Filter News
Area of Research
- Biological Systems (1)
- Biology and Environment (75)
- Biology and Soft Matter (1)
- Clean Energy (32)
- Climate and Environmental Systems (2)
- Fusion and Fission (20)
- Fusion Energy (4)
- Isotopes (2)
- Materials (16)
- Materials for Computing (1)
- National Security (9)
- Neutron Science (4)
- Nuclear Science and Technology (16)
- Quantum information Science (1)
- Supercomputing (35)
News Type
News Topics
- (-) Bioenergy (48)
- (-) Climate Change (46)
- (-) Composites (5)
- (-) Environment (100)
- (-) Frontier (23)
- (-) Nuclear Energy (52)
- (-) Simulation (29)
- (-) Software (1)
- 3-D Printing/Advanced Manufacturing (35)
- Advanced Reactors (8)
- Artificial Intelligence (44)
- Big Data (21)
- Biology (56)
- Biomedical (28)
- Biotechnology (10)
- Buildings (17)
- Chemical Sciences (21)
- Clean Water (14)
- Computer Science (80)
- Coronavirus (17)
- Critical Materials (1)
- Cybersecurity (14)
- Decarbonization (43)
- Education (1)
- Emergency (2)
- Energy Storage (28)
- Exascale Computing (24)
- Fossil Energy (4)
- Fusion (28)
- Grid (23)
- High-Performance Computing (42)
- Hydropower (5)
- Isotopes (25)
- ITER (2)
- Machine Learning (21)
- Materials (39)
- Materials Science (41)
- Mathematics (5)
- Mercury (7)
- Microelectronics (2)
- Microscopy (20)
- Molten Salt (1)
- Nanotechnology (16)
- National Security (33)
- Net Zero (8)
- Neutron Science (46)
- Partnerships (14)
- Physics (26)
- Polymers (7)
- Quantum Computing (17)
- Quantum Science (27)
- Renewable Energy (1)
- Security (10)
- Space Exploration (12)
- Summit (30)
- Sustainable Energy (42)
- Transformational Challenge Reactor (3)
- Transportation (27)
Media Contacts
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.
When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.
ORNL researchers have teamed up with other national labs to develop a free platform called Open Energy Data Initiative Solar Systems Integration Data and Modeling to better analyze the behavior of electric grids incorporating many solar projects.
Four ORNL researchers traveled to Warsaw, Poland, during the first week of April to support the opening of Poland’s first Clean Energy Training Center, a regional hub dedicated to providing workforce development and training to expand new nuclear
ORNL scientists contributed to a DOE technical study that found transitioning coal plants to nuclear power plants would create high-paying jobs at the converted plants and hundreds of new jobs locally.
Computational scientists at ORNL have published a study that questions a long-accepted factor in simulating the molecular dynamics of water: the 2 femtosecond time step. According to the team’s findings, using anything greater than a 0.5 femtosecond time step can introduce errors in both the dynamics and thermodynamics when simulating water using a rigid-body description.
Groundbreaking report provides ambitious framework for accelerating clean energy deployment while minimizing risks and costs in the face of climate change.
Scientists at Oak Ridge National Laboratory and six other Department of Energy national laboratories have developed a United States-based perspective for achieving net-zero carbon emissions.
The U.S. Environmental Protection Agency has approved the registration and use of a renewable gasoline blendstock developed by Vertimass LLC and ORNL that can significantly reduce the emissions profile of vehicles when added to conventional fuels.
Simulations performed on the Summit supercomputer at ORNL are cutting through that time and expense by helping researchers digitally customize the ideal alloy.