Filter News
Area of Research
- Advanced Manufacturing (3)
- Biology and Environment (8)
- Clean Energy (18)
- Computer Science (3)
- Fuel Cycle Science and Technology (1)
- Fusion and Fission (10)
- Fusion Energy (1)
- Isotope Development and Production (1)
- Isotopes (2)
- Materials (24)
- Materials for Computing (2)
- National Security (16)
- Neutron Science (8)
- Nuclear Science and Technology (7)
- Quantum information Science (1)
- Sensors and Controls (1)
- Supercomputing (30)
News Type
News Topics
- (-) Artificial Intelligence (27)
- (-) Cybersecurity (17)
- (-) Nuclear Energy (25)
- (-) Partnerships (25)
- (-) Quantum Science (27)
- (-) Security (11)
- 3-D Printing/Advanced Manufacturing (43)
- Advanced Reactors (10)
- Big Data (7)
- Bioenergy (24)
- Biology (22)
- Biomedical (17)
- Biotechnology (7)
- Buildings (12)
- Chemical Sciences (27)
- Clean Water (1)
- Climate Change (21)
- Composites (9)
- Computer Science (56)
- Coronavirus (17)
- Critical Materials (10)
- Decarbonization (17)
- Education (3)
- Element Discovery (1)
- Energy Storage (40)
- Environment (35)
- Exascale Computing (9)
- Fossil Energy (1)
- Frontier (14)
- Fusion (14)
- Grid (15)
- High-Performance Computing (25)
- Isotopes (16)
- ITER (2)
- Machine Learning (12)
- Materials (58)
- Materials Science (50)
- Mercury (2)
- Microscopy (16)
- Molten Salt (2)
- Nanotechnology (26)
- National Security (16)
- Net Zero (3)
- Neutron Science (49)
- Physics (24)
- Polymers (12)
- Quantum Computing (9)
- Renewable Energy (1)
- Simulation (8)
- Space Exploration (3)
- Statistics (1)
- Summit (20)
- Sustainable Energy (32)
- Transformational Challenge Reactor (4)
- Transportation (25)
Media Contacts
ORNL was front and center recently at one of the world’s largest optical networking conferences, the 2024 Optic Fiber Communication Conference and Exhibition, or OFC. ORNL researchers had major roles at the OFC 2024, a three-day event held in San Diego, California from March 26-28 which featured thousands of the world’s leading optical communications and networking professionals.
In partnership with the National Cancer Institute, researchers from ORNL and Louisiana State University developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with exponentially more accurate information on cancer reporting.
Anuj J. Kapadia, who heads the Advanced Computing Methods for Health Sciences Section at ORNL, has been elected as president of the Southeastern Chapter of the American Association of Physicists in Medicine.
Four ORNL teams and one researcher were recognized for excellence in technology transfer and technology transfer innovation.
Gina Tourassi, associate laboratory director for computing and computational sciences at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory, has been named a fellow of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.
Ateios Systems licensed an ORNL technology for solvent-free battery component production using electron curing. Through Innovation Crossroads, Ateios continues to work with ORNL to enable readiness for production-quality battery components.
Effective Dec. 4, Gina Tourassi will assume responsibilities as associate laboratory director for the Computing and Computational Sciences Directorate at the Department of Energy’s Oak Ridge National Laboratory.
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.
ORNL is home to the world's fastest exascale supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations.
ORNL has joined a global consortium of scientists from federal laboratories, research institutes, academia and industry to address the challenges of building large-scale artificial intelligence systems and advancing trustworthy and reliable AI for