Filter News
Area of Research
- Advanced Manufacturing (7)
- Biology and Environment (12)
- Clean Energy (35)
- Computer Science (1)
- Fusion and Fission (10)
- Fusion Energy (2)
- Isotope Development and Production (1)
- Isotopes (7)
- Materials (23)
- Materials for Computing (4)
- National Security (11)
- Neutron Science (6)
- Nuclear Science and Technology (6)
- Quantum information Science (1)
- Supercomputing (16)
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (44)
- (-) Cybersecurity (17)
- (-) Exascale Computing (9)
- (-) Fossil Energy (1)
- (-) Fusion (14)
- (-) Isotopes (17)
- (-) Net Zero (3)
- (-) Space Exploration (3)
- Advanced Reactors (10)
- Artificial Intelligence (29)
- Big Data (8)
- Bioenergy (24)
- Biology (22)
- Biomedical (17)
- Biotechnology (7)
- Buildings (13)
- Chemical Sciences (29)
- Clean Water (1)
- Climate Change (22)
- Composites (9)
- Computer Science (57)
- Coronavirus (17)
- Critical Materials (11)
- Decarbonization (18)
- Education (3)
- Element Discovery (1)
- Energy Storage (41)
- Environment (36)
- Frontier (14)
- Grid (15)
- High-Performance Computing (26)
- ITER (2)
- Machine Learning (13)
- Materials (59)
- Materials Science (50)
- Mercury (2)
- Microscopy (16)
- Molten Salt (2)
- Nanotechnology (26)
- National Security (18)
- Neutron Science (49)
- Nuclear Energy (25)
- Partnerships (26)
- Physics (24)
- Polymers (12)
- Quantum Computing (9)
- Quantum Science (26)
- Renewable Energy (1)
- Security (11)
- Simulation (8)
- Statistics (2)
- Summit (20)
- Sustainable Energy (31)
- Transformational Challenge Reactor (4)
- Transportation (24)
Media Contacts
Building innovations from ORNL will be on display in Washington, D.C. on the National Mall June 7 to June 9, 2024, during the U.S. Department of Housing and Urban Development’s Innovation Housing Showcase. For the first time, ORNL’s real-time building evaluator was demonstrated outside of a laboratory setting and deployed for building construction.
Scientists have uncovered the properties of a rare earth element that was first discovered 80 years ago at the very same laboratory, opening a new pathway for the exploration of elements critical in modern technology, from medicine to space travel.
The United States could triple its current bioeconomy by producing more than 1 billion tons per year of plant-based biomass for renewable fuels, while meeting projected demands for food, feed, fiber, conventional forest products and exports, according to the DOE’s latest Billion-Ton Report led by ORNL.
Chuck Greenfield, former assistant director of the DIII-D National Fusion Program at General Atomics, has joined ORNL as ITER R&D Lead.
Two different teams that included Oak Ridge National Laboratory employees were honored Feb. 20 with Secretary’s Honor Achievement Awards from the Department of Energy. This is DOE's highest form of employee recognition.
Four scientists affiliated with ORNL were named Battelle Distinguished Inventors during the lab’s annual Innovation Awards on Dec. 1 in recognition of being granted 14 or more United States patents.
The Department of Energy’s Office of Science has allocated supercomputer access to a record-breaking 75 computational science projects for 2024 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program. DOE is awarding 60% of the available time on the leadership-class supercomputers at DOE’s Argonne and Oak Ridge National Laboratories to accelerate discovery and innovation.
As vehicles gain technological capabilities, car manufacturers are using an increasing number of computers and sensors to improve situational awareness and enhance the driving experience.
The Department of Energy’s Office of Science has selected three ORNL research teams to receive funding through DOE’s new Biopreparedness Research Virtual Environment initiative.
A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine