Filter News
Area of Research
- Advanced Manufacturing (3)
- Biological Systems (2)
- Biology and Environment (52)
- Clean Energy (55)
- Computational Engineering (1)
- Computer Science (2)
- Electricity and Smart Grid (2)
- Fusion and Fission (3)
- Fusion Energy (1)
- Materials (24)
- Materials for Computing (1)
- Mathematics (1)
- National Security (7)
- Neutron Science (7)
- Nuclear Science and Technology (1)
- Quantum information Science (2)
- Sensors and Controls (1)
- Supercomputing (20)
News Type
News Topics
- (-) Bioenergy (63)
- (-) Clean Water (27)
- (-) Composites (14)
- (-) Frontier (24)
- (-) Grid (43)
- (-) Physics (30)
- (-) Renewable Energy (1)
- 3-D Printing/Advanced Manufacturing (65)
- Advanced Reactors (21)
- Artificial Intelligence (56)
- Big Data (36)
- Biology (73)
- Biomedical (39)
- Biotechnology (13)
- Buildings (35)
- Chemical Sciences (28)
- Climate Change (67)
- Computer Science (119)
- Coronavirus (28)
- Critical Materials (13)
- Cybersecurity (17)
- Decarbonization (51)
- Education (1)
- Emergency (2)
- Energy Storage (59)
- Environment (143)
- Exascale Computing (25)
- Fossil Energy (4)
- Fusion (37)
- High-Performance Computing (53)
- Hydropower (11)
- Irradiation (2)
- Isotopes (30)
- ITER (5)
- Machine Learning (31)
- Materials (74)
- Materials Science (74)
- Mathematics (6)
- Mercury (10)
- Microelectronics (2)
- Microscopy (31)
- Molten Salt (6)
- Nanotechnology (28)
- National Security (36)
- Net Zero (9)
- Neutron Science (73)
- Nuclear Energy (70)
- Partnerships (15)
- Polymers (15)
- Quantum Computing (21)
- Quantum Science (37)
- Security (11)
- Simulation (35)
- Software (1)
- Space Exploration (22)
- Statistics (1)
- Summit (36)
- Sustainable Energy (86)
- Transformational Challenge Reactor (3)
- Transportation (62)
Media Contacts
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
Scientists at ORNL are looking for a happy medium to enable the grid of the future, filling a gap between high and low voltages for power electronics technology that underpins the modern U.S. electric grid.
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.
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.
The 2023 top science achievements from HFIR and SNS feature a broad range of materials research published in high impact journals such as Nature and Advanced Materials.
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 19-member team of scientists from across the national laboratory complex won the Association for Computing Machinery’s 2023 Gordon Bell Special Prize for Climate Modeling for developing a model that uses the world’s first exascale supercomputer to simulate decades’ worth of cloud formations.
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.
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.