Filter News
Area of Research
- (-) Electricity and Smart Grid (3)
- (-) Materials (86)
- (-) Neutron Science (30)
- Advanced Manufacturing (2)
- Biology and Environment (57)
- Biology and Soft Matter (1)
- Clean Energy (77)
- Climate and Environmental Systems (2)
- Computational Biology (1)
- Computational Engineering (2)
- Computer Science (11)
- Energy Frontier Research Centers (1)
- Functional Materials for Energy (1)
- Fusion and Fission (10)
- Fusion Energy (7)
- Isotopes (1)
- Materials for Computing (10)
- Mathematics (1)
- National Security (25)
- Nuclear Science and Technology (13)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (9)
- Sensors and Controls (1)
- Supercomputing (88)
News Topics
- (-) Advanced Reactors (5)
- (-) Artificial Intelligence (12)
- (-) Climate Change (5)
- (-) Grid (7)
- (-) Nanotechnology (43)
- (-) Physics (31)
- (-) Quantum Science (15)
- 3-D Printing/Advanced Manufacturing (27)
- Big Data (3)
- Bioenergy (15)
- Biology (10)
- Biomedical (18)
- Biotechnology (1)
- Buildings (5)
- Chemical Sciences (34)
- Clean Water (4)
- Composites (9)
- Computer Science (24)
- Coronavirus (11)
- Critical Materials (13)
- Cybersecurity (5)
- Decarbonization (9)
- Energy Storage (38)
- Environment (21)
- Exascale Computing (2)
- Fossil Energy (1)
- Frontier (4)
- Fusion (8)
- High-Performance Computing (6)
- Irradiation (1)
- Isotopes (13)
- ITER (1)
- Machine Learning (7)
- Materials (80)
- Materials Science (87)
- Mathematics (1)
- Microelectronics (1)
- Microscopy (27)
- Molten Salt (3)
- National Security (4)
- Net Zero (1)
- Neutron Science (108)
- Nuclear Energy (18)
- Partnerships (11)
- Polymers (18)
- Quantum Computing (4)
- Renewable Energy (1)
- Security (3)
- Simulation (1)
- Space Exploration (5)
- Summit (6)
- Sustainable Energy (14)
- Transformational Challenge Reactor (3)
- Transportation (19)
Media Contacts
Anne Campbell, a researcher at ORNL, recently won the Young Leaders Professional Development Award from the Minerals, Metals & Materials Society, or TMS, and has been chosen as the first recipient of the Young Leaders International Scholar Program award from TMS and the Korean Institute of Metals and Materials, or KIM.
In fiscal year 2023 — Oct. 1–Sept. 30, 2023 — Oak Ridge National Laboratory was awarded more than $8 million in technology maturation funding through the Department of Energy’s Technology Commercialization Fund, or TCF.
ORNL, a bastion of nuclear physics research for the past 80 years, is poised to strengthen its programs and service to the United States over the next decade if national recommendations of the Nuclear Science Advisory Committee, or NSAC, are enacted.
ORNL’s Fulvia Pilat and Karren More recently participated in the inaugural 2023 Nanotechnology Infrastructure Leaders Summit and Workshop at the White House.
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.
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.
ORNL is leading two nuclear physics research projects within the Scientific Discovery through Advanced Computing, or SciDAC, program from the Department of Energy Office of Science.
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.
The Department of Energy’s Office of Science has selected three ORNL research teams to receive funding through DOE’s new Biopreparedness Research Virtual Environment initiative.
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.