Filter News
Area of Research
- Advanced Manufacturing (2)
- Biology and Environment (22)
- Building Technologies (1)
- Clean Energy (37)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Computational Engineering (3)
- Computer Science (15)
- Fusion and Fission (9)
- Fusion Energy (8)
- Isotopes (1)
- Materials (48)
- Materials for Computing (7)
- Mathematics (1)
- National Security (32)
- Neutron Science (24)
- Nuclear Science and Technology (15)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (6)
- Supercomputing (100)
News Topics
- (-) Advanced Reactors (35)
- (-) Computer Science (199)
- (-) Cybersecurity (35)
- (-) Physics (64)
- 3-D Printing/Advanced Manufacturing (128)
- Artificial Intelligence (102)
- Big Data (62)
- Bioenergy (92)
- Biology (102)
- Biomedical (62)
- Biotechnology (24)
- Buildings (67)
- Chemical Sciences (74)
- Clean Water (31)
- Climate Change (106)
- Composites (30)
- Coronavirus (46)
- Critical Materials (29)
- Decarbonization (85)
- Education (5)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (112)
- Environment (201)
- Exascale Computing (44)
- Fossil Energy (6)
- Frontier (46)
- Fusion (59)
- Grid (67)
- High-Performance Computing (94)
- Hydropower (11)
- Irradiation (3)
- Isotopes (57)
- ITER (7)
- Machine Learning (51)
- Materials (150)
- Materials Science (149)
- Mathematics (10)
- Mercury (12)
- Microelectronics (4)
- Microscopy (51)
- Molten Salt (9)
- Nanotechnology (60)
- National Security (73)
- Net Zero (14)
- Neutron Science (140)
- Nuclear Energy (111)
- Partnerships (51)
- Polymers (33)
- Quantum Computing (39)
- Quantum Science (73)
- Renewable Energy (2)
- Security (26)
- Simulation (53)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Summit (61)
- Sustainable Energy (130)
- Transformational Challenge Reactor (7)
- Transportation (99)
Media Contacts
Power companies and electric grid developers turn to simulation tools as they attempt to understand how modern equipment will be affected by rapidly unfolding events in a complex grid.
Researchers conduct largest, most accurate molecular dynamics simulations to date of two million correlated electrons using Frontier, the world’s fastest supercomputer. The simulation, which exceed an exaflop using full double precision, is 1,000 times greater in size and speed than any quantum chemistry simulation of it's kind.
In the wet, muddy places where America’s rivers and lands meet the sea, scientists from the Department of Energy’s Oak Ridge National Laboratory are unearthing clues to better understand how these vital landscapes are evolving under climate change.
Oak Ridge National Laboratory scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.
Researchers used quantum simulations to obtain new insights into the nature of neutrinos — the mysterious subatomic particles that abound throughout the universe — and their role in the deaths of massive stars.
In May, the Department of Energy’s Oak Ridge and Brookhaven national laboratories co-hosted the 15th annual International Particle Accelerator Conference, or IPAC, at the Music City Center in Nashville, Tennessee.
Anuj J. Kapadia, who leads the Advanced Computing in Health Sciences Section at the Department of Energy’s Oak Ridge National Laboratory, was named a 2024 Fellow by the American Association of Physicists in Medicine.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
Researchers tackling national security challenges at ORNL are upholding an 80-year legacy of leadership in all things nuclear. Today, they’re developing the next generation of technologies that will help reduce global nuclear risk and enable safe, secure, peaceful use of nuclear materials, worldwide.
A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.