Filter News
Area of Research
- Advanced Manufacturing (11)
- Biology and Environment (13)
- Building Technologies (1)
- Clean Energy (32)
- Climate and Environmental Systems (1)
- Computational Engineering (2)
- Computer Science (5)
- Fusion Energy (1)
- Materials (7)
- Materials for Computing (3)
- Mathematics (1)
- National Security (3)
- Neutron Science (1)
- Quantum information Science (3)
- Supercomputing (10)
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (31)
- (-) Big Data (16)
- (-) Climate Change (22)
- (-) Machine Learning (10)
- (-) Quantum Science (10)
- (-) Security (1)
- (-) Simulation (7)
- Advanced Reactors (13)
- Artificial Intelligence (13)
- Bioenergy (15)
- Biology (17)
- Biomedical (11)
- Biotechnology (3)
- Buildings (19)
- Chemical Sciences (9)
- Clean Water (13)
- Composites (9)
- Computer Science (39)
- Coronavirus (11)
- Critical Materials (12)
- Cybersecurity (3)
- Decarbonization (8)
- Energy Storage (31)
- Environment (43)
- Exascale Computing (1)
- Frontier (1)
- Fusion (9)
- Grid (20)
- High-Performance Computing (11)
- Hydropower (6)
- Irradiation (2)
- Isotopes (5)
- ITER (3)
- Materials (35)
- Materials Science (33)
- Mathematics (1)
- Mercury (3)
- Microscopy (11)
- Molten Salt (5)
- Nanotechnology (12)
- National Security (3)
- Net Zero (1)
- Neutron Science (27)
- Nuclear Energy (19)
- Partnerships (1)
- Physics (4)
- Polymers (9)
- Quantum Computing (4)
- Space Exploration (10)
- Statistics (1)
- Summit (6)
- Sustainable Energy (44)
- Transportation (35)
Media Contacts
Global carbon emissions from inland waters such as lakes, rivers, streams and ponds are being undercounted by about 13% and will likely continue to rise given climate events and land use changes, ORNL scientists found.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.
Researchers at Oak Ridge National Laboratory have empirically quantified the shifts in routine daytime activities, such as getting a morning coffee or takeaway dinner, following safer at home orders during the early days of the COVID-19 pandemic.
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.
Oak Ridge National Laboratory is debuting a small satellite ground station that uses high-performance computing to support automated detection of changes to Earth’s landscape.
To study how space radiation affects materials for spacecraft and satellites, Oak Ridge National Laboratory scientists sent samples to the International Space Station. The results will inform design of radiation-resistant magnetic and electronic systems.
Oak Ridge National Laboratory researchers recently used large-scale additive manufacturing with metal to produce a full-strength steel component for a wind turbine, proving the technique as a viable alternative to
A new analysis from Oak Ridge National Laboratory shows that intensified aridity, or drier atmospheric conditions, is caused by human-driven increases in greenhouse gas emissions. The findings point to an opportunity to address and potentially reverse the trend by reducing emissions.
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.