Filter News
Area of Research
- (-) Neutron Science (42)
- (-) Supercomputing (67)
- Advanced Manufacturing (6)
- Biological Systems (1)
- Biology and Environment (39)
- Clean Energy (128)
- Climate and Environmental Systems (1)
- Computational Biology (2)
- Computational Engineering (2)
- Computer Science (9)
- Electricity and Smart Grid (3)
- Functional Materials for Energy (1)
- Fusion and Fission (9)
- Fusion Energy (2)
- Isotope Development and Production (1)
- Isotopes (8)
- Materials (99)
- Materials Characterization (1)
- Materials for Computing (18)
- Materials Under Extremes (1)
- National Security (24)
- Nuclear Science and Technology (5)
- Quantum information Science (1)
- Sensors and Controls (1)
- Transportation Systems (2)
News Topics
- (-) Artificial Intelligence (39)
- (-) Biomedical (26)
- (-) Grid (5)
- (-) Materials Science (33)
- (-) Transportation (10)
- 3-D Printing/Advanced Manufacturing (10)
- Advanced Reactors (2)
- Big Data (21)
- Bioenergy (13)
- Biology (15)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (7)
- Clean Water (2)
- Climate Change (17)
- Composites (1)
- Computer Science (98)
- Coronavirus (17)
- Critical Materials (3)
- Cybersecurity (9)
- Decarbonization (7)
- Energy Storage (14)
- Environment (28)
- Exascale Computing (24)
- Fossil Energy (1)
- Frontier (30)
- Fusion (2)
- High-Performance Computing (41)
- Isotopes (2)
- Machine Learning (16)
- Materials (28)
- Mathematics (1)
- Microscopy (8)
- Molten Salt (1)
- Nanotechnology (19)
- National Security (8)
- Net Zero (1)
- Neutron Science (103)
- Nuclear Energy (7)
- Partnerships (1)
- Physics (17)
- Polymers (3)
- Quantum Computing (19)
- Quantum Science (29)
- Security (6)
- Simulation (15)
- Software (1)
- Space Exploration (5)
- Summit (43)
- Sustainable Energy (11)
Media Contacts
The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
The Department of Energy’s Oak Ridge National Laboratory hosted its Smoky Mountains Computational Science and Engineering Conference for the first time in person since the COVID pandemic broke in 2020. The conference, which celebrated its 20th consecutive year, took place at the Crowne Plaza Hotel in downtown Knoxville, Tenn., in late August.
Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.
ORNL hosted its fourth Artificial Intelligence for Robust Engineering and Science, or AIRES, workshop from April 18-20. Over 100 attendees from government, academia and industry convened to identify research challenges and investment areas, carving the future of the discipline.
Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s Oak Ridge National Laboratory, with a mission to better understand and predict environmental change.
To support the development of a revolutionary new open fan engine architecture for the future of flight, GE Aerospace has run simulations using the world’s fastest supercomputer capable of crunching data in excess of exascale speed, or more than a quintillion calculations per second.
Innovations in artificial intelligence are rapidly shaping our world, from virtual assistants and chatbots to self-driving cars and automated manufacturing.
A study led by researchers at ORNL could uncover new ways to produce more powerful, longer-lasting batteries and memory devices.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.