
Filter News
Area of Research
- Advanced Manufacturing (2)
- Biology and Environment (24)
- Biology and Soft Matter (1)
- Computational Biology (1)
- Energy Science (19)
- Fusion and Fission (17)
- Fusion Energy (4)
- Isotopes (17)
- Materials (34)
- Materials for Computing (5)
- National Security (15)
- Neutron Science (56)
- Nuclear Science and Technology (18)
- Quantum information Science (1)
- Supercomputing (37)
News Type
News Topics
- (-) Cybersecurity (14)
- (-) Frontier (44)
- (-) Isotopes (33)
- (-) Molten Salt (2)
- (-) Nanotechnology (17)
- (-) Neutron Science (82)
- (-) Nuclear Energy (66)
- (-) Polymers (9)
- (-) Space Exploration (13)
- 3-D Printing/Advanced Manufacturing (56)
- Advanced Reactors (12)
- Artificial Intelligence (77)
- Big Data (45)
- Bioenergy (68)
- Biology (80)
- Biomedical (42)
- Biotechnology (25)
- Buildings (30)
- Chemical Sciences (35)
- Clean Water (16)
- Composites (11)
- Computer Science (111)
- Coronavirus (19)
- Critical Materials (5)
- Education (2)
- Emergency (3)
- Energy Storage (32)
- Environment (116)
- Exascale Computing (51)
- Fossil Energy (6)
- Fusion (38)
- Grid (32)
- High-Performance Computing (81)
- Hydropower (6)
- ITER (4)
- Machine Learning (37)
- Materials (51)
- Materials Science (55)
- Mathematics (8)
- Mercury (7)
- Microelectronics (3)
- Microscopy (23)
- National Security (60)
- Partnerships (36)
- Physics (34)
- Quantum Computing (35)
- Quantum Science (48)
- Security (16)
- Simulation (42)
- Software (1)
- Statistics (2)
- Summit (40)
- Transportation (30)
Media Contacts

The National Center for Computational Sciences, located at the Department of Energy’s Oak Ridge National Laboratory, made a strong showing at computing conferences this fall. Staff from across the center participated in numerous workshops and invited speaking engagements.

ORNL’s National Security Sciences Directorate partnered with the University of Tennessee’s Howard H. Baker Jr. School of Public Policy and Public Affairs to develop a graduate certificate in nuclear security that launched in the fall of 2024.

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.

In early November, researchers at the Department of Energy’s Argonne National Laboratory used the fastest supercomputer on the planet to run the largest astrophysical simulation of the universe ever conducted. The achievement was made using the Frontier supercomputer at Oak Ridge National Laboratory.

ORNL has been recognized in the 21st edition of the HPCwire Readers’ and Editors’ Choice Awards, presented at the 2024 International Conference for High Performance Computing, Networking, Storage and Analysis in Atlanta, Georgia.

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.

Teletrix, a company specializing in radiation training tools, has transitioned from a research and development license to a commercial license for its augmented reality, or AR, platform that simulates ionizing radiation. This advanced platform was developed using technologies licensed from ORNL.

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.