Filter News
Area of Research
- Advanced Manufacturing (5)
- Biological Systems (2)
- Biology and Environment (73)
- Clean Energy (63)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Computational Engineering (2)
- Computer Science (4)
- Fusion and Fission (23)
- Fusion Energy (13)
- Isotope Development and Production (1)
- Isotopes (1)
- Materials (66)
- Materials for Computing (11)
- National Security (10)
- Neutron Science (15)
- Nuclear Science and Technology (13)
- Quantum information Science (2)
- Supercomputing (68)
News Topics
- (-) Big Data (53)
- (-) Bioenergy (91)
- (-) Composites (26)
- (-) Emergency (2)
- (-) Fusion (54)
- (-) Irradiation (3)
- (-) Mercury (12)
- (-) Microscopy (51)
- (-) Molten Salt (8)
- (-) Polymers (33)
- (-) Summit (57)
- 3-D Printing/Advanced Manufacturing (119)
- Advanced Reactors (34)
- Artificial Intelligence (91)
- Biology (98)
- Biomedical (58)
- Biotechnology (22)
- Buildings (57)
- Chemical Sciences (63)
- Clean Water (29)
- Climate Change (99)
- Computer Science (187)
- Coronavirus (46)
- Critical Materials (25)
- Cybersecurity (35)
- Decarbonization (79)
- Education (4)
- Element Discovery (1)
- Energy Storage (108)
- Environment (194)
- Exascale Computing (37)
- Fossil Energy (5)
- Frontier (42)
- Grid (62)
- High-Performance Computing (84)
- Hydropower (11)
- Isotopes (53)
- ITER (7)
- Machine Learning (47)
- Materials (143)
- Materials Science (139)
- Mathematics (7)
- Microelectronics (3)
- Nanotechnology (60)
- National Security (61)
- Net Zero (13)
- Neutron Science (131)
- Nuclear Energy (107)
- Partnerships (43)
- Physics (61)
- Quantum Computing (34)
- Quantum Science (69)
- Renewable Energy (2)
- Security (24)
- Simulation (47)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Sustainable Energy (125)
- Transformational Challenge Reactor (7)
- Transportation (97)
Media Contacts
Electric vehicles can drive longer distances if their lithium-ion batteries deliver more energy in a lighter package. A prime weight-loss candidate is the current collector, a component that often adds 10% to the weight of a battery cell without contributing energy.
ORNL will lead a new DOE-funded project designed to accelerate bringing fusion energy to the grid. The Accelerate award focuses on developing a fusion power plant design concept that supports remote maintenance and repair methods for the plasma-facing components in fusion power plants.
Two fusion energy leaders have joined ORNL in the Fusion and Fission Energy and Science Directorate, or FFESD.
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%.
A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.
Scientists from more than a dozen institutions have completed a first-of-its-kind high-resolution assessment of carbon dioxide removal potential in the United States, charting a path to achieve a net-zero greenhouse gas economy by 2050.
A team of eight scientists won the Association for Computing Machinery’s 2023 Gordon Bell Prize for their study that used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.
ORNL is leading three research collaborations with fusion industry partners through the Innovation Network for FUSion Energy, or INFUSE, program that will focus on resolving technical challenges and developing innovative solutions to make practical fusion energy a reality.
Lee's paper at the August conference in Bellevue, Washington, combined weather and power outage data for three states – Texas, Michigan and Hawaii – and used a machine learning model to predict how extreme weather such as thunderstorms, floods and tornadoes would affect local power grids and to estimate the risk for outages. The paper relied on data from the National Weather Service and the U.S. Department of Energy’s Environment for Analysis of Geo-Located Energy Information, or EAGLE-I, database.