
Filter News
Area of Research
- Advanced Manufacturing (4)
- Biology and Environment (31)
- Building Technologies (1)
- Computational Biology (2)
- Computational Engineering (2)
- Computer Science (12)
- Energy Science (42)
- Fusion and Fission (5)
- Fusion Energy (7)
- Isotopes (20)
- Materials (29)
- Materials for Computing (5)
- Mathematics (1)
- National Security (18)
- Neutron Science (12)
- Nuclear Science and Technology (14)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (4)
- Supercomputing (77)
News Type
News Topics
- (-) Advanced Reactors (25)
- (-) Clean Water (30)
- (-) Composites (21)
- (-) Computer Science (153)
- (-) Cybersecurity (17)
- (-) Isotopes (38)
- (-) Software (1)
- (-) Space Exploration (23)
- (-) Summit (48)
- 3-D Printing/Advanced Manufacturing (89)
- Artificial Intelligence (92)
- Big Data (62)
- Bioenergy (84)
- Biology (100)
- Biomedical (53)
- Biotechnology (28)
- Buildings (50)
- Chemical Sciences (48)
- Coronavirus (30)
- Critical Materials (17)
- Education (2)
- Emergency (4)
- Energy Storage (64)
- Environment (164)
- Exascale Computing (52)
- Fossil Energy (7)
- Frontier (45)
- Fusion (47)
- Grid (54)
- High-Performance Computing (93)
- Hydropower (12)
- Irradiation (2)
- ITER (7)
- Machine Learning (51)
- Materials (87)
- Materials Science (89)
- Mathematics (11)
- Mercury (10)
- Microelectronics (3)
- Microscopy (34)
- Molten Salt (7)
- Nanotechnology (29)
- National Security (63)
- Neutron Science (109)
- Nuclear Energy (85)
- Partnerships (37)
- Physics (38)
- Polymers (18)
- Quantum Computing (39)
- Quantum Science (59)
- Security (17)
- Simulation (51)
- Statistics (3)
- Transportation (66)
Media Contacts

ORNL researchers reached a significant milestone by building an entire 6.5-foot turbine blade tip using novel materials. The team then tested it against the forces of simulated lightning in a specialized lab at Mississippi State University, where the blade tip emerged pristine after tests that isolate the effects of high voltage.

The Summit supercomputer did not have its many plugs pulled as planned after its five years of service. Instead, a new DOE Office of Science-backed allocation program called SummitPLUS was launched, extending Summit's production for another year. What did we learn during Summit’s bonus year of scientific discovery? Here are five projects with important results.

In early November, ORNL hosted the International Atomic Energy Agency (IAEA) Interregional Workshop on Safety, Security and Safeguards by Design in Small Modular Reactors, which welcomed 76 attendees representing 15 countries, three U.S. national labs, domestic and international industry partners, as well as IAEA officers.

A paper written by researchers from the Department of Energy’s Oak Ridge National Laboratory was selected as the top paper of 2023 by Welding Journal that explored the feasibility of using laser-blown powder direct energy deposition, or Laser-powder DED.

The ForWarn visualization tool was co-developed by ORNL with the U.S. Forest Service. The tool captures and analyzes satellite imagery to track impacts such as storms, wildfire and pests on forests across the nation.

Researchers have identified a molecule essential for the microbial conversion of inorganic mercury into the neurotoxin methylmercury, moving closer to blocking the dangerous pollutant before it forms.

Two-and-a-half years after breaking the exascale barrier, the Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory continues to set new standards for its computing speed and performance.

Researchers used the world’s fastest supercomputer, Frontier, to train an AI model that designs proteins, with applications in fields like vaccines, cancer treatments, and environmental bioremediation. The study earned a finalist nomination for the Gordon Bell Prize, recognizing innovation in high-performance computing for science.

Researchers at Oak Ridge National Laboratory used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts. This achievement earned them a finalist nomination for the prestigious Gordon Bell Prize for Climate Modeling.

A research team led by the University of Maryland has been nominated for the Association for Computing Machinery’s Gordon Bell Prize. The team is being recognized for developing a scalable, distributed training framework called AxoNN, which leverages GPUs to rapidly train large language models.