
Filter News
Area of Research
- Biology and Environment (4)
- Computational Biology (1)
- Computer Science (2)
- Electricity and Smart Grid (1)
- Energy Science (38)
- Fusion Energy (1)
- Materials (6)
- Materials for Computing (1)
- National Security (4)
- Neutron Science (1)
- Quantum information Science (1)
- Sensors and Controls (1)
- Supercomputing (7)
- Transportation Systems (2)
News Type
News Topics
- (-) Grid (22)
- (-) Mercury (3)
- (-) Summit (8)
- (-) Transportation (36)
- 3-D Printing/Advanced Manufacturing (34)
- Advanced Reactors (13)
- Artificial Intelligence (16)
- Big Data (17)
- Bioenergy (17)
- Biology (21)
- Biomedical (11)
- Biotechnology (4)
- Buildings (21)
- Chemical Sciences (13)
- Clean Water (14)
- Composites (11)
- Computer Science (42)
- Coronavirus (11)
- Critical Materials (12)
- Cybersecurity (3)
- Emergency (1)
- Energy Storage (32)
- Environment (48)
- Exascale Computing (1)
- Fossil Energy (1)
- Frontier (1)
- Fusion (9)
- High-Performance Computing (12)
- Hydropower (6)
- Irradiation (2)
- Isotopes (5)
- ITER (3)
- Machine Learning (14)
- Materials (36)
- Materials Science (34)
- Mathematics (3)
- Microscopy (11)
- Molten Salt (5)
- Nanotechnology (12)
- National Security (3)
- Neutron Science (27)
- Nuclear Energy (19)
- Partnerships (2)
- Physics (4)
- Polymers (10)
- Quantum Computing (5)
- Quantum Science (11)
- Security (1)
- Simulation (9)
- Space Exploration (10)
- Statistics (1)
Media Contacts

Scientists have developed a new machine learning approach that accurately predicted critical and difficult-to-compute properties of molten salts, materials with diverse nuclear energy applications.

Researchers at Oak Ridge National Laboratory have developed a new automated testing capability for semiconductor devices, which is newly available to researchers and industry partners in the Grid Research Integration and Deployment Center.

Researchers at Stanford University, the European Center for Medium-Range Weather Forecasts, or ECMWF, and ORNL used the lab’s Summit supercomputer to better understand atmospheric gravity waves, which influence significant weather patterns that are difficult to forecast.

ORNL has partnered with Western Michigan University to advance intelligent road infrastructure through the development of new chip-enabled raised pavement markers. These innovative markers transmit lane-keeping information to passing vehicles, enhancing safety and enabling smarter driving in all weather conditions.

Researchers at Oak Ridge National Laboratory have opened a new virtual library where visitors can check out waveforms instead of books. So far, more than 350 users worldwide have utilized the library, which provides vital understanding of an increasingly complex grid.

A team of researchers at ORNL demonstrated that a light-duty passenger electric vehicle can be wirelessly charged at 100-kW with 96% efficiency using polyphase electromagnetic coupling coils with rotating magnetic fields.

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.

Oak Ridge National Laboratory researchers have identified the most energy-efficient 2024 model year vehicles available in the United States, including electric and hybrids, in the latest edition of the Department of Energy’s

ORNL researchers determined that a connected and automated vehicle, or CAV, traveling on a multilane highway with integrated traffic light timing control can maximize energy efficiency and achieve up to 27% savings.

Currently, the biggest hurdle for electric vehicles, or EVs, is the development of advanced battery technology to extend driving range, safety and reliability.