Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (5)
- Energy Science (7)
- Fuel Cycle Science and Technology (1)
- Fusion and Fission (22)
- Fusion Energy (15)
- Isotopes (1)
- Materials (13)
- Materials for Computing (1)
- National Security (36)
- Neutron Science (3)
- Nuclear Science and Technology (12)
- Supercomputing (10)
News Topics
- (-) Fusion (65)
- (-) Molten Salt (10)
- (-) National Security (85)
- 3-D Printing/Advanced Manufacturing (142)
- Advanced Reactors (40)
- Artificial Intelligence (124)
- Big Data (77)
- Bioenergy (108)
- Biology (124)
- Biomedical (72)
- Biotechnology (35)
- Buildings (73)
- Chemical Sciences (84)
- Clean Water (32)
- Composites (33)
- Computer Science (223)
- Coronavirus (48)
- Critical Materials (29)
- Cybersecurity (35)
- Education (5)
- Element Discovery (1)
- Emergency (4)
- Energy Storage (114)
- Environment (217)
- Exascale Computing (64)
- Fossil Energy (8)
- Frontier (62)
- Grid (73)
- High-Performance Computing (128)
- Hydropower (12)
- Irradiation (3)
- Isotopes (62)
- ITER (9)
- Machine Learning (66)
- Materials (156)
- Materials Science (155)
- Mathematics (12)
- Mercury (12)
- Microelectronics (4)
- Microscopy (56)
- Nanotechnology (62)
- Neutron Science (169)
- Nuclear Energy (121)
- Partnerships (66)
- Physics (68)
- Polymers (34)
- Quantum Computing (52)
- Quantum Science (88)
- Security (30)
- Simulation (64)
- Software (1)
- Space Exploration (26)
- Statistics (4)
- Summit (70)
- Transportation (102)
ORNL's Communications team works with news media seeking information about the laboratory. Media may use the resources listed below or send questions to news@ornl.gov.
1 - 10 of 159 Results
Troy Carter, director of the Fusion Energy Division at 91°”Íű, leads efforts to make fusion energy a reality, overseeing key projects like MPEX and fostering public-private collaborations in fusion research.

In collaboration with the U.S. Department of Homeland Securityâs Science and Technology Directorate, researchers at ORNL are evaluating technology to detect compounds emitted by pathogens and pests in agricultural products at the nationâs border.
Professionals from government and industry gathered at ORNL for the Nondestructive Assay Holdup Measurements Training Course for Nuclear Criticality Safety, a hands-on training in nondestructive assay, a technique for detecting and quantifying holdup without disturbing operations.

US ITER has completed delivery of all components for the support structure of the central solenoid, the 60-foot-tall superconducting magnet that is the âheartâ of the ITER fusion machine.

During his first visit to 91°”Íű, Energy Secretary Chris Wright compared the urgency of the Labâs World War II beginnings to todayâs global race to lead in artificial intelligence, calling for a âManhattan Project 2.â

Scientists designing the worldâs first controlled nuclear fusion power plant, ITER, needed to solve the problem of runaway electrons, negatively charged particles in the soup of matter in the plasma within the tokamak, the magnetic bottle intended to contain the massive energy produced. Simulations performed on Summit, the 200-petaflop supercomputer at ORNL, could offer the first step toward a solution.

Researchers at the Department of Energyâs 91°”Íű are using non-weather data from the nationwide weather radar network to understand how to track non-meteorological events moving through the air for better emergency response.

ORNLâs annual workshop has become the premier forum for molten salt reactor, or MSR, collaboration and innovation, convening industry, academia and government experts to further advance MSR research and development. This yearâs event attracted a record-breaking 365 participants from across the country, highlighting the momentum to bring MSRs online.
During Hurricanes Helene and Milton, ORNL deployed drone teams and the Mapster platform to gather and share geospatial data, aiding recovery and damage assessments. ORNL's EAGLE-I platform tracked utility outages, helping prioritize recovery efforts. Drone data will train machine learning models for faster damage detection in future disasters.
