Filter News
Area of Research
- (-) Clean Energy (54)
- (-) Isotopes (1)
- (-) Supercomputing (21)
- Advanced Manufacturing (3)
- Biology and Environment (24)
- Climate and Environmental Systems (1)
- Computer Science (2)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (1)
- Materials (26)
- Materials for Computing (5)
- National Security (8)
- Neutron Science (8)
- Nuclear Science and Technology (3)
News Type
News Topics
- (-) Artificial Intelligence (17)
- (-) Clean Water (1)
- (-) Composites (6)
- (-) Environment (22)
- (-) Polymers (5)
- (-) Sustainable Energy (28)
- (-) Transformational Challenge Reactor (3)
- 3-D Printing/Advanced Manufacturing (32)
- Advanced Reactors (4)
- Big Data (5)
- Bioenergy (15)
- Biology (7)
- Biomedical (9)
- Biotechnology (3)
- Buildings (10)
- Chemical Sciences (11)
- Climate Change (10)
- Computer Science (35)
- Coronavirus (8)
- Critical Materials (4)
- Cybersecurity (7)
- Decarbonization (12)
- Energy Storage (30)
- Exascale Computing (11)
- Fossil Energy (1)
- Frontier (14)
- Fusion (1)
- Grid (13)
- High-Performance Computing (17)
- Isotopes (8)
- Machine Learning (9)
- Materials (24)
- Materials Science (17)
- Mercury (1)
- Microscopy (8)
- Molten Salt (1)
- Nanotechnology (7)
- National Security (7)
- Net Zero (1)
- Neutron Science (12)
- Nuclear Energy (7)
- Partnerships (8)
- Physics (4)
- Quantum Computing (5)
- Quantum Science (11)
- Renewable Energy (1)
- Security (6)
- Simulation (5)
- Software (1)
- Space Exploration (1)
- Summit (15)
- Transportation (20)
Media Contacts
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 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
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 Hub & Spoke Sustainable Materials & Manufacturing Alliance for Renewable Technologies, or SM2ART, program has been honored with the composites industry’s Combined Strength Award at the Composites and Advanced Materials Expo, or CAMX, 2023 in Atlanta. This distinction goes to the team that applies their knowledge, resources and talent to solve a problem by making the best use of composites materials.
ORNL has been selected to lead an Energy Earthshot Research Center, or EERC, focused on developing chemical processes that use sustainable methods instead of burning fossil fuels to radically reduce industrial greenhouse gas emissions to stem climate change and limit the crisis of a rapidly warming planet.
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.
Yarom Polsky, director of the Manufacturing Science Division, or MSD, at the Department of Energy’s Oak Ridge National Laboratory, has been elected a Fellow of the American Society of Mechanical Engineers, or ASME.
Innovations in artificial intelligence are rapidly shaping our world, from virtual assistants and chatbots to self-driving cars and automated manufacturing.
Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.
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.