Filter News
Area of Research
- (-) National Security (4)
- Advanced Manufacturing (1)
- Biological Systems (1)
- Biology and Environment (30)
- Clean Energy (21)
- Computational Biology (2)
- Computational Engineering (2)
- Fusion and Fission (8)
- Fusion Energy (7)
- Isotopes (6)
- Materials (43)
- Materials for Computing (2)
- Mathematics (1)
- Neutron Science (22)
- Nuclear Science and Technology (15)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (1)
- Supercomputing (26)
News Topics
- (-) Advanced Reactors (1)
- (-) Biomedical (2)
- (-) Physics (1)
- 3-D Printing/Advanced Manufacturing (2)
- Artificial Intelligence (12)
- Big Data (6)
- Bioenergy (3)
- Biology (5)
- Biotechnology (1)
- Buildings (1)
- Chemical Sciences (2)
- Climate Change (5)
- Computer Science (19)
- Coronavirus (2)
- Cybersecurity (19)
- Decarbonization (2)
- Energy Storage (2)
- Environment (5)
- Exascale Computing (1)
- Frontier (1)
- Fusion (1)
- Grid (6)
- High-Performance Computing (4)
- Machine Learning (12)
- Materials (2)
- Materials Science (3)
- Nanotechnology (1)
- National Security (35)
- Neutron Science (4)
- Nuclear Energy (5)
- Partnerships (5)
- Quantum Science (1)
- Security (11)
- Simulation (1)
- Summit (2)
- Sustainable Energy (3)
- Transportation (2)
Media Contacts
A partnership of ORNL, the Tennessee Department of Economic and Community Development, the Community Reuse Organization of East Tennessee and TVA that aims to attract nuclear energy-related firms to Oak Ridge has been recognized with a state and local economic development award from the Federal Laboratory Consortium.
Nine student physicists and engineers from the #1-ranked Nuclear Engineering and Radiological Sciences Program at the University of Michigan, or UM, attended a scintillation detector workshop at Oak Ridge National Laboratory Oct. 10-13.
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.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.