Filter News
Area of Research
- Advanced Manufacturing (2)
- Biology and Environment (9)
- Clean Energy (32)
- Computer Science (1)
- Electricity and Smart Grid (1)
- Fusion and Fission (14)
- Fusion Energy (4)
- Isotopes (3)
- Materials (29)
- National Security (13)
- Neutron Science (7)
- Nuclear Science and Technology (20)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (3)
- Supercomputing (25)
News Topics
- (-) Critical Materials (8)
- (-) Grid (23)
- (-) Machine Learning (23)
- (-) Microscopy (15)
- (-) Nuclear Energy (52)
- (-) Quantum Science (23)
- 3-D Printing/Advanced Manufacturing (48)
- Advanced Reactors (17)
- Artificial Intelligence (34)
- Big Data (21)
- Bioenergy (34)
- Biology (34)
- Biomedical (28)
- Biotechnology (8)
- Buildings (15)
- Chemical Sciences (29)
- Clean Water (7)
- Climate Change (41)
- Composites (7)
- Computer Science (62)
- Coronavirus (27)
- Cybersecurity (13)
- Decarbonization (31)
- Education (3)
- Emergency (1)
- Energy Storage (42)
- Environment (72)
- Exascale Computing (18)
- Fossil Energy (2)
- Frontier (20)
- Fusion (22)
- High-Performance Computing (36)
- Hydropower (3)
- Irradiation (2)
- Isotopes (19)
- Materials (61)
- Materials Science (53)
- Mathematics (4)
- Mercury (3)
- Microelectronics (2)
- Molten Salt (3)
- Nanotechnology (24)
- National Security (23)
- Net Zero (5)
- Neutron Science (62)
- Partnerships (24)
- Physics (27)
- Polymers (11)
- Quantum Computing (12)
- Renewable Energy (2)
- Security (6)
- Simulation (29)
- Software (1)
- Space Exploration (6)
- Summit (26)
- Sustainable Energy (41)
- Transformational Challenge Reactor (5)
- Transportation (33)
Media Contacts
Sreenivasa Jaldanki, a researcher in the Grid Systems Modeling and Controls group at the Department of Energy’s Oak Ridge National Laboratory, was recently elevated to senior membership in the Institute of Electrical and Electronics Engineers, or IEEE.
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.
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
Quantum computers process information using quantum bits, or qubits, based on fragile, short-lived quantum mechanical states. To make qubits robust and tailor them for applications, researchers from the Department of Energy’s Oak Ridge National Laboratory sought to create a new material system.
In June, ORNL hit a milestone not seen in more than three decades: producing a production-quality amount of plutonium-238
The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.
Speakers, scientific workshops, speed networking, a student poster showcase and more energized the Annual User Meeting of the Department of Energy’s Center for Nanophase Materials Sciences, or CNMS, Aug. 7-10, near Market Square in downtown Knoxville, Tennessee.
Cadet Elyse Wages, a rising junior at the United States Air Force Academy, visited ORNL with one goal in mind: collect air.
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.