing (1)
- Renewable Energy (1)
- Simulation (10)
- Space Exploration (2)
- Summit (8)
- Sustainable Energy (26)
- Transportation (3)
Media Contacts
Scientists at ORNL have developed 3D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments
Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.
Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s Oak Ridge National Laboratory, with a mission to better understand and predict environmental change.
When reading the novel Jurassic Park as a teenager, Jerry Parks found the passages about gene sequencing and supercomputers fascinating, but never imagined he might someday pursue such futuristic-sounding science.
A new report published by ORNL assessed how advanced manufacturing and materials, such as 3D printing and novel component coatings, could offer solutions to modernize the existing fleet and design new approaches to hydropower.
The presence of minerals called ash in plants makes little difference to the fitness of new naturally derived compound materials designed for additive manufacturing, an Oak Ridge National Laboratory-led team found.
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.
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.
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.