
Filter News
Area of Research
- Advanced Manufacturing (3)
- Biology and Environment (20)
- Computer Science (4)
- Energy Science (52)
- Fuel Cycle Science and Technology (1)
- Fusion and Fission (11)
- Fusion Energy (1)
- Isotope Development and Production (1)
- Isotopes (2)
- Materials (41)
- Materials for Computing (5)
- National Security (10)
- Neutron Science (16)
- Nuclear Science and Technology (8)
- Quantum information Science (1)
- Sensors and Controls (1)
- Supercomputing (36)
News Type
News Topics
- (-) Artificial Intelligence (35)
- (-) Bioenergy (25)
- (-) Composites (12)
- (-) Coronavirus (17)
- (-) Energy Storage (43)
- (-) Machine Learning (13)
- (-) Nuclear Energy (28)
- (-) Quantum Science (31)
- (-) Security (12)
- 3-D Printing/Advanced Manufacturing (48)
- Advanced Reactors (12)
- Big Data (8)
- Biology (26)
- Biomedical (17)
- Biotechnology (10)
- Buildings (15)
- Chemical Sciences (35)
- Clean Water (2)
- Computer Science (63)
- Critical Materials (11)
- Cybersecurity (17)
- Education (3)
- Element Discovery (1)
- Environment (38)
- Exascale Computing (13)
- Fossil Energy (1)
- Frontier (16)
- Fusion (17)
- Grid (16)
- High-Performance Computing (32)
- Isotopes (20)
- ITER (2)
- Materials (60)
- Materials Science (56)
- Mercury (2)
- Microelectronics (1)
- Microscopy (17)
- Molten Salt (3)
- Nanotechnology (29)
- National Security (18)
- Neutron Science (54)
- Partnerships (31)
- Physics (26)
- Polymers (13)
- Quantum Computing (13)
- Simulation (10)
- Space Exploration (3)
- Statistics (1)
- Summit (22)
- Transportation (26)
Media Contacts

Researchers at ORNL have developed an innovative new technique using carbon nanofibers to enhance binding in carbon fiber and other fiber-reinforced polymer composites – an advance likely to improve structural materials for automobiles, airplanes and other applications that require lightweight and strong materials.

A research team from the Department of Energy’s Oak Ridge National Laboratory, in collaboration with North Carolina State University, has developed a simulation capable of predicting how tens of thousands of electrons move in materials in real time, or natural time rather than compute time.

Analyzing massive datasets from nuclear physics experiments can take hours or days to process, but researchers are working to radically reduce that time to mere seconds using special software being developed at the Department of Energy’s Lawrence Berkeley and Oak Ridge national laboratories.

Gerald Tuskan, director of the Center for Bioenergy Innovation and a Corporate Fellow at ORNL, has been awarded the Marcus Wallenberg Prize, the world’s highest honor in the field of forestry, for his pioneering work in sequencing and analyzing the first tree genome.

Working at nanoscale dimensions, billionths of a meter in size, a team of scientists led by ORNL revealed a new way to measure high-speed fluctuations in magnetic materials. Knowledge obtained by these new measurements could be used to advance technologies ranging from traditional computing to the emerging field of quantum computing.

Researchers at ORNL joined forces with EPB of Chattanooga and the University of Tennessee at Chattanooga to demonstrate the first transmission of an entangled quantum signal using multiple wavelength channels and automatic polarization stabilization over a commercial network with no downtime.

A team of scientists with two Department of Energy Bioenergy Research Centers — the Center for Bioenergy Innovation at Oak Ridge National Laboratory and the Center for Advanced Bioenergy and Bioproducts Innovation at the University of Illinois Urbana-Champaign — identified a gene in a poplar tree that enhances photosynthesis and can boost tree height by about 30% in the field and by as much as 200% in the greenhouse.

The Department of Energy announced a $67 million investment in several AI projects from institutions in both government and academia as part of its AI for Science initiative. Six ORNL-led (or co-led) projects received funding.

A new technology to continuously place individual atoms exactly where they are needed could lead to new materials for devices that address critical needs for the field of quantum computing and communication that cannot be produced by conventional means.

A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.