Filter News
Area of Research
- Advanced Manufacturing (2)
- Biology and Environment (28)
- Biology and Soft Matter (1)
- Clean Energy (44)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (6)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (8)
- Fusion Energy (7)
- Materials (18)
- Materials for Computing (1)
- National Security (15)
- Neutron Science (9)
- Nuclear Science and Technology (12)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Supercomputing (41)
- Transportation Systems (1)
News Topics
- (-) Advanced Reactors (34)
- (-) Artificial Intelligence (95)
- (-) Decarbonization (81)
- 3-D Printing/Advanced Manufacturing (125)
- Big Data (58)
- Bioenergy (92)
- Biology (100)
- Biomedical (59)
- Biotechnology (23)
- Buildings (59)
- Chemical Sciences (69)
- Clean Water (30)
- Climate Change (103)
- Composites (29)
- Computer Science (194)
- Coronavirus (46)
- Critical Materials (29)
- Cybersecurity (35)
- Education (4)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (111)
- Environment (198)
- Exascale Computing (39)
- Fossil Energy (6)
- Frontier (44)
- Fusion (55)
- Grid (65)
- High-Performance Computing (88)
- Hydropower (11)
- Irradiation (3)
- Isotopes (54)
- ITER (7)
- Machine Learning (48)
- Materials (145)
- Materials Science (144)
- Mathematics (9)
- Mercury (12)
- Microelectronics (4)
- Microscopy (51)
- Molten Salt (8)
- Nanotechnology (60)
- National Security (68)
- Net Zero (14)
- Neutron Science (133)
- Nuclear Energy (110)
- Partnerships (49)
- Physics (63)
- Polymers (33)
- Quantum Computing (35)
- Quantum Science (70)
- Renewable Energy (2)
- Security (24)
- Simulation (49)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Summit (59)
- Sustainable Energy (129)
- Transformational Challenge Reactor (7)
- Transportation (97)
Media Contacts
Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.
For the first time, Oak Ridge National Laboratory has completed testing of nuclear fuels using MiniFuel, an irradiation vehicle that allows for rapid experimentation.
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool
In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.
Oak Ridge National Laboratory is using artificial intelligence to analyze data from published medical studies associated with bullying to reveal the potential of broader impacts, such as mental illness or disease.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.
OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
The Department of Energy’s Oak Ridge National Laboratory is collaborating with industry on six new projects focused on advancing commercial nuclear energy technologies that offer potential improvements to current nuclear reactors and move new reactor designs closer to deployment.
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