Filter News
Area of Research
- Advanced Manufacturing (4)
- Biology and Environment (18)
- Building Technologies (1)
- Clean Energy (54)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Computational Engineering (3)
- Computer Science (13)
- Electricity and Smart Grid (1)
- Fuel Cycle Science and Technology (1)
- Fusion and Fission (11)
- Fusion Energy (9)
- Isotope Development and Production (1)
- Isotopes (4)
- Materials (23)
- Materials for Computing (4)
- Mathematics (1)
- National Security (22)
- Neutron Science (17)
- Nuclear Science and Technology (20)
- Nuclear Systems Modeling, Simulation and Validation (2)
- Quantum information Science (4)
- Sensors and Controls (2)
- Supercomputing (59)
News Type
News Topics
- (-) Advanced Reactors (24)
- (-) Artificial Intelligence (48)
- (-) Biomedical (28)
- (-) Computer Science (101)
- (-) Cybersecurity (20)
- (-) Grid (37)
- (-) Machine Learning (25)
- (-) Nuclear Energy (46)
- (-) Security (13)
- 3-D Printing/Advanced Manufacturing (76)
- Big Data (24)
- Bioenergy (39)
- Biology (40)
- Biotechnology (11)
- Buildings (35)
- Chemical Sciences (43)
- Clean Water (15)
- Climate Change (46)
- Composites (20)
- Coronavirus (28)
- Critical Materials (23)
- Decarbonization (31)
- Education (3)
- Element Discovery (1)
- Energy Storage (74)
- Environment (81)
- Exascale Computing (11)
- Fossil Energy (2)
- Frontier (16)
- Fusion (26)
- High-Performance Computing (41)
- Hydropower (6)
- Irradiation (2)
- Isotopes (23)
- ITER (5)
- Materials (94)
- Materials Science (87)
- Mathematics (2)
- Mercury (5)
- Microelectronics (1)
- Microscopy (27)
- Molten Salt (8)
- Nanotechnology (38)
- National Security (21)
- Net Zero (5)
- Neutron Science (78)
- Partnerships (30)
- Physics (28)
- Polymers (21)
- Quantum Computing (14)
- Quantum Science (37)
- Renewable Energy (1)
- Simulation (16)
- Space Exploration (13)
- Statistics (2)
- Summit (27)
- Sustainable Energy (75)
- Transformational Challenge Reactor (4)
- Transportation (61)
Media Contacts
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.
Kate Evans, director for the Computational Sciences and Engineering Division at ORNL, has been awarded the 2024 Society for Industrial and Applied Mathematicians Activity Group on Mathematics of Planet Earth Prize.
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.
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.
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
Pablo Moriano, a research scientist in the Computer Science and Mathematics Division at ORNL, was selected as a member of the 2024 Class of MGB-SIAM Early Career Fellows.
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
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.
Corning uses neutron scattering to study the stability of different types of glass. Recently, researchers for the company have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.