Filter News
Area of Research
- (-) Supercomputing (23)
- Advanced Manufacturing (2)
- Biology and Environment (29)
- Clean Energy (65)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Computational Engineering (3)
- Computer Science (3)
- Fusion and Fission (12)
- Fusion Energy (11)
- Isotopes (3)
- Materials (28)
- Materials for Computing (5)
- Mathematics (1)
- National Security (9)
- Neutron Science (11)
- Nuclear Science and Technology (11)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Transportation Systems (2)
News Type
News Topics
- (-) Advanced Reactors (1)
- (-) Biomedical (9)
- (-) Climate Change (5)
- (-) Fusion (1)
- (-) Machine Learning (6)
- (-) Molten Salt (1)
- (-) Transportation (3)
- 3-D Printing/Advanced Manufacturing (3)
- Artificial Intelligence (13)
- Big Data (5)
- Bioenergy (6)
- Biology (5)
- Biotechnology (1)
- Buildings (1)
- Chemical Sciences (4)
- Computer Science (47)
- Coronavirus (7)
- Critical Materials (3)
- Cybersecurity (6)
- Decarbonization (1)
- Energy Storage (6)
- Environment (7)
- Exascale Computing (8)
- Frontier (13)
- Grid (3)
- High-Performance Computing (14)
- Isotopes (1)
- Materials (9)
- Materials Science (7)
- Microscopy (5)
- Nanotechnology (6)
- National Security (5)
- Neutron Science (7)
- Nuclear Energy (2)
- Partnerships (1)
- Physics (4)
- Polymers (2)
- Quantum Computing (9)
- Quantum Science (13)
- Security (4)
- Simulation (2)
- Space Exploration (2)
- Summit (20)
- Sustainable Energy (6)
Media Contacts
Researchers from institutions including ORNL have created a new method for statistically analyzing climate models that projects future conditions with more fidelity.
Scientists at ORNL used their expertise in quantum biology, artificial intelligence and bioengineering to improve how CRISPR Cas9 genome editing tools work on organisms like microbes that can be modified to produce renewable fuels and chemicals.
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.
Researchers from Oak Ridge National Laboratory and Northeastern University modeled how extreme conditions in a changing climate affect the land’s ability to absorb atmospheric carbon — a key process for mitigating human-caused emissions. They found that 88% of Earth’s regions could become carbon emitters by the end of the 21st century.
Two years after ORNL provided a model of nearly every building in America, commercial partners are using the tool for tasks ranging from designing energy-efficient buildings and cities to linking energy efficiency to real estate value and risk.
The Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory earned the top ranking today as the world’s fastest on the 59th TOP500 list, with 1.1 exaflops of performance. The system is the first to achieve an unprecedented level of computing performance known as exascale, a threshold of a quintillion calculations per second.
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.