![White car (Porsche Taycan) with the hood popped is inside the building with an american flag on the wall.](/sites/default/files/styles/featured_square_large/public/2024-06/2024-P09317.jpg?h=8f9cfe54&itok=m6sQhZRq)
Filter News
Area of Research
News Topics
- (-) Artificial Intelligence (4)
- (-) Bioenergy (6)
- (-) Cybersecurity (2)
- (-) Grid (2)
- (-) High-Performance Computing (1)
- (-) Sustainable Energy (5)
- 3-D Printing/Advanced Manufacturing (5)
- Biology (1)
- Biomedical (5)
- Chemical Sciences (1)
- Climate Change (1)
- Composites (1)
- Computer Science (17)
- Coronavirus (5)
- Decarbonization (1)
- Energy Storage (1)
- Environment (4)
- Exascale Computing (1)
- Frontier (2)
- Isotopes (1)
- Machine Learning (1)
- Materials (2)
- Materials Science (7)
- Microscopy (2)
- Molten Salt (1)
- Nanotechnology (6)
- National Security (1)
- Neutron Science (21)
- Nuclear Energy (1)
- Physics (7)
- Quantum Science (8)
- Security (1)
- Summit (10)
- Transportation (2)
Media Contacts
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
![Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing. Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing.](/sites/default/files/styles/list_page_thumbnail/public/2018-P09551.jpg?itok=q7Ri01Qb)
Scientists at the Department of Energy’s Oak Ridge National Laboratory have created a recipe for a renewable 3D printing feedstock that could spur a profitable new use for an intractable biorefinery byproduct: lignin.
![ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system. ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.](/sites/default/files/styles/list_page_thumbnail/public/news/images/RAvENNA%20release%20pic.png?itok=2bDpK5Mo)
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the