Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (11)
- Clean Energy (19)
- Climate and Environmental Systems (1)
- Computational Engineering (1)
- Computer Science (1)
- Fusion and Fission (1)
- Materials (28)
- Materials for Computing (6)
- National Security (8)
- Neutron Science (42)
- Nuclear Science and Technology (1)
- Supercomputing (28)
News Type
News Topics
- (-) Artificial Intelligence (29)
- (-) Big Data (8)
- (-) Mercury (2)
- (-) Neutron Science (49)
- (-) Polymers (12)
- (-) Summit (20)
- 3-D Printing/Advanced Manufacturing (44)
- Advanced Reactors (10)
- Bioenergy (24)
- Biology (22)
- Biomedical (17)
- Biotechnology (7)
- Buildings (13)
- Chemical Sciences (29)
- Clean Water (1)
- Climate Change (22)
- Composites (9)
- Computer Science (57)
- Coronavirus (17)
- Critical Materials (11)
- Cybersecurity (17)
- Decarbonization (18)
- Education (3)
- Element Discovery (1)
- Energy Storage (41)
- Environment (36)
- Exascale Computing (9)
- Fossil Energy (1)
- Frontier (14)
- Fusion (14)
- Grid (15)
- High-Performance Computing (26)
- Isotopes (17)
- ITER (2)
- Machine Learning (13)
- Materials (59)
- Materials Science (50)
- Microscopy (16)
- Molten Salt (2)
- Nanotechnology (26)
- National Security (18)
- Net Zero (3)
- Nuclear Energy (25)
- Partnerships (27)
- Physics (24)
- Quantum Computing (9)
- Quantum Science (26)
- Renewable Energy (1)
- Security (11)
- Simulation (8)
- Space Exploration (3)
- Statistics (2)
- Sustainable Energy (31)
- Transformational Challenge Reactor (4)
- Transportation (24)
Media Contacts
Vanderbilt University and ORNL announced a partnership to develop training, testing and evaluation methods that will accelerate the Department of Defense’s adoption of AI-based systems in operational environments.
Scientists at ORNL completed a study of how well vegetation survived extreme heat events in both urban and rural communities across the country in recent years. The analysis informs pathways for climate mitigation, including ways to reduce the effect of urban heat islands.
A first-ever dataset bridging molecular information about the poplar tree microbiome to ecosystem-level processes has been released by a team of DOE scientists led by ORNL. The project aims to inform research regarding how natural systems function, their vulnerability to a changing climate and ultimately how plants might be engineered for better performance as sources of bioenergy and natural carbon storage.
Jens Dilling has been named associate laboratory director for the Neutron Sciences Directorate at the Department of Energy’s Oak Ridge National Laboratory, effective April 1.
The United States could triple its current bioeconomy by producing more than 1 billion tons per year of plant-based biomass for renewable fuels, while meeting projected demands for food, feed, fiber, conventional forest products and exports, according to the DOE’s latest Billion-Ton Report led by ORNL.
In partnership with the National Cancer Institute, researchers from ORNL and Louisiana State University developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with exponentially more accurate information on cancer reporting.
Anuj J. Kapadia, who heads the Advanced Computing Methods for Health Sciences Section at ORNL, has been elected as president of the Southeastern Chapter of the American Association of Physicists in Medicine.
Gina Tourassi, associate laboratory director for computing and computational sciences at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory, has been named a fellow of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.
Corning uses neutron scattering to study the stability of different types of glass. Recently, researchers for the company have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.