Filter News
Area of Research
- (-) Materials (90)
- (-) Neutron Science (26)
- (-) Supercomputing (125)
- Advanced Manufacturing (5)
- Biology and Environment (59)
- Building Technologies (2)
- Clean Energy (104)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Computational Engineering (3)
- Computer Science (15)
- Electricity and Smart Grid (1)
- Energy Sciences (1)
- Functional Materials for Energy (1)
- Fusion and Fission (8)
- Fusion Energy (3)
- Isotopes (1)
- Materials for Computing (17)
- Mathematics (1)
- National Security (32)
- Nuclear Science and Technology (6)
- Quantum information Science (8)
News Topics
- (-) Computer Science (100)
- (-) Cybersecurity (9)
- (-) Frontier (29)
- (-) Microscopy (29)
- (-) Physics (36)
- (-) Polymers (19)
- (-) Sustainable Energy (20)
- 3-D Printing/Advanced Manufacturing (30)
- Advanced Reactors (6)
- Artificial Intelligence (40)
- Big Data (20)
- Bioenergy (21)
- Biology (17)
- Biomedical (30)
- Biotechnology (2)
- Buildings (8)
- Chemical Sciences (33)
- Clean Water (4)
- Climate Change (21)
- Composites (9)
- Coronavirus (20)
- Critical Materials (15)
- Decarbonization (13)
- Energy Storage (41)
- Environment (39)
- Exascale Computing (22)
- Fossil Energy (1)
- Fusion (9)
- Grid (9)
- High-Performance Computing (41)
- Irradiation (1)
- Isotopes (13)
- ITER (1)
- Machine Learning (16)
- Materials (86)
- Materials Science (90)
- Mathematics (1)
- Molten Salt (3)
- Nanotechnology (46)
- National Security (8)
- Net Zero (2)
- Neutron Science (108)
- Nuclear Energy (22)
- Partnerships (11)
- Quantum Computing (20)
- Quantum Science (35)
- Renewable Energy (1)
- Security (6)
- Simulation (14)
- Software (1)
- Space Exploration (7)
- Summit (42)
- Transformational Challenge Reactor (3)
- Transportation (23)
Media Contacts
![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
![Arjun Shankar Arjun Shankar](/sites/default/files/styles/list_page_thumbnail/public/shankar.png?itok=qqOR_eUI)
The field of “Big Data” has exploded in the blink of an eye, growing exponentially into almost every branch of science in just a few decades. Sectors such as energy, manufacturing, healthcare and many others depend on scalable data processing and analysis for continued in...
![COHERENT collaborators were the first to observe coherent elastic neutrino–nucleus scattering. Their results, published in the journal Science, confirm a prediction of the Standard Model and establish constraints on alternative theoretical models. Image c COHERENT collaborators were the first to observe coherent elastic neutrino–nucleus scattering. Their results, published in the journal Science, confirm a prediction of the Standard Model and establish constraints on alternative theoretical models. Image c](/sites/default/files/styles/list_page_thumbnail/public/SLIDESHOW%202_collaboration.jpg?itok=icKSVyYi)
After more than a year of operation at the Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL), the COHERENT experiment, using the world’s smallest neutrino detector, has found a big fingerprint of the elusive, electrically neutral particles that interact only weakly with matter.
![ORNL-Lenvio_tech_license_signing_ceremony2 ORNL-Lenvio_tech_license_signing_ceremony2](/sites/default/files/styles/list_page_thumbnail/public/ORNL-Lenvio_tech_license_signing_ceremony2.jpg?itok=xcfN-PbJ)
Virginia-based Lenvio Inc. has exclusively licensed a cyber security technology from the Department of Energy’s Oak Ridge National Laboratory that can quickly detect malicious behavior in software not previously identified as a threat.
![ORNL’s Xiahan Sang unambiguously resolved the atomic structure of MXene, a 2D material promising for energy storage, catalysis and electronic conductivity. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Carlos Jones ORNL’s Xiahan Sang unambiguously resolved the atomic structure of MXene, a 2D material promising for energy storage, catalysis and electronic conductivity. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Carlos Jones](/sites/default/files/styles/list_page_thumbnail/public/Sang_2016-P07680_0.jpg?itok=w0e5eR_U)
Researchers have long sought electrically conductive materials for economical energy-storage devices. Two-dimensional (2D) ceramics called MXenes are contenders. Unlike most 2D ceramics, MXenes have inherently good conductivity because they are molecular sheets made from the carbides ...